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Officer injured while responding to mental health crisis call, Atlanta police say
A police officer is expected to recover after he was shot while exchanging gunfire with a man having a mental crisis in a southwest Atlanta neighborhood, officials say.
Atlanta police officer shot while responding to mental health crisis, suspect in custody
An Atlanta police officer is expected to recover after he was shot in the arm while responding to a mental health crisis in southwest Atlanta on Monday morning, city officials said.
BIG PIVOTS: The Nexus of Climate Change Politics in Colorado
Our Colorado mountain town is being hammered by climate change. We are responding in many ways…
As Asian business ownership declines, Tulsa commissioners pivot focus
The percentage of Asian Tulsans who own businesses is dropping. Asian Affairs commissioners are responding, shifting their focus from events to business resources.
Firefighters rescue kittens from Decatur business fire
Firefighters rescued a litter of kittens while responding to a business fire in Decatur Thursday morning.
As North Florida's need for healthcare providers grows, FSU Health is responding
As North Florida faces a growing shortage of healthcare providers, Florida State University is helping address the challenge through FSU Health, the
Amazon will train on Twitch streamers' content by default, unless they opt out
"If this was opt-in, nobody would opt in," Twitch CPO Mike Minton said on a livestream responding to user feedback. "That's honestly the answer."
How The Global Business Community Is Responding To Tariffs & The Strait Of Hormuz Impasse: Expert
When the Supreme Court blocked a large swath of his tariffs, Trump said his administration had "very powerful alternatives." Now we know what those alternatives are.
Commentary: Schools keep calling moms, reinforcing old assumptions and roles
The start of the school year brings a familiar list of responsibilities for parents: buying school supplies, keeping track of forms, coordinating transportation and responding to a steady stream of
Riverside County deputies shoot person during mental health call
Sheriff’s deputies in Moreno Valley shot an unidentified person while responding to a mental health crisis after, according to the Riverside County sheriff's office, they aimed a firearm at the deputies.
Sitting up straight may improve your mood and decision-making
A simple change in posture may subtly affect how people feel and make decisions. Participants who sat upright reported greater feelings of pride and took more successful risks in a virtual balloon game than those who hunched over. Most did not realize researchers had influenced their posture, helping rule out the possibility that they were merely responding to expectations. The results suggest workplace ergonomics could influence more than physical comfort.
Debt Digest | Federal Debt is a Health Care Problem
Welcome David Ditch to the Debt Dispatch! We are pleased to announce a new regular contributor: David Ditch will be joining the Cato Institute as a Policy Analyst for Budget and Entitlement Policy later this week. David has more than a decade of experience in fiscal policy issues, with a particular focus on federal spending. He previously worked at the Senate Budget Committee, the Heritage Foundation, and the Economic Policy Innovation Center. David’s areas of expertise include appropriations, transportation, agriculture, federalism, grantmaking, and policy options for deficit reduction. Originally from the Rochester, N.Y. area, David has a BA in Economics and Political Science from the University of Rochester and a MA in Political Management from George Washington University. David currently lives in Arlington, VA. You may have enjoyed his earlier guest posts: CBO: New Highway Bill Has More Spending, Taxes, and Deficits Trump Administration’s Proposed Changes to Federal Grants Highlight Problems of Big Government Here are this week’s reading links and fiscal facts: The federal debt is largely a health care problem. In a new report, the Congressional Budget Office and Joint Committee on Taxation find that “In 2026, federal subsidies for health insurance, net of related payments to the government, are projected to equal $2.4 trillion, or 7.4 percent of gross domestic product (GDP). In CBO and JCT’s projections, those subsidies grow by 65 percent, reaching $3.9 trillion, or 8.4 percent of GDP, in 2036. Subsidies for Medicare contribute most to that overall growth, increasing by $900 billion. Over the entire 2026–2036 period, federal subsidies for health insurance total $33.6 trillion.” Cato’s Michael Cannon emphasizes, “The long-term federal debt problem is a health care problem. […] Only two categories of federal outlays will grow faster than gross domestic product (GDP): health care subsidies and interest payments on the debt. The former is, therefore, the primary driver of the latter.” The bond market fears deficits, not the loss of tariff revenue. Responding to a New York Times essay claiming tariff revenue has grown too important for a future administration to unwind, Cato’s Kyle Handley argues: “Bond investors are not attached to customs duties as a line item revenue source. They care about the government’s overall fiscal position.” He continues, “tariff revenue is a side hustle. And the Trump administration has already promised to dole out the funds through schemes like tariff dividend rebates, farm subsidies, and pay-fors on tax cuts or other spending.” Furthermore, “tariff revenue is simply not large enough to transform the government’s fiscal trajectory.” Take net interest for example: it “reached $970 billion in fiscal year 2025, absorbing 18.5 percent of federal receipts. Customs duties accounted for only 3.7 percent of receipts—and that was before refunds (see Figure 2).” Handley concludes, “The real bond-market concern is a large and growing interest bill, persistent budget deficits, and a political system unwilling to bring spending and revenue into alignment.” Medicare’s spending growth is driven by more volume and utilization. A Congressional Research Service report finds that Medicare spending “grew at an average annual rate of 7.3%” from 1985 through 2025, and the trustees project health care expenditures will keep rising “faster than gross domestic product (GDP) in most future years.” Citing CBO, the report attributes Medicare’s projected 2026–2036 spending growth to “23% from higher enrollment, 31% from inflation, and 47% from the growth of inflation-adjusted spending per beneficiary. In other words**, the largest single driver of Medicare spending growth during the next decade is expected to be higher volume and intensity of health care services.”** Boccia and Thakur explain: “as the economy grows, Medicare spending tends to grow at least as fast—and often faster—because the program automatically pays the bill for more and more healthcare consumption by seniors, even as prices rise.” The Fed has little control over market interest rates. Cato’s Jai Kedia documents that the Fed has held its rate target steady since December, yet “nearly every rate Americans actually borrow at has climbed over the same stretch.” Kedia continues, “The Fed did nothing, and the cost of credit went up anyway. […] Markets spent these months repricing macroeconomic events such as sticky core inflation, a volatile energy market driven by the conflict in the Middle East, and global trade disrupted by tariffs, among others. None of that required a policy change to show up in borrowing costs because markets, not the FOMC, set prices.” He concludes, “Accurately priced borrowing rates will come from credible disinflation and disciplined budgets and from a Fed content to follow the economy rather than pretend it leads it.” Nearly half of US farm income comes from taxpayers. Former Reagan OMB director David Stockman notes that “in the most recently completed full year (FY 2025) farmer incomes in the US totaled $97.8 billion, but fully 42.7% or $41.8 billion of that amount came from taxpayers, not the marketplace. Nor is this some kind of one-year aberration. If we look at the most recent decade as a whole, total farm income posted at nearly $708 billion, but, as indicated, fully $322 billion or 45% of this came compliments of US taxpayers.” Cato’s Chris Edwards explains why so little of that income is market-earned: “Farmers are businesspeople, but the government shields them from just about every type of weather and market risk. Furthermore, just about every part of the agricultural industry is subsidized, including insurance, loans, marketing, research, export sales, and land improvements.” The Debt Dispatch is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
Panama: Haemophilus influenzae meningitis case reported in Veraguas Health Region
The Veraguas Health Region, located in the central-western region of Panama, confirmed a case of meningitis caused by the Haemophilus influenzae bacteria in a 12-year-old student from La Primavera School, diagnosed on July 29. The patient remains hospitalized, is receiving appropriate treatment, and is in stable clinical condition. The regional health director of Veraguas, Xavier A. Torres Domínguez, reported that, once the diagnosis was confirmed, the Ministry of Health (Minsa), in coordination with the Social Security Fund (CSS), immediately activated the epidemiological investigation and health response protocols established for this type of event. Canada: Haemophilus influenzae type B outbreak in Calgary As part of the actions implemented, the Epidemiology teams carried out the identification and monitoring of the patient’s close contacts, applying the corresponding preventive measures to reduce the risk of transmission and safeguard the health of the educational community. Health authorities explained that meningitis caused by Haemophilus influenzae is a bacterial disease that requires timely medical attention. In that regard, they urged the population to immediately seek medical attention if they experience symptoms such as high fever, severe headache, stiff neck, vomiting, drowsiness, or altered mental status. They also reiterated that vaccination is the main preventive measure against this disease, and therefore called on parents and guardians to verify that their children’s immunization schedules are complete, in accordance with the Expanded Program on Immunization (EPI). Outbreak News Today is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
Reno fire crews respond to business smoke call and recycling trailer blaze on Saturday
Reno firefighters had a busy start to the day, responding to separate calls involving smoke at a business and a recycling trailer fire.Fire crews were called to
The business of back-to-school
Back-to-school shopping is more than a seasonal ritual for families. It is one of the country's largest annual retail events, generating billions of dollars in spending.For retailers, it is a critical sales period. For economists, it offers an early snapshot of how Americans are responding to rising prices, shifting consumer confidence and broader economic uncertainty.
United Way fund available to help Ely-area small businesses impacted by wildfires recover
Small business owners can begin applying for the aid today, Friday, July 31, and all local organizations actively responding to the wildfires are eligible to request funding, too.
Cardinals’ Demote Promising Starter, Recall Veteran Reliever Before Cubs Game
The St. Louis Cardinals are demoting right-handed pitcher Hunter Dobbins to Triple-A Memphis. In a corresponding move, the team has selected the contract of Peter Strzlecki. Dobbins, 26, was acquired from the Boston Red Sox this past offseason. As it stands, he has a 3.74 ERA through his first 33.2 innings for the Cardinals. This season, Dobbins […] The post Cardinals’ Demote Promising Starter, Recall Veteran Reliever Before Cubs Game appeared first on HEAVY.
College Park business sees backlash after Rick Jackson visit
Metro Atlanta business owners are responding to online backlash after hosting visits from Republican gubernatorial candidate Rick Jackson.
