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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 OSTI2020

Fuel Conversion Efforts at the High Flux Isotope Reactor – a 2020 Status Update

The High Flux Isotope Reactor (HFIR) provides one of the world’s highest steady-state neutron fluxes in the world for neutron scattering experiments focused on impactful scientific discovery, as well as materials irradiation studies and production of medical, industrial, and research isotopes. Efforts are ongoing to convert HFIR from high-enriched uranium (HEU) to low-enriched uranium (LEU) fuel while maintaining or enhancing current performance and safety margin, thus sustaining HFIR’s mission portfolio and reactor-based neutron science leadership. This paper presents a status update on the HFIR fuel conversion efforts.

Chandler, David↗
DOE OSTI2023

Fuel Conversion Efforts at the High Flux Isotope Reactor – a 2023 Status Update

The High Flux Isotope Reactor (HFIR) provides one of the world’s highest steady-state neutron fluxes in the world for neutron scattering experiments focused on impactful scientific discovery, as well as materials irradiation studies and production of medical, industrial, and research isotopes. Efforts are ongoing to convert HFIR from high-enriched uranium (HEU) to low-enriched uranium (LEU) fuel while maintaining or enhancing current performance and safety margin, thus sustaining HFIR’s mission portfolio and reactor-based neutron science leadership. This paper presents a status update on the HFIR fuel conversion efforts.

Sizemore, Carol↗
DOE OSTI2024

Surface-Enhanced Raman Spectroscopy Combined with Multivariate Analysis for Fingerprinting Clinically Similar Fibromyalgia and Long COVID Syndromes

Fibromyalgia (FM) is a chronic central sensitivity syndrome characterized by augmented pain processing at diffuse body sites and presents as a multimorbid clinical condition. Long COVID (LC) is a heterogenous clinical syndrome that affects 10–20% of individuals following COVID-19 infection. FM and LC share similarities with regard to the pain and other clinical symptoms experienced, thereby posing a challenge for accurate diagnosis. This research explores the feasibility of using surface-enhanced Raman spectroscopy (SERS) combined with soft independent modelling of class analogies (SIMCAs) to develop classification models differentiating LC and FM. Venous blood samples were collected using two supports, dried bloodspot cards (DBS, n = 48 FM and n = 46 LC) and volumetric absorptive micro-sampling tips (VAMS, n = 39 FM and n = 39 LC). A semi-permeable membrane (10 kDa) was used to extract low molecular fraction (LMF) from the blood samples, and Raman spectra were acquired using SERS with gold nanoparticles (AuNPs). Soft independent modelling of class analogy (SIMCA) models developed with spectral data of blood samples collected in VAMS tips showed superior performance with a validation performance of 100% accuracy, sensitivity, and specificity, achieving an excellent classification accuracy of 0.86 area under the curve (AUC). Amide groups, aromatic and acidic amino acids were responsible for the discrimination patterns among FM and LC syndromes, emphasizing the findings from our previous studies. Overall, our results demonstrate the ability of AuNP SERS to identify unique metabolites that can be potentially used as spectral biomarkers to differentiate FM and LC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Enhancement of Carbon Capture Reactor Performance (Final Technical Report)

Significant challenges are still present in post-combustion CO 2 capture and new technologies and advanced components are needed to significantly advance the deployment of CO 2 capture for natural gas combined cycle (NGCC) plants. Critical elements of CO 2 capture that still need to be addressed include how to increase CO 2 mass transfer in the absorber column with liquid to gas ratios of <1.2, while reducing the size of the absorber column to reduce capital costs. Research involving chemical mechanism with design, synthesis, and assembly of materials with targeted functionally were combined with advanced additive manufacturing techniques towards development of enhanced CO 2 capture reactors that can lead to safe, reliable, and low-cost carbon capture technologies. The objective of the project was to develop and test novel carbon capture materials and reactor components that contribute to increased CO 2 mass transfer through increased turbulent gas-liquid interface and improved solvent wetting within the absorber. A technoeconomic analysis (TEA) was completed showing how the proposed technology decreases capital costs by reducing the size of the absorber column and the amount of packing required for high CO 2 capture rates. A technology maturation plan (TMP) was also developed to describe the current technology readiness levels (TRL) and outline additional research and development (R&D) needed to further develop these advanced components for NGCC CO 2 capture plants. The successful completion of this project has shown a pathway to reduce the absorber size and associated construction costs of post-combustion NGCC CO 2 capture systems at 97% capture and promote the utilization of abundant natural gas for production of reliable electricity.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Förster Resonance Energy Transfer and Enhanced Emission in Cs 4 PbBr 6 Nanocrystals Encapsulated in Silicon Nano-Sheets for Perovskite Light Emitting Diode Applications

Encapsulating Cs 4 PbBr 6 quantum dots in silicon nano-sheets not only stabilizes the halide perovskite, but also takes advantage of the nano-sheet for a compatible integration with the traditional silicon semiconductor. Here, we report the preparation of un-passivated Cs 4 PbBr 6 ellipsoidal nanocrystals and pseudo-spherical quantum dots in silicon nano-sheets and their enhanced photoluminescence (PL). For a sample with low concentrations of quantum dots in silicon nano-sheets, the emission from Cs 4 PbBr 6 pseudo-spherical quantum dots is quenched and is dominated with Pb 2+ ion/silicene emission, which is very stable during the whole measurement period. For a high concentration of Cs 4 PbBr 6 ellipsoidal nanocrystals in silicon nano-sheets, we have observed Förster resonance energy transfer with up to 87% efficiency through the oscillation of two PL peaks when UV excitation switches between on and off, using recorded video and PL lifetime measurements. In an area of a non-uniform sample containing both ellipsoidal nanocrystals and pseudo-spherical quantum dots, where Pb 2+ ion/silicene emissions, broadband emissions from quantum dots, and bandgap edge emissions (515 nm) appear, the 515 nm peak intensity increases five times over 30 min of UV excitation, probably due to a photon recycling effect. This irradiated sample has been stable for one year of ambient storage. Cs 4 PbBr 6 quantum dots encapsulated in silicon nano-sheets can lead to applications of halide perovskite light emitting diodes (PeLEDs) and integration with traditional semiconductor materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Capturing the fractocohesive length scale in elastomers through a statistical mechanics-based gradient enhanced damage model

