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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quantum simulations of nuclear resonances with variational methods

Background: The many-body nature of nuclear physics problems poses significant computational challenges. These challenges become even more pronounced when studying the resonance states of nuclear systems, which are governed by the non-Hermitian Hamiltonian. Quantum computing, particularly for quantum many-body systems, offers a promising alternative, especially within the constraints of current noisy intermediate-scale quantum (NISQ) devices. Purpose: This work aims to simulate nuclear resonances using quantum algorithms by developing a variational framework compatible with non-Hermitian Hamiltonians and implementing it fully on a quantum simulator. Methods: We employ the complex scaling technique to extract resonance positions classically and adapt it for quantum simulations using a two-step algorithm. First, we transform the non-Hermitian Hamiltonian into a Hermitian form by using the energy variance as a cost function within a variational framework. Second, we perform 𝜃-trajectory calculations to determine optimal resonance positions in the complex energy plane. To address resource constraints on NISQ devices, we utilize Gray code (GC) encoding to reduce qubit requirements. Results: We first validate our approach using a schematic potential model that mimics a nuclear potential, successfully reproducing known resonance energies with high fidelity. We then extend the method to a more realistic 𝛼−𝛼 nuclear potential and compute the 𝐷- and 𝐺-wave resonance energies with a basis size of 𝑁=16, using only four qubits. The quantum simulation results closely match the classical values, demonstrating the feasibility of our approach. Conclusions: This study demonstrates, for the first time, that the complete 𝜃-trajectory method can be implemented on a quantum computer without relying on any classical input beyond the Hamiltonian. The results establish a scalable and efficient quantum framework for simulating resonance phenomena in nuclear systems. This work represents a significant step toward quantum simulations of open quantum systems and lays the foundation for future investigations into resonance structures in nuclear, atomic, and molecular physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Systematic Benchmarking of Climate Models: Methodologies, Applications, and New Directions

As climate models become increasingly complex, there is a growing need to comprehensively and systematically assess model performance with respect to observations. Given the increasing number and diversity of climate model simulations in use, the community has moved beyond simple model intercomparison and toward developing methods capable of benchmarking a large number of simulations against a suite of climate metrics. Here, we present a detailed review of evaluation and benchmarking methods and approaches developed in the last decade, focusing primarily on scientific implications for Coupled Model Intercomparison Project (CMIP) simulations and CMIP6 results that contributed to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Based on this review, we explain the resulting contemporary philosophy of model benchmarking, and provide clear distinctions and definitions of the terms model verification, process validation, evaluation, and benchmarking. While significant progress has been made in model development based on systematic evaluation and benchmarking efforts, some climate system biases still remain. The development of open‐source community software packages has played a fundamental role in identifying areas of significant model improvement and bias reduction. We review the key features of several software packages that have been commonly used over the past decade to evaluate and benchmark global and regional climate models. Additionally, we discuss best practices for the selection of evaluation and benchmarking metrics and for interpreting the obtained results, the importance of selecting suitable sources of reference data and accurate uncertainty quantification.

Environmental sciences↗
DOE OSTI2025

Cavity electrodynamics of van der Waals heterostructures

Van der Waals heterostructures host many-body quantum phenomena that are tunable in situ using electrostatic gates. Their constituent two-dimensional materials and gates can naturally form plasmonic self-cavities, confining light in standing waves of current density due to finite-size effects. The plasmonic resonances of typical graphite gates fall in the gigahertz to terahertz range, corresponding to the same microelectronvolt to millielectronvolt energy scale as the phenomena in van der Waals heterostructures that they electrically control. This raises the possibility that the built-in cavity modes of graphite gates are relevant for shaping the low-energy physics of these heterostructures. However, probing these cavity-coupled electrodynamics is challenging as devices are notably smaller than the diffraction limit at the relevant wavelengths. Here we report on the intrinsic cavity conductivity of gate-tunable graphene heterostructures. As the carrier density is tuned, we observe coupling and spectral weight transfer between graphene and graphite plasmonic cavity modes in the ultrastrong coupling regime. We present an analytical model to describe the results and provide general principles for cavity design. Our findings show that intrinsic cavity effects are important for understanding the low-energy electrodynamics of van der Waals heterostructures and open a pathway for useful functionality through cavity control.