Driver crashes into business in Cohasset - Boston News, Weather, Sports
COHASSET, MASS. (WHDH) - Emergency crews responded to a business in Cohasset on Friday after a driver crashed into a business in Cohasset.Crews responding toRead More
When It Comes to Fusion, Materials Matter
Fusion at high temperatures powers the sun and, if harnessed, could provide a potential source of energy here on Earth. But controlling fusion reactions has other benefits. The process also generates subatomic particles called neutrons that are used in a range of applications spanning medicine, research, and national security. Now, scientists at the University of California, Davis (UC Davis), and the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) have found that the materials surrounding a fusion reaction can dramatically increase how often it occurs, particularly at low energies where fusion is rare. The study was published July 18 in Nature Communications. Their approach sets up a way to study and engineer nuclear reactions within solid materials, opening a new field of “materials-driven fusion.” Instead of designing materials just to survive the harsh conditions of fusion, researchers might be able to design materials that boost the reaction in specific conditions, similar to the way catalysts speed up chemical processes. “It gives you a new knob to turn that you didn’t have before,” said Arun Persaud, head of the Fusion Science & Ion Beam Technology group in Berkeley Lab’s Accelerator Technology & Applied Physics (ATAP) Division. “If we understand this effect better, it opens the door to engineering new materials that would affect the fusion rate under certain conditions. Someday future progress might enable more compact and efficient neutron generators, which have all kinds of applications, like cargo screening, planetary science, and medical therapy and imaging.” In the experiment, researchers used two different methods to pack deuterium, a heavy form of hydrogen atoms that is often used in fusion, into thin foils of palladium and titanium. They then fired a beam of deuterium ions at the foils at different energies and measured how often fusion happened. Then they compared the rates from the different materials and methods with the “bare” fusion reaction (not in a material). The team found that fusion rates depended on how the deuterium was loaded into the metal foils. The biggest effect was at the lowest energies, below 2.5 kiloelectronvolts (keV), where theory predicts fusion rates drop off sharply. Instead, researchers found a surprising plateau: Some samples showed elevated fusion rates roughly a quintillion times higher than bare fusion reactions. (A quintillion is a 1 followed by 18 zeroes.) Researchers are not exactly sure why that’s happening, though they have some ideas and ways to test them. The electrons and defects within the material might partially shield repulsive electrostatic forces between deuterium nuclei, making it easier for them to get close together and fuse. Tuning the electronic structure, defects, and composition of materials could help make nuclear reactions happen more readily. “It comes down to better understanding the mechanism so that we can try to enhance it,” said corresponding author Jeremy Munday, a professor at UC Davis. “We’ve seen that we can increase fusion rates, but what is the limit? Can we bring it to lower temperatures or energies? There’s obviously a lot of interest and excitement about fusion, so if there’s something we can learn about the physics at these lower energy scales, maybe there’s something we can translate to other areas of nuclear science.” The team plans to explore a wider range of materials and continue probing the unexpected fusion plateau at lower energies. Their work establishes a reproducible experimental platform to study how solid materials influence nuclear reactions, creating a new area of research that links fusion science with materials science and chemistry. “The work shows conclusively that the material environment where fusion occurs at low temperatures is an active participant rather than a passive container,” said Cameron Geddes, director of ATAP. “That adds a new dimension to fusion research.” This work was funded by the U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E). ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.
Tesla investors want answers about a potential merger with SpaceX
Tesla investors are responding to rampant speculation about a mega-merger with SpaceX, which raised $86 billion in a blockbuster IPO last month.
Car drives into Jonesboro business, possible gas leak reported
Multiple crews are responding to a Jonesboro business after police say a car drove into the building
Woman shot in leg inside South Shore business, CPD says
Chicago police said responding officers found the victim with a gunshot wound to the leg inside the business.
N.H. lawmaker clocked at 107 mph asserts ‘legislative privilege’
The state representative likened her situation to that of an EMT or police officer responding to an urgent call. What was her emergency? She hasn’t said.
Austin Fire Department responds to smoke coming from roof of S Austin business
The Austin Fire Department stated Sunday evening that they were responding to a business under construction in South Austin that reportedly had smoke coming fro
Celtics Teammate Makes Feelings Clear on Jaylen Brown After Trade
The Boston Celtics have spent the past week responding to the Jaylen Brown trade from every corner of the organization. Brad Stevens laid out the reasoning. Joe Mazzulla spoke about trust and gratitude. Jayson Tatum reflected on what it felt like to lose a nine-year teammate.On Friday in Las Vegas, more voices from inside the […] The post Celtics Teammate Makes Feelings Clear on Jaylen Brown After Trade appeared first on HEAVY.
Trump threatens Iran after open calls for the U.S. leader's assassination
President Donald Trump made the threat on Truth Social, responding to Iranian threats against him.
Savannah liquor license dispute: Business owner, city leaders respond
A dispute over liquor licenses that divided Savannah City Council during its July meeting is continuing, with a local business owner and city leaders responding.
A safe return home: Tackling stigma on Uganda's Ebola frontline
As Uganda works to contain an Ebola outbreak that is also affecting neighbouring Democratic Republic of the Congo (DRC), health workers are doing more than responding to a deadly virus. They are helping families navigate fear, misinformation and stigma.
Google Gemini Spark Comes to Mac With Local File Automation
Google today launched Gemini Spark for its macOS desktop app, allowing the AI agent to automate tasks involving local files and desktop workflows. Google announced the update today, adding a dedicated Spark tab to the sidebar of the Gemini app for macOS. The feature allows the AI agent to take action on files stored locally on a user's computer rather than just responding to questions in a chat window.
How the Chicago Bulls retooled their sponsorship business to meet CMO data demands
As sports sponsorship spending rises, CMOs are looking for hard evidence to justify their deals. Teams and franchise owners are responding, but there’s competition.
The impact of club sports on student experience in higher education
Authors: Ryan Savitz1, Divit Gupta2, Jared Ward3, Andrew Bjorkelo1 1Neumann University 2Conestoga High School 3Brigham Young University Corresponding Author: Ryan Savitz savitzr@neumann.edu …
New study suggests health damage from exposure to Ohio toxic train spill
Research finds immune systems still ‘responding to toxic chemical exposures’ related to East Palestine derailment
Sweden and WHO launch new long-term initiative to transform Ukraine’s health system
WHO and the Swedish International Development Cooperation Agency (Sida) have launched a new multi-year cooperation project to support the long-term recovery and transformation of Ukraine’s health system. The new project, “Ukraine’s Health System Transformation Initiative: Strengthening Health Governance, Health Financing and Service Delivery for Long-Term Recovery”, was launched at the Ukraine Recovery Conference 2026 in Gdansk, Poland on 26 June, and will run from June 2026 to 2029. Sweden will contribute approximately US$ 26 million (240 million Swedish krona) to support this project. This contribution forms part of Sweden’s broader support to Ukraine through the Team Europe approach, which brings together the European Union, its Member States, and key partners such as the European Commission’s Directorate-General for Enlargement and Eastern Neighbourhood and Enabel, and WHO as lead health agency, to support Ukraine’s recovery, reform agenda and European integration.“Ukraine’s health recovery cannot be measured only by what is rebuilt, but by whether people can count on the health system when they need it most. The scale of the task is immense, with health reconstruction and modernization needs estimated at US$ 19.4 billion over the next decade. Sweden’s US$ 26 million contribution to Ukraine’s Health System Transformation Initiative is a timely investment in the institutions, financing and services that will support Ukraine’s long-term recovery and European integration. WHO remains a trusted partner of the Government of Ukraine in advancing this process. I am deeply grateful to Sweden for its consistent support and partnership,” said Dr Hans Henri P. Kluge, WHO Regional Director for Europe. More than 4 years of war have placed unprecedented pressure on Ukraine’s health system, creating 3 interconnected challenges. The first is responding to the immediate consequences of the war and the urgent health needs of the population. The second is recovering and modernizing health services today. The third is continuing reforms and aligning the health system with European standards in the context of Ukraine’s future accession to the European Union. The war has led to large-scale population displacement, an increasing need for trauma care and rehabilitation, and shortages of health workers. High out-of-pocket payments in Ukraine make access to health services more difficult. Around 46% of total health expenditure is paid directly by individuals, placing a significant financial burden on many households and underscoring the need for reforms in health financing. Older people, persons with disabilities, women, children and veterans continue to face the greatest difficulties in accessing health services. “Ukraine is demonstrating that health system transformation can continue even during war. Ukraine is also continuing to align its health system with European norms and standards. WHO is committed to supporting Ukraine on this journey. We provide technical support, help coordinate partners’ efforts and support the institutional changes needed to strengthen the system. We are grateful to Sweden for its support. Through this partnership, we can help Ukraine build a more resilient, accessible and people-centred health system,” said Dr Jarno Habicht, WHO Representative in Ukraine. About the Health System Transformation InitiativeThe new initiative will support Ukraine through 3 interconnected areas: strengthening governance and coordination of health sector reforms through more inclusive coordination platforms and structured policy dialogue; transforming service delivery by reinforcing a primary health care-centred model that integrates family medicine, nursing and midwifery; and improving financial sustainability by supporting reforms that ensure the long-term viability of the national health system and reduce out-of-pocket payments for households. Overall, these reforms are expected to make the health system more coherent and easier to navigate, improve the quality and continuity of care, and ensure more equitable access to services, particularly for those who need them most. They will also support Ukraine’s progress towards a more modern health system aligned with European standards. “We are convinced that long-term recovery is not possible without strong, high-quality, person-centred health services that are accessible to everyone. Our partnership with WHO is designed to support deep and lasting systemic changes. Investments in human capital especially autonomous midwives, whose role for maternal, newborn and adolescent sexual and reproductive health cannot be understated, stronger governance, digital transformation and the financial sustainability of the health system are investments in Ukraine’s future. We are proud to support this process,” said Malin Perhult, the Head of the Ukraine Unit at Sida. Focus throughout implementation will be given to the most vulnerable population groups, including older people, women and children, and persons with disabilities, who have been affected by the war and face greater health-care needs. The initiative will be implemented in close cooperation with the Ministry of Health of Ukraine, the National Health Service of Ukraine, the Public Health Centre of Ukraine, regional authorities and international partners. This project will help Ukraine move towards a system where everyone can access the health care they need. It will strengthen primary care, make the health finance system more stable and predictable, and reduce the out-of-pocket costs that Ukrainians face when using health services. As a result, the Ukrainian health system will become more aligned with European standards and more sustainable in the long run.
