Remi Dingreville

Nuclear energy depends on isotopes. From testing how reactor materials perform under extreme conditions to validating fuel performance and safety margins, isotopes make modern nuclear energy possible. They help researchers track corrosion, measure change, and understand how materials behave inside operating systems over time. At ORNL, isotope science supports every stage of nuclear energy development, from early research and modeling to demonstration and deployment. These capabilities reduce uncertainty, strengthen reliability, and help ensure technologies are ready to perform when it matters most. Learn how isotopes are advancing nuclear energy: https://bit.ly/4rXZYcp

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At Argonne, powerful X-ray beams are helping scientists expand our understanding of an array of quantum behaviors - https://bit.ly/3TQEsaq In a recent collaboration with SLAC National Accelerator Laboratory, researchers used the Advanced Photon Source to study strontium titanate. Once sold as a diamond substitute, it may now hold the key to understanding unusual quantum behaviors. By stretching ultra-thin layers of the material, the team discovered how to switch it into a special electric state—and watched its atoms shift in real time. This kind of insight could one day lead to smarter electronics and breakthroughs in energy technology.

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As part of the Mechanical Engineering Seminar Series, I am organizing a webinar in collaboration with COMSOL, Inc. for our students, researchers, and anyone interested in multiphysics simulation. The session will be delivered by Venkat Krisshna, Applications Engineer at COMSOL, who specializes in heat and mass transport modeling and multiphysics simulation. He has several years of experience applying Computational Fluid Dynamics (CFD), heat transfer, and numerical modeling tools to solve real engineering problems. During this hands-on web workshop, participants will be introduced to the COMSOL Multiphysics modeling workflow and will learn how to build a model from scratch. Attendees will be able to follow along on their own computers, ask questions during the session, and gain practical experience with the software. Participants who register and attend will also receive access to a free trial license after the webinar, so I strongly encourage students to take advantage of this opportunity. Event link and registration: https://lnkd.in/e5rDEmry This should be a useful session for anyone working in CFD, heat transfer, multiphysics simulation, or computational engineering. #COMSOL #CFD #FEA #multiphysics #engineeringsimulation #mechanicalengineering

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I am excited to see our recent article highlighted by Acta Materialia. “Accelerated multi-objective alloy discovery through efficient Bayesian methods: Application to the FCC high entropy alloy space” Using the BIRDSHOT framework applied to the Co-Cr-Fe-Ni-V-Al FCC high-entropy alloy system, we optimized three key material objectives (ultim​ate/yield strength ratio, hardness, and strain-rate sensitivity) and identified a three-objective Pareto front while exploring only ~0.15% of the feasible alloy composition space. Grateful to my co-authors and collaborators for their outstanding contributions, and to Acta Materialia for sharing our work with the broader materials community. #MaterialsScience #AlloyDesign #HighEntropyAlloys #BayesianOptimization #MachineLearning #AIForScience #DataDrivenDiscovery #AcceleratedDiscovery #MaterialsInnovation #FutureOfMaterials

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The "MOF zoo" is becoming nearly impossible to navigate. The recent Nobel Prize highlighted Metal-Organic Frameworks as a cornerstone of materials science. Now the challenge has shifted from creating these materials to finding the right one among millions of possibilities. The bottleneck is that traditional macroscopic descriptors, like pore size, often miss the subtle atomic-level physics that actually drive their complex chemical properties. In our latest work in Journal of Materials Chemistry A, we move beyond simple (human-identified) geometric descriptors. We developed an optimization workflow that couples Graph Neural Networks (GNNs) with Multi-Objective Bayesian Optimization (BO). By representing MOFs as graphs, the GNN "sees" the local chemical environments—the specific node-linker geometries etc—that determine performance. When paired with BO, we can navigate the trade-offs of competing performance goals (like selectivity vs. capacity) far more efficiently than brute-force screening. Instead of just searching the zoo, we are using those deep topological descriptors to map it. Great work with Lane Schultz, Nickolas Gantzler, @Scott Bobbitt, and Dorina Sava Gallis. Read the details here: https://lnkd.in/gRTXKsYu

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Nuclear Science User Facilities (NSUF) is proud to partner with Argonne National Laboratory on the Activated Material Laboratory at the Advanced Photon Source.

