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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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At least 19 records

Developing and Evaluating Energy Justice Metrics for Early-Stage Materials Research

Materials science is a central component of early-stage research and development of virtually all clean energy technologies. But as much as material breakthroughs often hold the key to high efficiencies, long lifetimes, and high stability in eventual devices, early-stage choices about material types, structures, and processing can also serve to lock in long-term social and equity impacts of deployed energy technologies. Thus, to achieve a just and sustainable energy transition, tools to assess the energy justice impacts of early-stage materials research are critical. Here, we discuss development of the Justice Underpinning Science and Technology Research (JUST-R) metrics framework - a suite of metrics targeted at early-stage researchers to assess energy justice considerations in their work. The framework is evaluated for its appeal to researchers and effectiveness at promoting integration of energy justice into research through case studies, which reveal its ability to broaden researcher perspectives and key avenues for future improvement.

energy justice↗

A new capability facilitating nuclear materials research: the Activated Materials Laboratory at the Advanced Photon Source

The Activated Materials Laboratory (AML), located in the Long Beamline Building (LBB) of the Advanced Photon Source (APS) of Argonne National Laboratory (ANL), serves as a centralized radiological facility for preparing radioactive samples for APS beamline experiments. The AML is equipped to receive shipments, handle open-form radioactive materials, encapsulate samples, and transport samples to-and-from beamline end-stations. The AML works closely with users and the APS radiological safety committee to make sure the safe conduct of experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Artificial intelligence for materials research at extremes

Abstract Materials development is slow and expensive, taking decades from inception to fielding. For materials research at extremes, the situation is even more demanding, as the desired property combinations such as strength and oxidation resistance can have complex interactions. Here, we explore the role of AI and autonomous experimentation (AE) in the process of understanding and developing materials for extreme and coupled environments. AI is important in understanding materials under extremes due to the highly demanding and unique cases these environments represent. Materials are pushed to their limits in ways that, for example, equilibrium phase diagrams cannot describe. Often, multiple physical phenomena compete to determine the material response. Further, validation is often difficult or impossible. AI can help bridge these gaps, providing heuristic but valuable links between materials properties and performance under extreme conditions. We explore the potential advantages of AE along with decision strategies. In particular, we consider the problem of deciding between low-fidelity, inexpensive experiments and high-fidelity, expensive experiments. The cost of experiments is described in terms of the speed and throughput of automated experiments, contrasted with the human resources needed to execute manual experiments. We also consider the cost and benefits of modeling and simulation to further materials understanding, along with characterization of materials under extreme environments in the AE loop. Graphical abstract AI sequential decision-making methods for materials research: Active learning, which focuses on exploration by sampling uncertain regions, Bayesian and bandit optimization as well as reinforcement learning (RL), which trades off exploration of uncertain regions with exploitation of optimum function value. Bayesian and bandit optimization focus on finding the optimal value of the function at each step or cumulatively over the entire steps, respectively, whereas RL considers cumulative value of the labeling function, where the latter can change depending on the state of the system (blue, orange, or green).

36 MATERIALS SCIENCE↗

Are We on Track for 2050? A Materials Research & Sustainability Perspective

In commemoration of the Materials Research Society (MRS)'s 50th anniversary, the 2050 panel hosted a discussion to reflect on the past, present, and future of sustainability and the role of materials research and development. Three panelists discussed their views, based on their expertise, about future challenges and lessons from the past. Sustainable development is a broad topic; therefore, the discussion centered on their experience as material researchers and their efforts for a better and greener future. This work is developed in collaboration with the co-authors team, highlighting the need for accelerating research and development efforts, especially in materials science and applications, fostering interdisciplinary partnerships, and mobilizing collective action to address the complex and interconnected sustainability challenges that humanity is currently facing.

ENERGY PLANNING, POLICY, AND ECONOMY,ENVIRONMENTAL↗

Light Water Reactor Sustainability: Program Materials Research Pathway (FY22 Technical Program Plan)

The Materials Research (MR) Pathway within the Light Water Reactor Sustainability (LWRS) program is charged with performing R&D to develop the scientific basis for understanding and predicting the long-term environmental degradation behavior of materials in nuclear reactors. Furthermore, the mechanistic understanding of degradation phenomena in materials must be leveraged to develop mitigation and repair strategies and new material alternatives for existing components. This research will provide data and methods to assess the performance of systems, structures, and components essential to safe and sustained reactor operations. The R&D products developed from the LWRS program will be used by stakeholders—including utilities, industry groups, and regulators—to inform operational and regulatory requirements for materials in reactor systems, structures, and components subjected to long-term operation conditions, providing key inputs to regulators and industry. Therefore, the intent of this research is to provide options to reduce the operating costs, which may be in the form of offset maintenance costs due to better predictive models for component lifetimes, improved analyses of materials through nondestructive evaluation, reduced costs for repairs, or extended performance of plants through the selection of improved replacement materials. To provide the best options, industry experience and guidance are important because of their role in coordinated or collaborative research projects. The objectives of this report are to describe the motivation and organization of the MR Pathway within the LWRS program; provide details on the individual research tasks within the MR Pathway; describe the outcomes and deliverables of the MR Pathway, including recent technical highlights and progress; and describe the requirements for performing this critically important research.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Towards physics-informed explainable machine learning and causal models for materials research