Bell County sheriff’s deputies shoot man while responding to mental health crisis call
The Bell County Sheriff’s Office says deputies shot and injured a suspect Friday afternoon while responding to a reported violent domestic disturbance east of Holland.
Broncos sign OL Reid Holskey and DB Blake Cotton
According to multiple reports, including The Denver Post’s Parker Gabriel, the Denver Broncos are signing offensive lineman Reid Holskey and defensive back Blake Cotton. Both players participated as tryout players during the Broncos’ most recent minicamp practices and have now earned themselves a contract from the Broncos. There have been no corresponding moves announced as […]
She called police in an emotional crisis. She says the responding officer raped her.
A Westchester County woman has filed a lawsuit against a former Harrison Township Police Lieutenant, alleging he sexually assaulted her after she called police headquarters during a mental health crisis in August of 2023.
Authorities respond after car crashes into massage business in Hallandale Beach
Authorities were responding after a car crashed into a massage business in Hallandale Beach on Tuesday.
SkinVision Pro Launches Globally at HLTH Europe: AI-powered Skin Health Platform Connected To Healthcare Providers
SkinVision today launched SkinVision Pro, a platform that connects medical practices directly to the SkinVision Service, an AI-powered solution that provides a risk indication for skin spots. The announcement was made at HLTH Europe, responding to growing demand from medical practices seeking to integrate skin assessment results into their clinical workflow. The launch comes as skin cancer incidence has tripled over the past two decades, dermatology wait times reach up to six months in many heal
Firefighters called to equipment fire at Wilmington business
New Hanover County Fire Rescue crews are responding to a piece of equipment that caught fire at a business on N. Kerr Avenue Monday afternoon.
Is SMIC N+3’s Metal Pitch Smaller than Intel 18A’s?
Almost four years ago, we published that SMIC had started shipping 7 nm (N+1) chips. Now, SMIC is shipping its third-generation 7 nm (N+3) process in Huawei’s Kirin 9030, with a minimum metal pitch of 32.5 nm, about 10% tighter than the 36 nm minimum metal pitch shipping in Intel’s latest Panther Lake CPUs on 18A. The headline is true, but incomplete cherry picked metric. N+3 reaches the density of TSMC N6 through aggressive DUV multi-patterning and design-technology co-optimization (DTCO), but it pays for that in complexity, efficiency and process control. We found this and more in our reverse engineering and teardown where we cover SMIC’s N3 process technology, Huawei’s packaging, memory, architecture, and more. SemiAnalysis has been building a state-of-the-art teardown lab in Oregon capable of analyzing the world’s most advanced and important chips over the last year and half. We have already generated revenue on advanced datacenter chip teardowns including our recent reverse engineering of a major TSMC customer’s COUPE CPO optical engine + EIC 3D stack. This is the first public report from the SemiAnalysis Teardown Engineering & Evaluation Lab, or STEEL for short. The lab is aggressively scaling up and out and we’re excited to announce it publicly. This is a bit of inconvenient timing for TechInsights as they are private equity owned and currently being sold while having enjoyed virtually no credible competition for decades. This has led to TechInsights underinvesting in CAPEX. SemiAnalysis exceeds TechInsights in revenue despite no venture or private equity ownership and being founded only 6 years ago. Because we have no external investors and are founder led, we move faster, build faster, and we can release client chip teardowns for free regularly, while focusing on datacenter for our major clients. Here’s the first public image from our lab, the HiSilicon Kirin 9030 Pro SoC: This report will detail our teardown of the Kirin 9030 and our findings on SMIC’s N+3 process, the most advanced in China. For comparison, we’ll show our teardown of the MediaTek Helio G99, made on TSMC N6. Through this comparison, we can look at the effect of export controls – SMIC N+3 and TSMC N6 are comparable nodes, but one is heavily export-controlled, the other free to use the West’s most advanced equipment. Here we see both China’s progress and constraints. SMIC N+3 reaches TSMC N6-class logic density, but it requires far more aggressive DUV multi-patterning, so it does not match N6 on process maturity or cost. The Kirin 9030 Pro performs similarly to three-year-old Android flagships, and trails far behind the current flagship SoCs from Apple, Qualcomm, MediaTek, and Samsung. The efficiency gap is even wider. Export controls have not stopped Huawei and SMIC from shipping advanced silicon, but they have forced a different path. Without EUV, SMIC is leaning harder on DUV multi-patterning, DTCO, and increasingly complex integration. The roadmap continues forward through tighter design rules and backside power, but each step adds cost and process risk. Huawei’s τ scaling and LogicFolding show another path: stacking active logic and recovering density through advanced packaging and system-technology co-optimization (STCO). To understand the Kirin 9030, we must first understand Huawei’s SoC history. HiSilicon is Huawei’s chip design arm, responsible for the Kirin smartphone SoCs, Kunpeng server CPUs, Ascend AI accelerators, and switch/router networking silicon. Before export controls, Huawei was TSMC’s largest customer – the only customer on TSMC’s first EUV node, N7+, and among the first on N5, alongside Apple. That ended in late 2020. Huawei switched to Qualcomm SoCs in its flagship smartphones, though export controls limited them to 4G-only variants. In late 2023, Huawei returned to in-house silicon with the Kirin 9000s, a successor to the Kirin 9000, fabricated on SMIC N+2 instead of TSMC N5. In the following years, they released the Kirin 9010 and 9020 on the same N+2 process. These chips used Huawei’s in-house TaiShan CPU cores and Maleoon GPU. We have not torn down a Kirin 9020 ourselves, so the predecessor die shot is from Kurnal. The die shots show how Huawei spent its silicon budget: which functional blocks are where, and how their areas compare to the predecessor. First, a quick guide to the major blocks on the die. The total die area is nearly identical, but the 9030 uses that area more aggressively. A denser process lets Huawei fit an extra middle CPU core, more GPU and NPU cores, and larger caches into the same footprint. In contrast, the Helio G99 is a much smaller, low-cost SoC, built for budget smartphones rather than a flagship device. While the Kirin 9030 is ~140 mm², the G99 is only ~29 mm², roughly one-fifth the area. The underlying TSMC process technology, however, is directly comparable as a baseline for analyzing SMIC’s. The Kirin 9030 is an evolutionary refresh, not a clean-sheet design. Its CPU, GPU and NPU cores carry over the 9020’s families, and the gains come from three levers: the SMIC N+2-to-N+3 process step, DTCO and floorplan work, and incremental microarchitecture. Area is where the first two show up, and the 9030 scales well here. Performance and efficiency are the harder test. Huawei’s design holds up better than its node would suggest, but the chip still trails, both because N+3 sits behind the leading-edge nodes and because its cores, while competent, remain a few generations behind the newest designs. The new prime core is an incremental update. The main changes are a 10% frequency increase from 2.5 GHz to 2.75 GHz and a doubling in the L2 cache from 1 MiB to 2 MiB. Despite the increased cache, the core size decreased by 7.6%. Excluding the private L2 cache, the core size decreased by 21%. This is a large reduction for an incremental node. Compared with the TaiShan New V120 core in the Kirin 9020, the Kirin 9030’s middle core is almost unchanged architecturally, yet each core shrinks by ~22%. Most of that comes from the move from N+2 to N+3, with layout likely accounting for the rest. Visually, the most noticeable change is the increase from 3 middle cores to 4. There is also a 20% increase in the shared L3 cache of the big cluster. This helps to improve multi-core performance without sacrificing much in terms of area. Even with each core shrinking, the big CPU cluster’s total area is essentially unchanged. The per-core savings went back into an additional middle core and larger caches. The tiny cores shrank less than the prime core (excluding its L2 cache) and less than the middle cores. This is likely because fixed overhead is a larger share on a small core. We cannot resolve any architectural changes from the die shot alone, but the per-clock and efficiency gains shown below point to more than pure process and layout scaling. The area reduction was offset by a doubling of the shared L2 cache from 2 MiB to 4 MiB, leaving the total tiny CPU cluster area slightly larger. Area is the easiest improvement to see from a die shot, but it is only one part of PPA (power, performance, area). For modern logic, power and performance matter just as much, and often more. Since Dennard scaling broke down in the mid-2000s, voltage and frequency have not scaled in step with transistor dimensions, so each node has had to fight harder for gains in performance and efficiency. The starkest comparison is not Kirin 9020 versus Kirin 9030 Pro. Apple’s efficiency cores run circles around Huawei’s prime core. Apple’s low-power core delivers 20% higher integer performance while drawing only 1 W, compared with 4.5 W for Huawei’s prime core. N+3 matches TSMC N6, but N6 is several generations old. Apple and Qualcomm build on N4 and N3P, which are denser and sit on a better voltage-frequency curve, giving them a larger transistor budget and more performance per watt. The 9030’s own cores did improve. The middle and tiny cores gained 17% and 14% in per-clock integer performance over the 9020, with floating-point flat on the middle core and up 11% on the tiny. The tiny core improves cleanly, with performance rising while power falls and efficiency increases by 45% in integer and 24% in floating point. The middle core is mixed: integer performance rises but power rises faster, cutting integer efficiency by 7%, while lower power lifts floating-point efficiency 16%. Per-clock gains at the same or lower frequency are microarchitectural, so the cores are tuned, not just shrunk. Both also failed to hold their rated maximum frequencies, pointing to thermal, power, or stability limits. Per clock, the middle core sits around Arm Cortex-A720 and the tiny core near the Cortex-A520; absolute performance trails because Huawei clocks them much lower. The prime core is roughly Cortex-X2 class per clock, a 2021 design. Apple’s 2020 M1 Firestorm core is still 35% higher per clock and 57% faster in absolute integer performance at a similar 4.5 W. The current leading edge is further ahead again: the Apple M5 P-core is 60% higher per clock and 2.7× faster, the Arm C1 Ultra 45% higher and 2× faster. Matching older high-end cores per clock is a genuine design achievement. What Huawei cannot match is the voltage-frequency curve