Electronic properties and materials↗
DOE OSTI2025

Colloidal quantum dots for optoelectronics

Colloidal quantum dots (QDs) are semiconductor nanocrystals that have unique size-tunable optoelectronic properties and are suitable for wet processing. QD research aims to answer fundamental questions about the chemical and physical properties of nanoscale materials and use these tools for technological applications ranging from bio-imaging to quantum optics. At the core of this field is a set of synthetic, processing and analytical methods designed to produce QDs in uniform ensembles that meet the highest performance standards. Here, this Primer reviews QD fabrication methods with a focus on the applications of QDs in printed optoelectronics and quantum optics. After outlining the current state-of-the-art QD syntheses, the experimental and computational analysis of QDs is discussed. These topics are then connected to the methodologies, processes and concepts required for developing QD-based photodetectors, light-emitting devices and quantum optics applications. Special attention is paid to challenges in reproducibility and current limitations of the field, such as the need to balance non-restricted material composition with high performing technology while achieving long-term stability in QD devices under operating conditions. Finally, the ongoing advancement in QD synthesis, precise atomic-level analysis and computational methodologies are highlighted as key drivers towards rational QD design, particularly in understanding how structural changes under loading impact QD properties.

optical materials↗
DOE OSTI2022

New challenges in oxygen reduction catalysis: a consortium retrospective to inform future research

In this perspective, we highlight results of a research consortium devoted to advancing understanding of oxygen reduction reaction (ORR) catalysis as a means to inform fuel cell science. We demonstrate how targeted collaborations between different institutions from academic, national lab, and industry backgrounds and different scientific disciplines like theory, experiment, and characterization can yield unique insights into fuel cell catalysts. We comment on such insights into material designs for platinum-group-metal alloys, transition metal oxides, and non-traditional materials including metal–organic frameworks; systems that have served as the foundational building blocks for our consortium. We also motivate a renewed focus on catalyst durability in light of emerging technological requirements and paths forward in understanding in situ and operando electrochemical stability. Lastly, we describe new frontiers ORR research can take and how emerging artificial intelligence tools can assist researchers in capturing data, selecting new experiments, and guiding characterization to accelerate the design and discovery of fuel cell catalysts. A main goal of sharing this perspective is to discuss the rationale for our future research plans based on our consortium work. However, we also hope to illustrate both the potential impact of a collaborative strategy with the hopes of inspiring a higher degree of Industry-Academia-National Laboratory collaboration and encourage other centers and consortiums to distill and share their findings in a similar perspective-type article. Together we hope to enable the fuel cell research community to engage in a discussion of strategies for research and accelerated development of catalysts with improved activity and stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

FY2020 LDRD Annual Report

The Laboratory Directed Research and Development (LDRD) program funds scientific efforts to build upon the unique knowledge base of Savannah River National Laboratory (SRNL). The program yields foundational scientific research and development (R&D) essential to SRNL’s core business areas, while aligning optimally and continuously with SRNL’s Strategic Plan and providing long-term benefits to DOE and the National Nuclear Security Administration (NNSA), other customers, and stakeholders. While fiscal year (FY) 2020 presented unprecedented challenges due to the COVID-19 global pandemic, the SRNL research team continued to advance science and further technology through the support of the LDRD program.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Alaska Meteorology, Energy, and Transmission (MET) Toolkit

The Alaska MET (Meteorology, Energy, and Transmission) Toolkit is the National Laboratory of the Rockies' (NLR) new flagship atmospheric dataset, designed to support comprehensive long-term planning and operations across the entire power sector. Serving as the regional counterpart to CONUS-wide HRRR MET Toolkit, this dataset provides a comprehensive, high-fidelity meteorological record covering Alaska.The Alaska MET Toolkit is delivered at an hourly resolution on a standardized 2-km horizontal grid. This dataset is repackaged from the National Oceanic and Atmospheric Administration's (NOAA) operational High-Resolution Rapid Refresh for Alaska (HRRR-AK) forecasts. Spanning from 2019 to 2025, it overcomes the technical barriers of native weather models by providing spatial regridding from the native 3-km HRRR-AK horizontal resolution to a 2-km grid, temporal gap-filling, and vertical interpolation at key energy-relevant heights. By delivering highly accurate, validation-backed data across a comprehensive suite of atmospheric variables - including temperature, pressure, humidity, and wind characteristics - the Alaska MET Toolkit provides a highly accessible and strictly standardized foundation for modern power system modeling.