From emergent material descriptions to estimation of properties stemming from structures to optimization of process parameters for achieving best performance – all key facets of materials science and related fields have experienced tremendous growth with the introduction of data-driven models. This gradual progression goes at par with developments of machine learning workflows, from purely data-driven shallow models to those that are well-capable in encoding more complex graphs, symbolic representations, invariances, and positional embeddings. Furthermore, this perspective aims at summarizing strategic aspects of such transitions while providing insights into the requirements of bringing in explainable, interpretable predictive models, and causal learning to aid in materials design and discovery. Although the focus remains on a variety of functional materials by providing a handful of case studies, the applications of such integrated methodologies are universal to facilitate fundamental understandings of materials physics while enabling autonomous experiments.

36 MATERIALS SCIENCE↗

Applying energy justice metrics to photovoltaic materials research

Abstract Achieving the energy transition sustainably requires addressing how new technologies may impact justice in the energy system. The Justice Underpinning Science and Technology Research (JUST-R) metrics framework was recently proposed to aid researchers in considering justice in early-stage research on energy technologies; however, case study evaluations of the framework revealed a desire from researchers to see metrics specialized to particular fields of study. Here, we refine metrics from the JUST-R framework to enhance its applicability to photovoltaic (PV) materials research. Metrics are reorganized to align with aspects of the research process (e.g., research team or source materials). For most metrics, baseline values are suggested to enable researchers to compare their project to competing technologies or standards at their institutions. These refinements are integrated into a tool to facilitate easier understanding and evaluation of justice considerations in early-stage PV research, which can serve as a template for evaluating other energy technologies. Graphical abstract

14 SOLAR ENERGY↗

Evaluating Technology Adoption Risks in Early-Stage Materials Research

Development of new technologies often begins with fundamental materials science research. Decisions at this stage can shape factors related to the eventual adoption readiness of the technology, such as process scalability or materials availability. Here we present the early-Stage Technology Evaluation for Adoption Risks (STEAR) framework as a method for qualitatively assessing metrics spanning four categories of adoption risks: value proposition, market acceptance, resource maturity, and license to operate. We conduct a case study applying STEAR to different methanol production processes at a range of technology readiness levels and demonstrate how the assessment identifies key challenges related to adoption readiness. Finally, we discuss efforts to expand the applicability and utility of STEAR, including focus group feedback and complementary quantitative analysis methods.

36 MATERIALS SCIENCE↗

Ultrasonic Resonance Techniques for Materials Research

Mechanical resonances are directly related to the physical behavior of a system at the bulk and microscopic levels. In materials science, resonant ultrasound spectroscopy (RUS) has long been a preferred nondestructive method to study mechanical resonances of solids and precisely measure quantitative material properties, namely elasticity. In recent years, advances in computational power and hardware have enabled RUS to be relevant for an increasing range of applications, such as advanced manufacturing. An extension of this technique, nonlinear RUS (NRUS), has been demonstrated to provide unmatched sensitivity to early-stage damage. NRUS was originally developed to probe geologic materials but has become a vital tool in nondestructive evaluation and materials research, offering a powerful means of quantifying and characterizing microstructural nonlinearity in a broad range of materials. This review summarizes recent developments and growth opportunities in RUS and NRUS techniques, modeling, and applications across a wide range of material systems including metals, composites, geomaterials, and explosives.

36 MATERIALS SCIENCE↗

Materials Research for Battery Recycling

This presentation for the summer 2024 class of Energy Execs offers a summary of materials research work for battery recycling conducted at NREL.

battery recycling↗

ALchemist (Active Learning Toolkit for Chemical and Materials Research) [SWR-25-102]

ALchemist is a modular Python toolkit that brings active learning and Bayesian optimization to experimental design in chemical and materials research. It is designed for scientists and engineers who want to efficiently explore or optimize high-dimensional variable spaces—without writing code—using an intuitive graphical interface.