and transistor budget of leading-edge nodes, which let Apple, Qualcomm and others spend more transistors in the same area on wider cores, larger caches and deeper buffers while running at lower voltage. Huawei’s LogicFolding roadmap is one answer, stacking active logic to recover density and shorten signal paths. We return to it later. The GPU compute units (CUs) changed more visibly than the CPU cores, moving to a more rectangular layout for both the arithmetic logic unit (ALU) clusters and the CU overall. Even with ray-tracing support added, a CU shrank ~28%. However, that shrink is offset by the increase from 4 to 6 CUs and the area outside the CUs grew 33%. Overall, the GPU cluster is larger by ~10%. The GPU is where Huawei makes its biggest gains. The Maleoon 935 is not competitive with current flagships, but it is a large step up from the 920 and reaches older-flagship territory. In 3DMark it is 70% faster in Wild Life Extreme (WLE) and 79% faster in Steel Nomad Light (SNL) than the 920; with 11% higher clocks and 50% more CUs, the ~67% theoretical uplift roughly matches WLE and is beaten by SNL. It edges ahead of the Snapdragon 8+ Gen 1 in WLE and SNL, and the Dimensity 9200 and Apple A16 in WLE, but stays far behind newer parts: the Snapdragon 8 Elite Gen 5 and Dimensity 9500 are ~2.4–2.6× faster in WLE and ~3.2× faster in SNL. The Maleoon 935 is Huawei’s first GPU with hardware-accelerated ray tracing; there it lands slightly ahead of the Exynos 2200, and on par with the Apple A16, with current flagships up to 3.7× faster. The Neural Processing Unit (NPU) saw the largest structural changes of any block, moving from a Lite and a Tiny core in the Kirin 9020 to a Lite and two Tiny cores in the Kirin 9030. Both core types also show significant layout changes. This is a reversal in Huawei’s NPU design. The Kirin 9000 5G, its last flagship chip on TSMC N5, used two Lite and one Tiny core. The series of SoCs on SMIC N+2 moved to one Lite and one Tiny core, likely for area savings. With the Kirin 9030, Huawei has shifted back toward a larger multi-core NPU cluster, but with the additional area going to a Tiny core rather than a Lite core. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Interested in joining us on this ride and think you can be a difference maker? Check out our Careers page. Before diving into the process stack, the package and memory are worth separating from the SoC itself. The Pro variant of the Kirin 9030 carries 12 GB of Samsung DRAM, with two stacks of four dies each. The dies were identified as the K4L2E165YD, a 12 Gb LPDDR5X-9600 device fabricated on Samsung’s 1a node, the fourth generation of its 10 nm-class DRAM after 1x, 1y and 1z. 1a has shipped in volume since 2022, so this is current memory rather than older-node inventory. The 16 GB Pro Max variants we obtained were found with both CXMT and Samsung packages. The CXMT package is marked CXDD7JEDM, with two stacks of four dies, packaged in week 45 of 2025. The inferred die dimensions from X-ray computed tomography (CT) are consistent with a known density of ~0.3 Gib/mm² for the CXMT G4 process, roughly equivalent to other manufacturers’ 1z processes. The Kirin 9030 uses a typical integrated package-on-package (iPoP) stack: multiple DRAM dies in a memory package sit above an organic redistribution layer (RDL) interposer, which sits above the SoC and package substrate. The full package is then mounted to the printed circuit board (PCB) through ball-grid array (BGA) solder bumps. The memory package substrate is a thin bismaleimide-triazine (BT) laminate carrying the LPDDR5X stack. The organic RDL interposer over the SoC routes the PoP signals around the die and carries possible dummy thermal copper pillars. The package substrate, a thicker Ajinomoto Build-up Film (ABF) build-up over a BT core, fans the flip-chip bumps out to BGA pitch and embeds the power planes. The whole stack is organic. The only silicon is the SoC and the LPDDR5X dies; there is no silicon interposer. Keeping it all-organic brings the package’s coefficient of thermal expansion (CTE) close to the PCB’s, reducing board-level warpage, and avoids the cost of a silicon interposer the SoC’s bandwidth does not need. In an iPoP stack, the memory package connects to the organic RDL interposer through an array of solder bumps. Underfill fills the gap around those bumps, adding stiffness and protecting the joints from mechanical stress. The Pro and Pro Max variants differ here, which we cover behind the paywall. The die shot and architecture tell us how Huawei allocated its silicon budget. The process tells us what SMIC can manufacture. We use the Helio G99 as the process reference for TSMC N6. Both SMIC N+3 and TSMC N6 are evolutions of previous 7 nm-class nodes. We used targeted TEM cross-sections through logic and memory regions, imaged in both fin-cut and gate-cut directions. Each cross-section caption gives its horizontal field width (HFW), the real width of the imaged area. We start at the transistor fins, then move up through standard cells, local interconnect, and SRAM. SMIC has not overtaken Intel or TSMC. It uses aggressive DUV scaling and DTCO to reach N6-class density, but that density doesn’t translate into comparable performance and efficiency, for two reasons: the node gap to leading-edge nodes, and Huawei’s core designs. Fin Profile One of the most important knobs in a FinFET process is the fin profile: the shape of an individual fin and the channel where current passes from source to drain. The ideal fin is tall, narrow, and nearly vertical. A taller fin increases effective channel width, while a narrower fin improves electrostatic control by thinning the body the gate must control. Push either too far, and the process pays for it: weaker drive current, fragile fins, taper, footing and line-edge variation that hit yield and device variability. The Intel 22 nm, 14 nm, and 10 nm fin cross-sections show how FinFET nodes have improved over time. 22 nm fins were a first-generation structure, relatively short, wide and strongly tapered. The shape limits current density and reduces gate control uniformity across the height of the fin. At 14 nm and 10 nm, Intel pushed the fins taller and narrower while also making the sidewalls more vertical. Rather than shrinking the device, these changes increase the effective channel width per fin and improve electrostatic control. The trade-off is that taller fins at tighter pitches are much more difficult to manufacture. Now, let’s compare the Helio G99 on TSMC N6 with the Kirin 9030 on SMIC N+3. Both processes are in the same class, with fin pitch of 30-32 nm on N+3 and 34 nm in our N6 cross-section. The pitch for N6 is especially interesting as N7’s HD library is generally listed with a 33 nm fin pitch, and N6 did not shrink pitches directly. Its density gains came from DTCO instead of tighter pitches. The 34 nm pitch was stable across our sampled region and serves more as a comparison against the SMIC N+3 we have not investigated further. Pinning down N+3’s fin patterning scheme takes more than one core unit. The CPU cores show a dense ~32 nm pitch, with the pitch between N-P fin pairs alternating between 78 and 88 nm. Logic alone may be consistent with dual-pitch mandrels of 120 and 110 nm, but this is a complex and unusual approach. Combining the pitch from the the 8T SRAM, which has more complex repeat unit, with the CPU core sequence allows us to reverse engineer the patterning steps with more confidence. As both the logic and SRAM should share the same base grid, a single CD mandrel lithography pattern with 128 nm pitch undergoing SAQP produces a die-wide ~32 nm grid (128 nm/4), which supports the pitch sequencing seen in both logic and SRAM cells. In the sampled cross-sections, N+3 shows a taller, narrower, higher-aspect-ratio fin than N6. The measured fin aspect ratio is ~9.5:1 on N+3 versus 7.8:1 on N6. N+3 also shows less top rounding, with an estimated radius of ~2 nm, compared with 2.8 nm on N6. Even though the fin widths differ, the ratio of top rounding to fin width tells the same story, with N+3 at 0.37 and N6 at 0.44. In a geometric sense, lower is better; a perfectly rectangular fin would have no top-rounding penalty. These are single-digit-nanometer features measured from a handful of cuts, so treat the absolute numbers as approximate. The important result is the relative gap: N+3’s fins are consistently taller, narrower and less rounded than N6’s. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Interested in joining us on this ride and think you can be a difference maker? Check out our Careers page. Standard Cell A standard cell is the basic building block of chip layout: a fixed-height row pairing one NMOS and one PMOS transistor that share a gate, tiled in a grid to build logic blocks. The key dimensions are contacted gate pitch (CGP), cell height (CH), fin count, and the lower-metal routing grid. To measure density, we use the Bohr metric: a weighted average of NAND2 gate area (60%) and scan flip-flop area (40%). This represents a realistic mix of combinational and sequential logic. This metric has its limitations, especially for complex cell layouts like TSMC’s FinFLEX, which alternates cells with different fin counts. Even so, it is the best metric for a pure process-level comparison. Another important measurement is the fin pitch; it refers to the distance between two fins of the same transistor. In a FinFET process, multiple fins are used in each transistor to increase the drive current and thus performance. TSMC N6 ships both a high-density (HD) library with 2 PMOS and 2 NMOS fins per cell, and a high-performance (HP) library with 3 of each. More fins under the shared gate mean more effective channel width. HP cells switch harder at the cost of area. Designers mix the two on a die, primarily spending HP cells on timing-critical paths, and matching their PPA targets. In the Cortex-A55 core of the Helio G99, we found a cell height of 240 nm for the HD cell. MediaTek has used HD cells in the G99 to minimize die size and thus cost. As an SoC for budget smartphones at ~$100, this is essential. By contrast, we found only one library in the Kirin 9030, with 2 NMOS and 2 PMOS fins. This suggests a narrower library strategy than TSMC N6, where both HD and HP libraries are widely used. This likely reflects the smaller customer base and the more constrained domestic design and electronic design automation (EDA) ecosystem. In all three CPU cores of the Kirin 9030, we found cell heights of 228 nm, 5% smaller than on N6. This is also a reduction of 9.5% over SMIC N+2’s cell height of 252 nm. SMIC N+3 and TSMC N6’s HD library both feature a CGP of 57 nm. For SMIC, this is a 9.5% shrink over N+2. In the past, CGP and cell height alone may have been enough to compare transistor density. Now, however, we must consider scaling boosters and DTCO as well. SMIC’s density gain does not come from EUV. It comes from using every available DTCO booster aggressively. First is fin depopulation: reducing the number of NMOS and PMOS fins in each cell. The first FinFET nodes started with 3 or 4 fins for each transistor. SMIC N+3 and TSMC N6 HD both use only 2 fins per transistor, trading drive strength for density. Next