17 WIND ENERGY↗
DOE OSTI2025

Yes, No, Maybe So: Human Factors Considerations for Fostering Calibrated Trust in Foundation Models Under Uncertainty

High-stakes analytical environments require analysts to evaluate evidence and generate conclusions to inform critical decisions often under conditions of uncertainty. Probabilistic decision-making based on incomplete or inaccurate information can reduce productivity, compromise national interests, and endanger public safety. Researchers are developing expert systems built on foundation models (FMs) to support analysts’ decision-making processes by enabling human-artificial intelligence (AI) teaming, in part through the quantification and expression of uncertainty information. As FMs continue to mature, it is imperative to correspondingly consider analysts’ needs for appropriately interpreting and using uncertainty information. However, prior research indicates that it remains unclear how analysts engage with FM-generated uncertainty information and the extent to which these interactions influence trust in, and reliance on, expert systems. We plan to review the state of the science and conduct an exploratory, qualitative study to (a) understand how properly communicated uncertainty can foster calibrated trust and appropriate reliance and (b) identify approaches for effectively conveying FM-generated uncertainty information during analytical workflows. We will administer semi-structured interviews with analysts from a specific high-stakes analytical environment to collect their current experiences with job-related uncertainty and their impressions when viewing FM-generated uncertainty information. During the interview protocol, participants will be presented with several different FM outputs and invited to discuss their thoughts and beliefs about the uncertainty information displayed. Participants may provide insights into how trust and reliance may be influenced by uncertainty. The results of this study will help us to better understand how analysts currently interpret and use uncertainty information. Our findings may inform human factors recommendations for effectively conveying uncertainty information to foster calibrated trust in, and appropriate reliance on, expert systems. Interaction designers and FM developers can use this knowledge to enhance human-AI teaming and ensure the responsible deployment of FM-based expert systems in analytical workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Excitonic Anisotropy in Single‐Crystalline 2D Silver Phenylchalcogenides

2D materials exhibiting in‐plane anisotropy enable new applications in directional energy transport and polarized optical response. Silver phenylchalcogenides (AgEPh) – including mithrene (AgSePh), tethrene (AgTePh), and thiorene (AgSPh) – represent an exciting new addition to this family, with optical response spanning the visible to near‐UV. Here, excitonic anisotropy is predicted and characterized in this family of materials using a combination of ab initio theory and optical micro‐spectroscopy of single‐crystalline flakes. Using density functional theory and GW with the Bethe–Salpeter equation calculations, it is revealed that all AgEPh compounds exhibit anisotropic electronic band structure and host multiple delocalized excitons with in‐plane anisotropy. Room‐temperature polarization‐resolved optical micro‐spectroscopy shows that orthogonally polarized excitons with similar energy lead to nearly isotropic absorption in AgSPh, whereas energy separation between excitonic resonances in AgSePh and AgTePh leads to strong absorption and emission anisotropy. Cryogenic reflectance micro‐spectroscopy further reveals exciton fine structure in AgSePh, reconciling the discrepancies between room‐temperature experiments and theoretical predictions. Finally, it is demonstrated that the optical response of thicker AgEPh crystals is influenced by photonic effects arising from finite crystal size. Overall, this work advances the understanding of the relationship between anisotropic structure, composition, and excitonic properties in AgEPh, providing a foundation for technological integration.