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Physics graduate Amaya Caudel has been selected for a prestigious summer internship at Los Alamos National Laboratory in New Mexico, marking another milestone in her impressive research career. Caudel, who completed three Research Experiences for Undergraduates (REU) programs during her time as an undergraduate, will be working on computational materials research focusing on titanium aluminum. Her project will leverage the speed of machine learning algorithms by training them off of highly accurate Density Functional Theory (DFT) outputs. 📰 👉 https://bit.ly/3SBADFw Austin Peay State University | #CoSTEM | #GovsLead

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ORNL researchers are advancing the future of data storage 💿 By better understanding how electric polarization behaves at extremely small scales, the team is opening pathways for faster, more reliable memory technologies for everyday electronics and next-generation computing systems. 🔗 Read more: https://bit.ly/4r2dEmn #MaterialsScience #Microelectronics #Innovation

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I’ll be honest, I’m an old-school shop floor guy who’s spent a career beating manufacturing processes into submission with a wrench and a little stubbornness. So when I came back to EWI and heard Alex Kitt talking about “data science” and “machine learning,” I rolled my eyes so hard I almost sprained something. Then I saw it in action. Over numerous projects, Alex and his team have used AI and machine learning to combine real-world test data with analytical data sets, rapidly zeroing in on robust welding parameters for some very complex metallurgical systems. The speed and accuracy are game-changing. Consider me a convert. The next step? Data and lots of it. At EWI, we’ve adopted a new mantra: data should be like breathing. For any program we are researching, if we can capture it (current, voltage, spatial location, etc.), we do, even if we don’t have an immediate use for it. Because building rich, high-quality datasets now means faster, smarter manufacturing solutions in the future. I'm not smart enough to explain all the gory details, but reach out to Alex or attend his presentation at FABTECH!

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ECE professor Ali Akoglu and professor Krishna Muralidharan, principal investigator for AZSCI, director of the Center for Semiconductor Manufacturing (CSM) and professor of materials science and engineering, are part of the team awarded $250K in the inaugural Office of Research and Partnerships’ Big Idea Challenge to develop orbital data centers, bringing sustainable, high-performance computing to space. This interdisciplinary effort spans optics, satellites, semiconductor manufacturing and policy. The team will first create a digital twin of an orbital data center to model thermal control, cyber resilience and communications before moving toward prototypes. The project also leverages CSM to integrate advanced chip technologies for space-based systems. Assistant professors Narayanan Rengaswamy (ECE) and Xiaodong Yan (MSE and ECE) are also collaborating with Dr. Akoglu on developing heterogeneous architectures for this initiative. Learn more: https://bit.ly/4p8s7f6 #SpaceTech #UArizonaECE #BigIdeaChallenge #Semiconductors #Innovation

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We’re thrilled to share that HF Controls has gifted $450,000 to UTA to support research and student success in the Computer Science and Engineering Department. The gift funds Dr. Yonghe Liu’s work using artificial intelligence to improve the safety and efficiency of nuclear power plant control systems. It also expands the HF Controls Student Success Center, “The Bughouse,” supporting tutoring, mentoring, and student community building. Read more about this exciting partnership here: https://shorturl.at/qgP0j #UTA #CSEUTA #AI #NuclearInnovation #StudentSuccess #MaverickPride

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🔬How do you study thousands of neurons at once? You build better tools. ECE Prof. Spencer Smith's SLAB Lab designed a scan angle multiplier that achieves the laser scanning trifecta: high speed, high resolution, and a larger area.🧠⚡️ "…we want to see hundreds of neurons, thousands of neurons, with the ultimate goal of being able to look at how individual neurons work together across the entire brain." – Postdoc Che-Hang Yu This paper was published last week in Optica, and spin-out company Pacific Optica is now bringing this tech to labs worldwide.🌎 📜https://lnkd.in/gcM8tSAX UCSB College of Engineering, UC Santa Barbara, Che-Hang Yu

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Misalignment of CNC machine tool axes leads to dimensional inaccuracies, extended downtime, and costly, labor-intensive correction efforts. Energy Science at ORNL researchers have developed a solution with a new technology that uses advanced computational modeling to guide machine alignment in a more predictable and efficient manner. #manufacturing

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Andrew Chuang of Argonne National Laboratory's Advanced Photon Source will discuss using diffraction-based methods for tracking phase evolution, lattice strain, texture, and microstructural change in metal additive manufacturing. go.osu.edu/we7895

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Argonne National Laboratory’s upgraded Advanced Photon Source (APS) is now being seamlessly integrated with top-tier supercomputers like Polaris, Frontier, and Perlmutter. This enables groundbreaking real-time analysis of X-ray data—boosting research speed and precision across countless disciplines. One of the key technologies supporting this effort is Globus, which brings secure, reliable, and automated data workflows to the heart of scientific exploration. It’s the backbone for moving massive amounts of data, connecting experimental facilities with computational power and researchers worldwide. This combination means researchers can: ✅ Capture fast-evolving phenomena and adjust experiments in real time. ✅ Harness data-intensive workflows to accelerate breakthrough discoveries. ✅ Operate across a unified, secure infrastructure for effortless collaboration. ➡️ Read the article and see how Globus is propelling the next era of research: https://lnkd.in/gwdfsV4B #Globus #AdvancedPhotonSource #Supercomputing #ScientificDiscovery

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