is contact over active gate (COAG). By landing the gate contact directly over the active gate, instead of out over the isolation region, the cell height drops. N+3 integrates COAG while N6 does not. Our N+3 gate-cut cross-sections indicate COAG, with the gate contact sitting over the active region, while N6 shows an off-gate contact. Last is single diffusion break (SDB). Diffusion breaks are inserted between cells in the same row to provide electrical isolation, but they also introduce local layout effects (LLE), layout-dependent shifts in electrical characteristics. In the past, a double diffusion break was used, consuming the space of two CGPs. SMIC N+3 and TSMC N6 instead use SDB, saving area but increasing LLE sensitivity. This must be controlled at the process level and accurately modeled in the process design kit (PDK) so that EDA tools can account for it. Overall, SMIC N+3 has a transistor density of 113.4 MTr/mm², slightly above TSMC N6 at 107.7 MTr/mm². Even without EUV, SMIC has achieved density beyond TSMC’s mature N6 node which utilizes EUV. Metal Stack The smallest critical dimension in the teardown is M0; SMIC N+3 uses a 32.5 nm local metal pitch. That is smaller than the 36 nm M0 pitch on Intel 18A in Panther Lake. However, this does not mean that SMIC has a better process than Intel 18A or TSMC N3P. M0 is a local intra-cell routing layer. Its usefulness depends on the full interconnect stack: M1 and M2 pitch, track count, via and line resistance, design rules, mask count, overlay control, and routing flexibility. The 32.5 nm M0 is consistent with self-aligned quadruple patterning (SAQP), whose four-population line-width loading we read coarsely as alternating widths of 21.5 to 24 nm; M1 and M2, at 38 and 40 nm, are consistent with self-aligned double patterning (SADP), a single A/B split. On TSMC N6, M0, M2, and M3 sit at a relaxed ~40 nm and are consistent with SADP-class double patterning, with no need for quadruple patterning. That said, we measure M2 for example at ~43 nm, likely inflated by sparse routing. We do not assign any specific layer to EUV from our cross-sections; the distinction we can draw is double versus quadruple patterning, not lithography wavelength. Transistor-level density in the front-end-of-line (FEOL) sets an upper bound, but the design is ultimately limited by what the interconnect stack can route. The lowest metals are the most important for standard-cell density, but the semi-global and global layers determine how usable that density is at the block and chip level. Two axes are commonly used for chip cross-sections: the fin-cut and the gate-cut. The micrograph above is a fin-cut and shows metals 0 through 3. This axis lets us see the even-numbered metals, with M0 right above the fins. There are two kinds of M0 lines. The first are the power rails; these are wide wires for the VDD and VSS running horizontally at the top and bottom edges of each standard cell. The wide wires measure 55 nm across, more than double the other M0 lines. Their width minimizes resistance and reduces IR drop. The second kind are intra-cell wires, short segments within the cell that connect terminals to M1. These have alternating widths between 21.5 and 24 nm. The M0 pitch is 32.5 nm, a 19% reduction versus N+2 and N6. At this pitch, DUV patterning requires more aggressive multi-patterning, increasing mask count, overlay sensitivity, process complexity and cost. M0 is below what a single DUV-defined spacer (SADP) can resolve, so SMIC cascades a second spacer step (SAQP). The cross-section reflects the cost: the M0 trenches are visibly more re-entrant (narrower at the bottom than the top) than M1 or M2 on the same chip and carry a bright barrier-rich foot where the trench meets the etch-stop layer. That shape is partly the intended damascene profile, as a slightly narrow bottom helps void-free copper fill, but its magnitude at M0 is driven by the tight pitch and the higher trench aspect ratio. Intel 18A supports an M0 pitch of 32 nm, although Panther Lake has only shipped with a looser 36 nm pitch. This is due to Intel’s heavy usage of HP libraries. Among leading-edge nodes, 18A has the loosest M0 pitches due to PowerVia. With power routing moving to the backside, congestion is reduced, and the entire front-side metal stack can be used for signal routing. M2 is the first true inter-cell routing layer. It runs horizontally like M0 but spans across multiple cells to carry block-level signals. The M2 pitch sets the cell’s track height – the number of M2 tracks that fit between the VDD and VSS rails, defining what the library calls a 6-track or 7.5-track cell. This layer is the most important, limiting the routing of entire blocks. SMIC N+3 features a 5.7-track cell. The M2 pitch is 40 nm, a 5% decrease over N+2 and the same as N6. This shrink keeps the pitch at the edge of what is possible with double patterning. Future nodes will need to increase the number of masks for M2 as reducing the number of tracks is much harder due to the limitations in routing. The micrograph above is in the perpendicular direction, the gate-cut, and shows metals 0 through 4. This allows us to see and measure the odd-numbered vertical metal layers. The M1 pitch is 38 nm, 9.5% less than N+2 and 33% less than N6. The M1-to-gate ratio matters because it sets local routing flexibility. N+2 and N+3 use a 3:2 ratio, while N6 uses a 1:1 ratio, explaining the huge differences in M1 pitch. The more M1 lines there are compared with the gates, the more flexibility there is for power and signal crossing within the cell. Routing flexibility enables more complex and better cells. Clean fractional ratios are also preferred as a grid is periodic and improves layouts. The 3:2 ratio gives SMIC more local routing flexibility than a strict 1:1 grid, but it also complicates layout and patterning. This is a DTCO choice, with SMIC increasing process complexity to recover density and routability without EUV. This 3:2 ratio is not very popular in the leading-edge nodes. TSMC has only used it on N7+, the N5 family, and the short-lived N3(B). They have switched back to a 1:1 ratio for N3E. Intel has only used it on the 10 nm/Intel 7 family, with Intel 4, 3 and 18A all using a 1:1 ratio. Samsung is the only one still using a 3:2 ratio at the leading edge, using it in the SF4 and SF3 families. It remains to be seen if SMIC will remain at a 3:2 ratio or move to a 1:1 ratio with its future nodes. The industry is still actively exploring these local-routing ratios. At VLSI 2026, imec will be presenting work on even higher ratios, including a 2:1 scheme that can reduce area by up to 14%. We will be covering the conference in a future newsletter article. Subscribe We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Interested in joining us on this ride and think you can be a difference maker? Check out our Careers page. The final local interconnect layer for N+3 is M3, with a pitch of 44 nm. The M3 pitch is the same as on N+2 and 10% larger than on N6. The semi-global layers carry the majority of block-level signal routing. They have a coarser pitch than the lower local layers. On leading-edge nodes, they are designed to sit at the limit of DUV single patterning. M4 through M11 pitches were found divided between 80–82 nm (M4–M6), 128 nm (M7–M10), and 148 nm (M11). Given limited sampling, it is possible these are divided further in dense routing areas. At the top are two giant metal layers, M12 and M13. These have kept the same pitches as N+2 at 1920 nm and 4600 nm respectively. While the lower layers’ pitches are generally fixed by the process and library, the upper layers vary much more in pitch and count, depending on the design. Even two smartphone SoCs on the same process can have wildly different metal stacks. The Helio G99 carries fewer routing layers, reaching coarse metal pitches of 850 nm by M9, while the larger and higher-performance Kirin 9030 keeps fine pitches until M11. SRAM At the leading edge, SRAM is much more difficult to scale than logic. TSMC’s latest nodes have seen little to no bitcell scaling, while logic still has more DTCO levers to pull. While looking for other logic libraries in the GPU compute units, we stumbled upon the SRAM. The most common type of SRAM has 6 transistors (6T), but this cell had 8 transistors (8T) instead. 8T SRAM adds two transistors to form a dedicated read port. Unlike a 6T cell, where reading disturbs the storage, the decoupled read port removes read-disturb, improving read stability and letting the cell be pushed harder for performance. At first glance, the cut looked like an unusual logic library, with each cell row having 3 fins of one polarity and 5 fins of another. The rows also alternated in orientation. Energy-dispersive X-ray spectroscopy (EDS) resolved our confusion. The cut had not landed on the GPU logic, but on the SRAM macro beside it. The unusual fin pattern was due to the SRAM library. We return to EDS in the process flow analysis behind the paywall. SRAM libraries are not like traditional logic libraries. Due to the unequal number of PMOS and NMOS transistors, they require specialized rules and layout libraries. They do not need the flexibility of logic libraries, so they are hyper-optimized for one purpose: dense, reliable memory. The SRAM cell we found is a 1:2:2-2:2 cell. This means there is 1 fin per pull-up (PU) PMOS transistor, and 2 fins per pull-down (PD) and pass-gate (PG) NMOS transistor. These 2 PU, 2 PD and 2 PG transistors would usually form a single 6T high-current cell (HCC). An 8T HCC adds a read-pull-down (RPD) and a read-pass-gate (RPG) NMOS transistor, each with two fins. We measured a cell height of 406 nm, which brings the bitcell size to 0.0463 µm². That is a theoretical peak density of 21.6 Mib/mm². We estimate that a 6T HCC would have a cell height of 292 nm and a size of 0.0337 µm². This is ~12% larger than a 6T HCC on Intel 3 and 4. We also estimate the 6T high-density cell (HDC) to have a cell height of 228 nm and a size of 0.0260 µm². This is coincidentally the same as the logic standard-cell height measured earlier. The estimate puts the cell near Samsung 7LPP/5LPP and slightly below TSMC N7/N6. That is a theoretical peak density of 38.5 Mib/mm². 6T HDC is arguably the most important cell as it is used for the largest caches in a chip, the L3 caches and system-level cache (SLC). Both the Kirin 9020 and 9030 have split the SLC into 4 banks to raise total SLC bandwidth. In the Kirin 9030, the SLC increased from 2 MiB to 3 MiB per bank. Correspondingly, the number of arrays within the bank also increased by 50%, from 16 to 24. Each array can store 128 KiB and forms an orderly pattern on the die shot. From the Kirin 9020 to the Kirin 9030, the area of a 128 KiB SLC array decreased from 0.0477 mm² to 0.0392 mm², an 18% shrink. The achieved density is 25.5 Mib/mm², 66% of the theoretical maximum. While the SLC was quite similar across both chips, the L3 has seen some major changes, particularly in terms of its layout. The total capacity also went up from 10 MiB to 12 MiB. Much like the SLC, the L3 is also split into 4 banks. In the Kirin 9020, an L3 bank consisted of 16× 128 KiB arrays and 16× 32 KiB arrays. However, an L3 bank in the Kirin 9030 instead consists of 48× 64 KiB arrays. In the Kirin 9020 L3, a 128 KiB array was 0.0513 mm² and a 32 KiB array was 0.0154 mm². The size of the 128 KiB array is different on the L3 and SLC as the assist circuitry for the two arrays differs depending on their purpose. In the Kirin 9030 L3, a 64 KiB array is 0.0210 mm². Although not a like-for-like comparison, normalized for capacity, it is 18% smaller than the 9020’s 128 KiB L3 array and 31% smaller than its 32 KiB L3 array. The achieved density is slightly lower than the SLC, at 23.8 Mib/mm², 62% of the theoretical maximum. Unlike the L3 and SLC, the prime cores’ private L2 cache uses a 2-bank design. As the prime cores’ L2 is latency-critical, it likely uses 6T HCC instead of 6T HDC. The 9020 has 16 arrays in each bank while the 9030 has 32. Each array has a capacity of 32 KiB. A 32 KiB array in the L2 shrank from 0.0171 mm² to 0.0142 mm², ~17% smaller. The density is 17.6 Mib/mm², ~59% of the theoretical maximum for 6T HCC. SRAM scaled well from N+2 to N+3, shrinking by ~19%, close to the theoretical logic shrink. The caveat is that N+2’s bitcells were unusually large, bigger than comparable 7 nm-class nodes, so part of the gain is catch-up rather than true scaling. With the insights from STEEL’s teardowns, we will be doing a deep dive into SRAM in a future newsletter article. Subscribe Everything above came out of a single STEEL teardown: die annotation, block-level area analysis and TEM cross-sections through logic and SRAM. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Future Roadmap The same cross-sections that pin down N+3 also show where SMIC can go next. Although N+3 is already close to the practical limits of DUV multi-patterning in several layers, SMIC still has a few scaling levers left. A theoretical N+4 would likely start with cell height. N+3 uses 5 M0 tracks between its power rails. Moving to 4 M0 tracks, as on SMIC N+2 and TSMC N6, could reduce cell height by roughly 15%. The routing grid is only one side of the shrink; the front end also must fit into the smaller cell. One possible FEOL lever is reducing the p-to-n isolation spacing from two diffusion grid units to one. Intel used this scaling booster on Intel 4, and TSMC did so on its N3 family. This path trades layout flexibility for density. Fewer M0 tracks reduce local routing resources, while tighter p-to-n spacing raises integration and design-rule difficulty. M2 is also constrained by the cell height shrink. For SMIC to maintain a ~5.7-track cell, M2 would need to move toward ~35 nm. That would move another layer into SAQP territory. SMIC could also reduce the CGP from 57 nm to 54 nm. Intel reached a similar CGP on Intel 10 nm/Intel 7 without EUV. The local interconnect is also tougher. If SMIC keeps the 3:2 M1-to-gate ratio, M1 would need to shrink to 36 nm and would likely require SAQP as well. If SMIC moves to a 1:1 ratio, M1 could relax to 54 nm, but it would give up routing flexibility. Under this theoretical path, we estimate that SMIC N+4 could reach a cell height of 198 nm and a CGP of 54 nm, implying a Bohr density of 137.8 MTr/mm², on par with TSMC N5 or Samsung SF4. However, the difficulty is cumulative. Each step is individually plausible, but together they make N+4 harder than the transition from N+2 to N+3. It will likely take longer, cost more, and carry less process margin. A theoretical N+5 would require a larger integration shift. One possible path is backside contacts (BSCon), moving power routing and source/drain contacts to the backside, which would reduce front-side routing pressure and enable another reduction in cell height. The front-side metal pitches could relax to reduce the process complexity. M0 would likely relax slightly to ~34 nm, and M2 and M4 pitches could relax further. CGP is unlikely to shrink much further. Even with EUV, 48 nm has been the practical limit for yield and process control. This approach would allow N+5’s cell height to fall to 170 nm and its CGP to 53 nm. This implies a Bohr density of 163.6 MTr/mm², on par with Intel 18A’s HP library. However, this would not make N+5 cost-competitive with the leading edge. It would reach a similar density through a much more expensive route. The integration difficulty rises sharply, with new process flows for backside alignment, wafer thinning, contact reveal, and backside metallization. Past this point, standard density and interconnect scaling become increasingly unattractive. That is where Huawei’s roadmap stops looking like a normal foundry roadmap and starts looking like a packaging roadmap. At ISCAS 2026, Huawei unveiled its tau (τ) scaling law, reframing process scaling in the time domain. τ is the time cost of data movement and processing: switching delays in transistors, RC signal propagation delays in circuits, compute, memory, and networking latency. Outside Huawei’s terminology, this is called system-technology co-optimization. This is Huawei’s answer to its lack of EUV lithography. Without EUV, planar density cannot keep pace with TSMC, Intel, or Samsung. If transistor density cannot shrink further, Huawei’s alternative is to shorten wires, reduce buffering, and stack logic vertically. “LogicFolding”, Huawei’s implementation of this new scaling idea, is, in practice, an aggressive 3D stacking approach. AMD V-Cache places SRAM above or below a CPU die. AMD’s MI350X places active interposer dies (AIDs) underneath accelerator and compute dies (XCDs), with the AIDs handling cache, IO interfaces, the network-on-chip (NoC) and embedded metal-insulator-metal (MIM) capacitors. With LogicFolding, parts of the same logic block are split across multiple active dies bonded face-to-face at ultra-fine pitch. This allows Huawei to shorten some critical paths and reduce buffer overhead, not merely add cache capacity or offload the IO and interconnect. Shortening wires is where the higher clocks come from. A large share of a modern core’s delay and energy budget goes into driving long interconnects and the repeater buffers along them. LogicFolding distributes a block’s critical-path gates across multiple stacked tiers bonded at a very fine pitch, so the bond interface behaves like an additional metal layer and the longest paths get shorter. That is how Huawei expects to recover frequency and efficiency it cannot get from the process alone. Huawei’s roadmap shows its intent. Prime core frequency is targeted to rise from 2.75 GHz in the Kirin 9030 to roughly 5 GHz by 2031, far beyond what planar scaling alone could deliver. Prime cores with 3.1 and 3.39 GHz clocks are being tested in its labs, although their power consumption is unknown. Beyond that, chips are in the design, simulation or pathfinding phase, meaning the frequencies are targets. However, the direction matters more: LogicFolding also helps with performance, not just density. The catch is that Huawei’s density claim is not directly comparable to foundry densities. A stacked design can report more transistors per package footprint by adding active layers, even if each patterned die remains well behind TSMC or Intel in front-end density. This is how Huawei can claim to reach foundry 14A-equivalent density by 2031. This is not a like-for-like foundry comparison, with Huawei using stacked logic and measuring density per package footprint. On a normalized Bohr-density basis, SMIC N+3 is ~114 MTr/mm², 38% less than Intel 18A’s HD library. Huawei’s 3D roadmap closes the gap by stacking active logic, reaching 215 MTr/mm² by 2030. In 2031, the roadmap density jumps to 295 MTr/mm², implying either a third active layer, partial EUV insertion or aggressive planar DUV scaling. Huawei’s methodology makes other foundries look much denser as well. Applying it to AMD’s MI450X with an N2 top die on an N3P base die yields a theoretical density of 460.2 MTr/mm² in 2026, compared with Huawei’s 295 MTr/mm² in 2031. This Kirin 9030 does not use LogicFolding, remaining in a conventional mobile SoC package. Instead, it forms the baseline for how far Huawei and SMIC can push planar scaling. Future teardowns of Kirin and Ascend chips will show both planar logic density and Huawei’s hybrid bonding solutions. Export controls changed China’s optimization problem rather than ending it. EUV restrictions raised the cost and complexity of leading-edge manufacturing without freezing it. SMIC reaches N6-class logic density through DUV immersion, SAQP and DTCO, while Huawei shifts more of the burden onto architecture, packaging and system-level integration. Future nodes will be tougher. N+3 still had room to tighten local metals and reduce cell height and CGP. Further scaling without EUV leaves fewer levers. More aggressive multi-patterning adds masks and overlay error. SMIC can keep pushing DUV, but each step will get more expensive and less forgiving. The design side is just as critical. Huawei had domestic EDA tools and flows before the Kirin 9030, with the Kirin 9000s, 9010 and 9020 making that clear. Huawei was able to ship multiple consumer SoCs on SMIC N+2 and N+3 while cut off from the Western EDA stack. US export controls restricted EDA tools for advanced chips in 2022 but did not target tools for more mature chips. In 2025, the US government briefly placed much broader restrictions on EDA software from Synopsys, Cadence, and others, before lifting them less than two months later as part of a trade deal tied to rare earths. Huawei has been unable to access those tools because it remains on a US trade blacklist. That forced Huawei, SMIC and Chinese academic institutions to build their own tools and flows. Researchers at Peking University recently announced a prototype EDA tool for Huawei’s LogicFolding architecture, which requires a new flow to handle the multilayer layout and floorplan. This is not the same as replacing the full Synopsys or Cadence stack, but it shows where domestic EDA is headed: toward tighter co-optimization between architecture, process and packaging. These advances are also diffusing into the Chinese ecosystem. SMIC is licensing its N+2 and N+3 processes to HLMC/Hua Hong at the government’s direction rather than by choice. If the same process learning feeds into Ascend accelerators for AI training and inference, the choke point shifts from one named fab to an ecosystem. Alibaba’s T-Head silicon arm and Cambricon, a Chinese AI chip designer that is expected to supply ByteDance, could also be major beneficiaries. Sanctions aimed at SMIC alone become less effective once the manufacturing knowledge has spread to other fabs and design houses. China is not closing the gap with Intel, Samsung and TSMC. The teardown shows the opposite in several places: no EUV, no backside power, higher process complexity, and visible trade-offs. But China is still advancing. If domestic chips become good enough for phones, inference, networking and security-sensitive workloads, they can matter strategically without matching TSMC at the leading edge. Behind the paywall, we show what else STEEL can do, with material and process flow analysis of SMIC N+3, and analysis of the Kirin 9030 package. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline, access the full Kirin 9030 and SMIC N+3 analysis or to commission a custom teardown, contact sales@semianalysis.com.