2D↗
DOE OSTI2023

Advanced Simulation and Computing: ASC FY24 Implementation Plan

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent. The ASC program is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification process, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This work requires a balance of resources, including technical staff, hardware, simulation software, and computer science solutions. The ASC program focuses on increasing the predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The Program continues to improve its unique tools for understanding and solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), and quantifying critical margins and uncertainties. Resolving each issue requires increasingly difficult analyses because the aging process has progressively moved the stockpile further from the original test base. While the focus remains on the U.S. nuclear weapons program, where possible, the Program also enables the use of high-performance computing (HPC) and simulation tools to address broader national security needs, such as foreign nuclear weapon assessments and nuclear counterterrorism. The 2022 Nuclear Posture Review (NPR) calls for NNSA to “deliver a modern, adaptive nuclear security enterprise based on an integrated strategy for risk management, production-based resilience, science and technology innovation, and workforce initiatives.” Furthermore, “NNSA will establish a Science and Technology Innovation Initiative to accelerate the integration of science and technology (S&T) throughout its activities.” Executing this strategy necessitates the continued emphasis on developing and sustaining high-quality scientific and engineering staff, as well as supporting computational and experimental capabilities. These components constitute the foundation of the nuclear weapons program. The continued success of the SSP and LEPs is predicated upon the ability to credibly certify the stockpile, without a return to underground nuclear tests (UGTs). Shortly after the nuclear test moratorium entered into force in 1992, the Accelerated Strategic Computing Initiative (ASCI) was established to provide an extensive simulation capability to underpin stockpile certification. While computing and simulation have always been essential to the success of the nuclear weapons program, the program goal of ASCI was to execute NNSA’s vision of using these tools in support of the stockpile stewardship mission. The ASCI program was essential to the successful demonstration of the SSP, providing critical nuclear weapons simulation and modeling capabilities. ASCI officially evolved into the ASC program in fiscal year (FY) 2005, but the mission remains essentially the same: provide the simulation and computational capabilities that underpin the ability to maintain a safe, secure, effective nuclear weapon stockpile, without returning to underground nuclear testing. The capabilities that the ASC program provides at the national laboratories play a vital role in the nuclear security enterprise and are necessary for fulfilling the stockpile stewardship and life extension requirements outlined for NNSA. The Program develops modern simulation tools that provide insights into stockpile aging issues, provide the computational and simulation tools that enable designers and analysts to certify the current stockpile and life-extended nuclear weapons, and inform the decision-making process when any modifications in nuclear warheads or the associated manufacturing processes are deemed necessary. Furthermore, ASC is enhancing the predictive simulation capabilities that are essential to evaluate weapons effects, design experiments, and ensure test readiness. The ASC program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Stockpile Management and Production Modernization programs (formerly Directed Stockpile Work) also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these life extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Prioritizing Nuclear Materials for SAM-3 Neutron Irradiation Campaign: Structural and Cladding Materials Candidates

This report outlines a framework for selecting structural and cladding materials for the Nuclear Science User Facilities (NSUF) SAM-3 neutron irradiation campaign to support the advancement of nuclear energy technologies. The document begins with an introduction that provides background context, highlights the motivations for launching a new irradiation campaign, and defines the overall objectives. The core of the report describes the design considerations for the irradiation campaign, including capsule configurations, irradiation temperature ranges, and target dose levels (defined by displacements per atom, or dpa). The material recommendation was guided by the Specimen Identification and Prioritization (SIP) Working Group, a multidisciplinary team of experts representing national laboratories, academia, industry, federal government and agency. This group played a central role in identifying candidate materials, evaluating technical justifications, and ensuring alignment with boarder programmatic goals. A detailed set of criteria for material prioritization is then presented, taking into account reactor relevance, performance gaps, advanced manufacturing methods, and emerging material classes. Based on the input of SIP working group, specific materials were selected and justified for inclusion in the irradiation campaign by the NSUF leadership and its U.S. Department of Energy (DOE)-Office of Nuclear Energy (NE) management. The final section provides recommended capsule designs, summarizing critical parameters such as material type, fabrication method, sample geometry, irradiation conditions, and specimen quantities. This report serves as a foundation for executing a focused and high-impact neutron irradiation campaign aimed at addressing key materials challenges for both existing and advanced nuclear reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Comprehensive Study of the Potential of Extracting and Processing Critical Minerals from Coal-Based Resources - Phase I