Coatney, Caleb [National Renewable Energy Laborato↗

Capability Needs for Irradiated and Radioactive Materials Research (Ad hoc Committee Summary Report)

It is essential for the U.S. nuclear energy community to have access to world-leading equipment suitable for conducting research on both nuclear fuels and structural materials, including neutron irradiated–and therefore activated–materials. To address future research infrastructure requirements to support the DOE-NE mission, the Office of Reactor Fleet and Advanced Reactor Deployment established an ad hoc committee to gather information on potential capability gaps for radioactive materials and radiation effects research. This document summarizes the discussions of the committee addressing the high-level challenges in irradiated and radioactive materials research and the capabilities needed to address these challenges. After considering the various needs, the committee agreed on the four top-level targets and priority capability gaps.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

In-situ heating-and-electron tomography for materials research: from 3D ( In-situ 2D) to 4D ( In-situ 3D)

In-situ observation has expanded the application of transmission electron microscopy (TEM) and has made a significant contribution to materials research and development for energy, biomedical, quantum, etc. Recent technological developments related to in-situ TEM have empowered the incorporation of three-dimensional observation, which was previously considered incompatible. In this review article, we take up heating as the most commonly used external stimulus for in-situ TEM observation and overview recent in-situ TEM studies. Then, we focus on the electron tomography (ET) and in-situ heating combined observation by introducing the authors’ recent research as an example. Assuming that in-situ heating observation is expanded from two dimensions to three dimensions using a conventional TEM apparatus and a commercially available in-situ heating specimen holder, the following in-situ heating-and-ET observation procedure is proposed: (i) use a rapid heating-and-cooling function of a micro-electro-mechanical system holder; (ii) heat and cool the specimen intermittently and (iii) acquire a tilt-series dataset when the specimen heating is stopped. This procedure is not too technically challenging and can have a wide range of applications. Essential technical points for a successful 4D (space and time) observation will be discussed through reviewing the authors’ example application.

36 MATERIALS SCIENCE↗

Theory-guided experimental design in battery materials research

A reliable energy storage ecosystem is imperative for a renewable energy future, and continued research is needed to develop promising rechargeable battery chemistries. To this end, better theoretical and experimental understanding of electrochemical mechanisms and structure-property relationships will allow us to accelerate the development of safer batteries with higher energy densities and longer lifetimes. This Review discusses the interplay between theory and experiment in battery materials research, enabling us to not only uncover hitherto unknown mechanisms but also rationally design more promising electrode and electrolyte materials. We examine specific case studies of theory-guided experimental design in lithium-ion, lithium-metal, sodium-metal, and all-solid-state batteries. We also offer insights into how this framework can be extended to multivalent batteries. To close the loop, we outline recent efforts in coupling machine learning with high-throughput computations and experiments. Last, recommendations for effective collaboration between theorists and experimentalists are provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Addendum to Capability Needs for Irradiated and Radioactive Materials Research (Ad Hoc Committee Summary Report)

Nuclear materials and fuels studies are challenging research and engineering targets because of their inherent radioactivity as well as their heterogeneous microstructure. Advanced light sources have made significant underpinning scientific contributions to the understanding of structural and fuel cladding material microstructure and properties and the development of structure-property relationships. These facilities have the potential to help advance the Department of Energy (DOE) Office of Nuclear Energy (DOE-NE) mission priorities providing underpinning understanding of technically important challenges, including: irradiation induced embrittlement and swelling; stress corrosion cracking and corrosion in extreme environments; ageing of reactor pressure vessels steels; nuclear fuel characterization; and nuclear waste form optimization as well as playing a major role in the development of a materials performance matrix to aid in the design of new materials to meet the needs of advanced reactor concepts. However, the delivery of underpinning understanding is the mission of DOE Office of Science (DOE-SC). While filling such knowledge gaps is important, efforts in this direction should not be confused with the strategic technology focused mission goals of DOE-NE to enable the continued operation of existing U.S. nuclear reactors, to enable the deployment of advanced nuclear reactors, to develop advanced nuclear fuel cycles, and to maintain U.S. leadership in nuclear energy technology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Magnetic Materials Research at SRNL

Introduction – What are Magnetic Materials? Magnetic materials are crystalline solids which below a certain temperature, known as the ordering temperature, display spontaneous order in their magnetic moments. Results • Enhanced thermal stability and saturation magnetization with Y substitution in Ce2Fe14B based permanent magnets • Discovered a new ferromagnetic phase transition at TC = 62.9 K in (Dy1/3Mo2/3)2AlC and validated the two previously reported low temperature magnetic phases Characterization of Magnetic Materials Raw high purity materials are melted together to synthesize a crystalline sample using an arc melter at Savannah River National Laboratory (SRNL). Use high energy ball milling to form a hard/soft magnetic composite using Y substituted Ce2Fe14B. Finish structural characterization on γ- irradiated (RE1/3Mo2/3)2AlC (RE = Rare Earth) MAX samples. Unit Cell Lattice Points

Bretana, Alex↗