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The work you can't always see: Beer is political, part 2
Recently I published a piece about beer, politics, and the question of who speaks up and who doesn’t. I meant every word of it. I still do. And then my inbox opened up. Cleveland Prost is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe I’ve been writing about beer since 2014. For most of that time, I kept things deliberately light — taproom profiles, new releases, the people behind the pints. Gradually, over years of building this thing, you gave me something I didn’t expect: permission. Permission to go deeper. To say what I actually saw in this industry and what I actually believed about it. That trust isn’t something I take lightly. It’s why that piece existed at all, and it’s why this one does too. I’m not walking anything back. But I want to go further. In that piece, I wrote that beer has never existed outside the system. That immigration policy affects who staffs breweries and harvests ingredients. That labor policy affects taproom workers. That civil rights policy affects who feels safe walking into a taproom. That “beer does not exist in a vacuum. The idea that it does is comforting. It is also false.” I believe that as much now as I did when I wrote it. But one idea came back at me, in different forms, over and over (from reader emails, comments, and conversations): that beer itself isn’t political — that it only becomes political when someone decides to make it that way. That what we’re really seeing is a choice by individuals to inject division into something that doesn’t inherently require it. It’s a comforting idea. It’s also wrong — and I think it’s worth being precise about why. That framing assumes that breweries operate outside the conditions shaping everything else. That politics is something you choose to bring into a room that was, until then, clean and neutral. That if you stay quiet, you stay clear of it. But the room was never neutral. It was never clean. Politics is already in the room. It’s in who walks through the door comfortably and who hesitates. It’s in whether a space can be used for organizing without fear. It’s in whether helping someone quietly might carry consequences you have to think carefully about in advance. It’s in who staffed the brewery, who harvested the grain, who can afford to be a regular. The idea that you opt out of all that by staying quiet is an illusion. You only change how visible your response to it is. This is, I realize, a hard thing to hear if you came to a beer newsletter for something lighter. I wrote recently that “beer, for me, has always felt like a refuge — a third place in an increasingly fractured world.” I meant that. I still do. But a refuge is not an escape from reality. It’s a place to gather strength to face it. Here’s what I actually missed — and what I want to correct. Multiple people in the industry reached out to me. I’m not naming them and I’m not identifying their businesses, because that’s not my call. If and when they want to be loud about what they’re doing, that agency belongs to them. What I can share is the substance of what they said, because it complicated something I presented too cleanly. The overall message: *You don’t know what we all are doing.* And they’re right. I don’t. One example involved a collaboration brewed quietly to support another business facing serious challenges in a whole different region, with proceeds directed toward solidarity, community, and keeping operations afloat. No announcement. It could have been broadcast widely. The point was never publicity. Another example involved logistical support for community efforts: organizing safe transportation, providing space for meetings on otherwise closed days, facilitating gatherings under difficult conditions. All of it happening while balancing real financial pressure and genuine concern for personal safety. None of what they described is a brewer “deciding to make beer political.” It’s people responding to the conditions around them — conditions that are already shaping who feels safe, who has access, who can gather, who needs help, and who has the capacity to offer it. Politics, again, already in the room. Already shaping choices. Whether anyone announced it or not. I’ve spent decades in taprooms, at barrel releases, at festivals, in back offices and brewing floors, talking to the people who built this industry from nothing. I know how much happens that never makes it onto social media. I know the owner who quietly comp’d a tab for someone having a crisis. The brewer who drove an hour to pick up a stranger who needed a safe ride. The taproom that stayed dark on a Tuesday so a community group could use the space without it becoming A Whole Thing. None of that gets a post. Most of it never will. So when I wrote recently about silence — when I said that “silence right now doesn’t feel neutral, it feels like complicity” — I was writing about what I could see. And I was right about what I saw. The public silence of breweries that have the platform, the stability, and frankly the safety to say something and choose not to? That still troubles me. I’m not softening that. But some of what I read as silence is actually something else entirely. It’s people doing the work with their hands instead of their phones. It’s people who are genuinely afraid — not of being canceled, but of real consequences for their families, their employees, their ability to keep the doors open at all. That deserves more than a footnote. It deserves to be named clearly. Here’s the tension I want to sit with honestly: public statements matter. They matter because people can’t rally around something they can’t see. Visibility creates awareness and solidarity. It helps people find each other. It tells someone standing outside your taproom door, uncertain whether they’ll be welcomed inside, something they need to know — or whether it’s even safe for them to be in public at all. That’s not performative. I wrote recently that the craft beer movement “was built on collective defiance. It was built on rejecting consolidation. On pushing back against homogeneity.” I believe that too. And I’ll extend it: breweries should be at least as loud about their values as they are when they drop a new seasonal. Your hazy IPA gets a full rollout — the label art, the tap handle photo, the countdown post. Human dignity deserves the same energy. Be as loud about human rights as you are about your beer. There is no reason those two things should require different levels of courage from you. But visibility isn’t the only form of courage. And not everyone can be visible right now without real consequences — financial, personal, sometimes physical. There are people in this industry doing hard, unglamorous, sometimes risky work in the background, and announcing it would compromise it or paint a target on someone who’s already stretched thin. That’s not silence as complicity. That’s operational discipline under pressure. What I want to push back on — clearly, not gently — is the idea that behind-the-scenes action and public visibility are in competition with each other. The person organizing quietly in the back room and the person posting a statement of solidarity on a Tuesday morning are both doing something real. We need both. We need the quiet infrastructure and we need the visible signal. We need people to know that this industry — at its best, at its most independent, and human — gives a fuck. I closed that piece with a question: “Reactive and fearful? Or clear and values-driven?” That question still stands. But having heard from you, I’d add a corollary: the values-driven path isn’t always the loudest one. Sometimes it’s a phone call and a recipe. Sometimes it’s a room made available on a closed Tuesday. Sometimes it’s a drive across town for someone who needed a safe ride home. All of it is political. All of it was always political. You don’t get to opt out of that — you only get to decide what you do with it. I’ve spent more than a decade writing about this industry because I believe it can be exactly that. I’ve been lucky enough to build an audience that lets me say so plainly. That’s a privilege I intend to use. The work is happening. Some of it you’ll see. Some of it you won’t. Support it either way. Cleveland Prost is a reader-supported publication covering beer and brewing across New York state. To receive new posts and support this work, consider becoming a free or paid subscriber. Cleveland Prost is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
Ministry of Public Health, WHO Thailand and the Embassy of the People’s Republic of China in the Kingdom of Thailand launch initiative to strengthen Thailand’s public health workforce
28 May 2026 | Embassy of the People’s Republic of China in ThailandA skilled and coordinated public health workforce is essential for protecting population health and responding to public health emergencies. Strengthening these capacities was the focus of a meeting held on 28 May 2026 at the Embassy of the People’s Republic of China in Thailand.Dr Ailan Li, WHO Representative to Thailand, together with Dr Watcharanan Tinnaitorn, Deputy Director of the Division of Public Health Emergency Management, Ministry of Public Health, and officials from WHO and the Ministry of Public Health, met with Counselor Zhang Xiaoxiao from the Economic & Commercial Counsellor's Office, Embassy of the People’s Republic of China in the Kingdom of Thailand to mark the launch of collaboration under the WHO Roadmap to strengthen the public health workforce.The initiative supports Thailand in strengthening its public health workforce across both health and non-health sectors. Public health emergencies require coordinated action across a wide range of professions and institutions, including health workers, border control officers, water safety specialists, communication professionals and local government authorities. Through the project, partners will work together to assess workforce capacities, strengthen competencies and promote coordination across sectors to support preparedness and response efforts.The discussion highlighted opportunities to enhance cross-country collaboration through knowledge exchange, communication activities and engagement at key project milestones, supporting workforce development and emergency preparedness efforts.Beyond its immediate objectives, the initiative also reflects Thailand’s contributions to public health at regional and global levels. The exchange highlighted the importance of sharing experiences, lessons learned and good practices through international cooperation to strengthen public health capacity and preparedness.WHO expressed appreciation to the Embassy of the People’s Republic of China in Thailand for supporting the project and recognizing the importance of investing in public health workforce development, preparedness and health security through partnership and multilateral cooperation. WHO also commended Thailand’s continued leadership and commitment to strengthening public health systems and emergency preparedness, including through cross-sector collaboration and workforce development.WHO remains committed to supporting Thailand and partners in advancing resilient and people-centred public health systems and strengthening preparedness for future health challengesAbout the EPHF Roadmap ProjectThailand is one of four countries selected in 2026 to initiate implementation of the Essential Public Health Functions (EPHF) Roadmap, alongside Maldives, Papua New Guinea and Timor-Leste. The initiative is funded by the China International Development Cooperation Agency (CIDCA). The project is led by Thailand’s Ministry of Public Health, with WHO Thailand serving as a co-implementing partner. Other partners include the Chinese Center for Disease Control and Prevention (China CDC), the International Association of National Public Health Institutes (IANPHI), the Global Network for Academic Public Health/Public Health Interprofessional Leadership Alliance (GNAPH/PHILA) and the World Federation of Public Health Associations (WFPHA).