The Phase I report prepared for the Department of Energy addresses U.S. Executive Order 13817 titled A Federal Strategy to Ensure Secure and Reliable Supplies of Critical Minerals, issued on December 20, 2017, that lists 35 critical minerals that are vulnerable to supply disruption. A comprehensive review of each of the minerals was conducted to determine the criticality based primarily on extractability from coal-based resources. Several other factors were also considered such as gaps in supply and demand, use in current technology, and the existence of viable substitutes. It was determined that the critical minerals that show highest potential for extraction from coal-based resources are lithium, rare earth elements (REEs), cobalt, and manganese. All four of the critical minerals listed serve an important role in the technology industry, have few substitutes, and have a heavy import reliance. Most notably are lithium, which is widely used in the electric vehicle industry, and the REEs which can be found in virtually all electronic devices. The research of critical mineral extraction from coal-based resources was completed using a combination of literature review from public sources as well as cooperation from coal mines and power plants across the United States. Samples collected from six different geographical locations across the U.S. were subjected to sample preparation (i.e., pH measurement, moisture content, particle size analysis) and characterization studies using Inductively Coupled Plasma-Mass Spectroscopy (ICP-MS) and Scanning Electron Microscopy, Energy Dispersive X-Ray Spectroscopy (SEM-EDX) instruments. 27 samples of coal waste materials such as refuse, sludge, and fly ash were tested to characterize the rare earth element concentration by total rare earth elements (TREEs), heavy rare earth elements (HREEs), and light rare earth elements (LREEs). Of the 27 samples tested, 22 contained a TREE concentration higher than the threshold of 300 ppm, which is considered a viable feedstock material. 3 samples contained less than 300 ppm of TREEs; however, they were within 20 ppm of the threshold, and could potentially be considered viable sources in the future pending the advancement of more efficient extraction technologies. 2 of the 27 samples had significantly low TREE concentrations, which does not imply any potential for being a source for REEs. For the minerals identified as most critical in the literature review, a conceptual process flow diagram (PFD) was developed for their extraction from different coal-based feedstocks. The process targets selective recovery of one commodity (i.e., rare earths, lithium, cobalt, and manganese) via several hydrometallurgical separation methods. By identifying potentially extractable coal-based critical mineral resources, a study of the current and future market environments for each critical mineral, and a review of current processing methodologies for critical mineral extraction from coal-based resources, the foundation has been laid to further characterize and explore new resources and extraction techniques. As reliance on technologies in industries such as the production of electronic devices, batteries, and alloys containing critical minerals utilizing critical minerals continues to increase, a sound understanding of our nation’s dependence on and even the global criticality of certain critical minerals, will serve as a catalyst for innovation in virtually all fields of science.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Correlation of Band Bending and Ionic Losses in 1.68 eV Wide Band Gap Perovskite Solar Cells

Abstract Perovskite solar cells (PSCs) are promising for high‐efficiency tandem applications, but their long‐term stability, particularly due to ion migration, remains a challenge. Despite progress in stabilizing PSCs, they still fall short compared to mature technologies like silicon. This study explores how different piperazinium salt treatments using iodide, chloride, tosylate, and bistriflimide anions affect the energetics, carrier dynamics, and stability of 1.68 eV bandgap PSCs. Chloride‐based treatments achieved the highest power conversion efficiency (21.5%) and open‐circuit voltage (1.28 V), correlating with stronger band bending and n‐type character at the surface. At the same time, they showed reduced long‐term stability due to increased ionic losses. Tosylate‐treated devices offered the best balance, retaining 96.4% efficiency after 1000 h (ISOS‐LC‐1I). These findings suggest that targeted surface treatments can enhance both efficiency and stability in PSCs.

14 SOLAR ENERGY↗
DOE OSTI2025

Deciphering Catalyst–Support Interaction via Doping for Highly Active and Durable Oxygen Evolution Catalysis

The design of oxygen evolution reaction (OER) electrocatalysts demands a delicate balance between activity and stability. Here, in this study, we present a rational design approach that leverages catalyst-support interactions to enhance both the intrinsic activity and durability of Ir-based catalysts. Our study reveals that while Mo doping energetically promotes the formation of high-valent Ir species, enhancing intrinsic catalytic activity, it also leads to a reduction in electrical conductivity. These findings emphasize that supporting doping can introduce both beneficial and limiting effects, highlighting the need for a carefully balanced design strategy to optimize the overall OER performance. Simultaneously, in situ analytical techniques and comparative evaluation reveal the crucial role of oxide supports in stabilizing the catalyst. These findings highlight the pivotal role of interface engineering in maintaining catalyst integrity and the need for support materials that balance dopant-driven electronic promotion with structural and electrochemical robustness. These interconnected degradation pathways highlight the need to move beyond a catalyst-centric view and instead adopt a system-level understanding of the stability. Our approach offers a strong foundation for the rational design and evaluation of high-performance OER electrocatalysts for electrochemical energy applications.