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New MatterChat Model Helps AI to ‘See’ the Language of Science
From writing emails to generating computer code, much of the artificial intelligence prevalent in our daily lives has succeeded by mastering one domain: text. However, this leaves a major blind spot in the physical sciences, where models depend on the high-resolution, three-dimensional data of the physical world, like the intricate lattice of atoms in a crystal. Delivering on the promise of using AI for science requires teaching these data-driven text models to seamlessly “talk to” physics-based models. Now, a new AI framework from Lawrence Berkeley National Laboratory (Berkeley Lab), called MatterChat, solves this problem by creating a specialized “bridge.” It connects the conversational power of a Large Language Model (LLM) with a physics-based AI that models “interatomic potentials”: the complex physical forces between atoms. The resulting system already significantly outperforms general-purpose AI tools like GPT-4 at predicting material properties, and the team hopes it can accelerate scientific discovery by serving as a robust research partner that provides grounded insights and generates step-by-step instructions for synthesizing novel materials. A paper describing this work was recently published in Nature Machine Intelligence. “Traditional simulations can provide the physical rigor required for materials science, yet their computational cost remains prohibitive for high-throughput screening. Conversely, while LLMs excel at rapid knowledge synthesis, they inherently lack the ‘structural vision’ to interpret materials directly from their underlying atomic coordinates,” said Yingheng Tang, a postdoctoral researcher in Berkeley Lab’s Applied Math and Computational Research Division (AMCR) and lead author on the paper. “MatterChat was built to solve this dilemma, empowering LLMs with a structural ‘vision’ that allows researchers to leverage their full potential for solving complex, real-world materials challenges.” Empowering language models to solve complex challenges in materials science To build MatterChat, the Berkeley Lab team drew inspiration from technologies like Vision Question Answering (VQA) and Text-to-Image (T2I) generation. In these tasks, AI must translate high-level text concepts into visual images, or vice versa. Doing so requires developers to build tools that “bridge” two fundamentally different forms of data. The researchers adapted this concept to the physical sciences. With MatterChat, they created a “bridge model” that successfully connects an LLM’s general knowledge with the deep understanding of the atomic-scale world encoded in scientific interatomic potentials. Until now, researchers using LLMs to solve materials problems usually had to feed them raw data files as if they were just strings of text. It’s like asking an AI to understand a complex 3D engine based only on a parts list: the LLM can read the names, but it can’t “see” how the atoms fit together in space. MatterChat solves this by training a specialized AI bridge model, pre-trained on millions of crystal structures and an LLM, to align the LLM’s representation of the world with the interatomic potential’s representation of the world. The bridge model can translate physical insights into a format the LLM can actually understand. By giving the LLM these “scientific eyes”— a scientific “inductive bias” in the terminology of AI — the Berkeley Lab team has transformed it into a robust research tool capable of providing grounded scientific insights into complex materials challenges, such as predicting thermal stability or analyzing electronic band gaps. “We think of atoms as living in a physical space, but from a machine learning perspective, they are just vectors living in some very non-trivially structured manifold in a high-dimensional Euclidean space; and, of course, the same is true for the sentences and paragraphs that we use to express our ideas about those atoms,” said co-author Michael Mahoney, Berkeley Lab’s Scientific Data Division (SDD) AI Initiative Research Lead. “The bridge model basically gets those two structures to ‘talk with’ each other.” As a proof-of-concept of this general approach, the team trained their bridge model on a dataset curated by pairing nearly 143,000 stable atomic structures from the Materials Project with their corresponding physical properties. This training data was automatically assembled using the Materials Project’s API and deliberately enriched with properties fundamental to microelectronics design — like formation energy and bandgap — allowing MatterChat to learn the complex patterns connecting a material’s atomic blueprint to its functional performance. To validate their model, the researchers benchmarked MatterChat against a suite of other AI systems, from general-purpose LLMs to other specialized scientific AI methods. The results show that MatterChat consistently outperformed its competitors across a range of tasks. The model was more accurate in classifying material types and demonstrated superior precision in predicting numerical properties. For example, it excelled at predicting a material’s bandgap, a property critical for designing new electronics from high-capacity energy storage to next-generation computer chips. “Our design is significantly more efficient because we don’t have to build a massive AI model from the ground up,” said co-author Zhi (Jackie) Yao, a research scientist in Berkeley Lab’s AMCR. “Instead, we take two powerful, pre-trained models — a structural encoder for materials physics and an open-source LLM — and use them off-the-shelf. The only component we actually train is the lightweight ‘bridge model’ that translates between them. It’s the difference between building an entire car factory and simply designing a smart adapter that connects a world-class engine to a world-class navigation system. This approach is not only computationally efficient, but also makes the system modular, so we can easily upgrade components or adapt the bridge for other scientific domains in the future.” Crucially, this modular design highlights exactly how institutions like Berkeley Lab and the Department of Energy are carving out a highly valuable niche in the booming AI landscape. Rather than competing with Silicon Valley tech giants to build ever-larger language models from scratch, the lab is focusing on the specialized connective tissue that makes commercial AI useful for hardcore science. Because the bridge model approach underlying MatterChat is forward-compatible, it is perfectly positioned to leverage these parallel tracks of innovation. As Mahoney pointed out, “We expect that industry will continue to develop improved LLMs, and we expect domain scientists and facilities will continue to generate new data. An important part of scientific machine learning is not simply to solve problems on today’s data, but instead to develop general methods that will be forward-compatible with orders of magnitude more data, whether from scientific domains or from LLMs.” According to Yao, the MatterChat project, which was initially developed and enhanced with funding from a Berkeley Lab Laboratory Directed Research & Development (LDRD) Program, will now expand its capabilities. In a collaboration with Fermilab, MatterChat is already contributing to a U.S. Department of Energy Genesis Mission project — called Accelerating eXtreme Environment Specs-to-Silicon (AXESS) — that aims to speed up the development of next-generation, high-speed, radiation-hardened detectors for challenging particle physics experiments by using advanced 3D integrated circuits (chiplets) and AI-driven data analysis. In addition to the LDRD support, the team also credits supercomputing resources at the National Energy Research Scientific Computing Center (NERSC), located at Berkeley Lab, with MatterChat’s success. “We are incredibly grateful to NERSC; this research simply would not have happened without access to the Perlmutter supercomputer through their AI for Science program,” said Tang. Wenbin Xu, a NERSC postdoctoral fellow at the time, was also a major co-author of the work, as was Benjamin Erichson, a research scientist in Berkeley Lab’s SDD, highlighting the benefits of AMCR-SDD collaboration on AI for science. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.
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The Rockdale County Sheriff’s Office said a woman was shot while deputies responded to a mental health disturbance on Saturday.
Indigenous Leadership for Health: Virtual Preparatory Webinar to UNPFII 2026
English - French - Portuguese - Spanish - Russian Indigenous Peoples have the right to the highest attainable standard of physical and mental health. WHO invites you to join Indigenous Leadership for Health, a virtual preparatory webinar to the 25th Session of the UN Permanent Forum on Indigenous Issues (UNPFII 2026), to be held on Thursday, 16 April 2026, from 13:30 to 16:00 CEST, via Zoom. Interpretation will be available in English, French, Portuguese, Russian, and Spanish.This event brings together Indigenous leaders working on health to help shape the forthcoming WHO Global Plan of Action on the Health of Indigenous Peoples (GPoA). It is co-organized by WHO, the Government of Brazil, the Government of the Philippines, and the Johns Hopkins Center for Indigenous Health.The webinar will be divided into two parts, each with a corresponding objective:Part I – Contents of the draft Global Plan of Action. Part I's objective is to provide an update on the process for development of the Global Plan of Action on the Health of Indigenous Peoples, to share important lessons learnt from previous work and inputs received thus far, and to invite participants to send written inputs to the Plan. The linkages to the health topics to be discussed at the forthcoming UNPFII will also be highlighted.Part II – Panel on Indigenous Leadership for Health. Part II's objective is to highlight Indigenous leadership, knowledge systems, and community-driven approaches that contribute to improving the health and well-being of Indigenous Peoples, through the sharing of select country and regional examples.Registration is free and open to all. Register hereWe encourage all Indigenous organizations, communities, partners, and individuals to join us and contribute to this important global process.
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Responding to impeachment calls, Rick Scott likens Donald Trump to Abraham Lincoln, FDR, Harry Truman
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LMPD releases names of 2 officers who shot woman during mental health crisis call
Louisville Metro Police Department released the names of two officers who, while responding to a mental health crisis, fired shots, and a woman died.
LMPD officers fatally shoot woman experiencing 'mental health' crisis
Two LMPD officers shot a woman while responding to a call about someone experiencing a \
Olympians react to the IOC policy change to protect women's sports
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