Kim, Jinyeop [Korea Advanced Inst. Science and Tec↗
DOE OSTI2026

A Discrete Hankel Transform Approach to Nuclear Data Processing for Fusion Applications

This study introduces advancements to the numerical solutions employed in the processing of nuclear data for fusion applications. It leverages the convolution theorem and Fourier transform techniques to enhance computational efficiency and broaden applicability. Building upon a previously reported discrete Hankel transform approach for Doppler broadening, this work refines the solution of convolution integrals central to these applications. The methodology provides a general and unified framework for evaluating any convolution operation, regardless of whether the underlying problem involves temperature effects in nuclear reactions. The applicability to the nuclear data processing for fusion is demonstrated by deriving the convolution integrals for some of the fusion-related quantities. As before, the convolution operation utilizes a Gaussian-based kernel; however, the discrete Hankel transform of order $𝛼$ = $\frac{1}{2}$ is now applied to the forward Fourier transform of the nonkernel argument, rather than the inverse Fourier transform. This modification eliminates the need for the integration of the nonkernel, cross section–based function, which is a step that posed challenges for certain pointwise cross-section representations. It also removes the requirement for cross-section linearization. Optimized for graphics processing unit architectures, the approach significantly improves computational performance. These advancements are currently under evaluation as the foundation for the next-generation thermonuclear data file processing codes being developed at Lawrence Livermore National Laboratory.

Nuclear science and engineering↗
DOE OSTI2024

MSD CoP Webinar: Metrics for Human Wellbeing

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Human well-being is an inherently multidimensional concept that broadly refers to what constitutes the "good life". Characterizing well-being requires a wide range of measures of quality of life. Taken together, these can provide a description of well-being and better guide decision making. In this webinar, our panel will first summarize the key themes and recommendations of interdisciplinary conversations that occurred during the course of a two-day, in-person workshop convened by PNNL September 27-28, 2023, which laid the foundations for a new research direction of well-being science and application. Next, they will present research exploring several dimensions of human well-being and their links to equity: energy security, food security, and economic measures. Finally, we will introduce the new Equity Working Group, gather community input to inform its activities, and provide avenues for ongoing engagement. Presenters : Stephanie Waldhoff (Joint Global Change Research Institute, Pacific Northwest National Laboratory; Invited Speaker), Brian O'Neill (Joint Global Change Research Institute, Pacific Northwest National Laboratory; Invited Speaker), Rebecca Saari (University of Waterloo; Co-Chair), Amanda Giang (University of British Columbia; Co-Chair), Sarah Fletcher (Stanford University; Co-Chair), and Matt Sparks (University of Waterloo; Communications Officer) Moderator: Pat M. Reed (MSD CoP Facilitation Team) This webinar was held on: May 29, 2024 from 1-2:15 PM ET

Equity↗
DOE OSTI2026

Toward a microscopic picture of hadronization and multi-parton processes

This project advanced the understanding of how quarks and gluons produced in high-energy collisions transform into the hadrons observed in particle detectors, a fundamental process known as quantum chromodynamics (QCD) hadronization. By combining theoretical calculations, quantum simulation methods, and modern AI techniques, the research developed new tools to study multi-parton dynamics and nonperturbative effects that are essential for interpreting data from current and future nuclear physics experiments. Key outcomes include new theoretical frameworks for jet and hadron measurements, pioneering quantum simulation algorithms for real-time dynamics in field theories, and the development of advanced machine-learning models, such as diffusion models and explainable classifiers, to simulate and analyze collider events. These results are directly relevant to experiments at Jefferson Lab, Brookhaven National Laboratory, and the future Electron-Ion Collider, and they also have a broader impact in areas such as quantum information science and data-driven modeling of complex systems. The project supported the training of graduate students and postdoctoral fellows and contributed to the broader scientific community through publications, workshops, and collaborative activities. Overall, this work provides new insights into the microscopic mechanisms of hadron formation and establishes a foundation for future studies at the intersection of nuclear physics, artificial intelligence, and quantum computing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Quantum geometry in quantum materials

Quantum geometry, characterized by the quantum geometric tensor, plays a central role in diverse physical phenomena in quantum materials. This pedagogical review introduces the concept and highlights its implications across multiple domains, including optical responses, Landau levels, fractional Chern insulators, superfluid weight, spin stiffness, exciton condensates, and electronphonon coupling. By integrating these topics, we emphasize the broad significance of quantum geometry in understanding emergent behaviors in quantum systems and conclude with an outlook on open questions and future directions.

Condensed-matter physics↗