Here, this study aims to examine modeling flaw sensitivity in elastomers. The direct incorporation of polymer chain statistical mechanics considerations into a continuum stretch-based gradient-enhanced damage formulation, in turn, allows a representation of diffuse chain damage and fracture events that align with known micromechanical mechanisms. Through a series of numerical experiments, we simulate crack propagation and extract the fracture energy as an output of the model, while keeping track of the micromechanical signatures of diffuse chain damage that accommodate fracture propagation and eventually influence flaw sensitivity. Finally, by combining the fracture toughness and the work to rupture, we identify a fractocohesive length of the material, corresponding to the full width of the damage process zone. As the damage-to-fracture cascade in the proposed GED model is influenced by the introduction of a length scale associated with network imperfection and long-range load transfer, the emerging relationship of the two length scales is discussed, providing a potential link between microscopic damage mechanisms and the observed macroscopic fracture response.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Laser Spectroscopy of Exotic Atoms and Molecules Containing Octupole-Deformed Nuclei

This project investigated the nuclear, atomic, and molecular structure of exotic atoms and molecules containing actinide isotopes. These short-lived radioactive systems are challenging to produce and study in the laboratory, yet they offer unique opportunities for fundamental science. These nuclei are predicted to exhibit pear-shaped (octupole) deformation, a rare collective nuclear behavior that dramatically enhances their sensitivity to fundamental physics phenomena such as time-reversal- and parity-violating effects. Such enhancements make them ideal probes for exploring open questions in our understanding of the universe such as the origin of the matter–antimatter asymmetry of the universe. To realize these measurements, the project led the development of a new laser spectroscopy experiment at MIT, and later commissioned at the Facility for Rare Isotope Beams (FRIB) at Michigan State University: the Resonance Ionization Spectroscopy Experiment (RISE). RISE combines the spectroscopic precision of collinear laser spectroscopy with the sensitivity of particle-detection techniques, enabling measurements of rare isotopes produced at rates as low as a few ions per second. The beamline was designed, built, and installed, and was successfully commissioned at FRIB during the grant period. RISE is now a permanent capability of the FRIB facility, and has produced several results on the study of rare atoms and molecules for nuclear structure and fundamental symmetries. In parallel with the FRIB program, the project contributed to the first precision laser-spectroscopy measurements of short-lived radioactive molecules. Working with international collaborators at CERN's ISOLDE facility, the team conducted pioneering experiments on radium monofluoride (RaF) and actinium monofluoride (AcF). The results from this work have been published in major journals of science, including Nature, Science, Nature Physics, Nature Communications, and Physical Review Letters. These findings have guided future experiments on the laser cooling of radioactive molecules, opening a new platform for precision tests of fundamental symmetries.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Laboratory Directed Research and Development Program: FY 2021 Completed Projects

Oak Ridge National Laboratory (ORNL) is the US Department of Energy’s (DOE’s) largest multiprogram science, technology, and energy laboratory. It possesses distinctive capabilities in neutron science, computing, advanced materials, nuclear science and technology, and other fields. Using these capabilities, ORNL conducts basic and applied R&D to support DOE’s overarching mission “to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.”1 As a national resource, ORNL also applies its capabilities and skills to specific needs of other federal agencies and customers through the DOE Strategic Partnership Projects (SPP) Program. Information about the laboratory and its programs is available on the ORNL website.2 The Laboratory Directed Research and Development (LDRD) Program at ORNL operates under the authority of the DOE Order 413.2C, “Laboratory Directed Research and Development,”3 which establishes DOE’s requirements for the program while providing the laboratory director broad flexibility for program implementation. The LDRD Program funds are obtained through a charge to all laboratory programs. Although it represents a relatively small portion of the overall research budget, the LDRD Program plays an essential role in maintaining the laboratory’s ability to respond to national needs. The program allows ORNL to improve its distinctive capabilities and to enhance its ability to conduct cutting-edge R&D. In accordance with the DOE order, R&D projects funded through the LDRD Program at ORNL support the following goals: (1) maintain the scientific and technical vitality of the laboratory; (2) enhance the laboratory’s ability to address future DOE missions; (3) foster creativity and stimulate exploration of forefront areas of science and technology; (4) serve as a proving ground for new concepts in R&D; and (5) support high-risk, potentially high-value R&D. This report provides an overview of the LDRD Program at ORNL in FY 2021 and contains summaries of all LDRD research projects that concluded between October 1, 2020, and September 30, 2021.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Modern chemical graph theory

Abstract Graph theory has a long history in chemistry. Yet as the breadth and variety of chemical data is rapidly changing, so too do graph encoding methods and analyses that yield qualitative and quantitative insights. Using illustrative cases within a basic mathematical framework, we showcase modern chemical graph theory's utility in Chemists' analysis and model development toolkit. The encoding of both experimental and simulation data is discussed at various levels of granularity of information. This is followed by a discussion of the two major classes of graph theoretical analyses: identifying connectivity patterns and partitioning methods. Measures, metrics, descriptors, and topological indices are then introduced with an emphasis upon enhancing interpretability and incorporation into physical models. Challenging data cases are described that include strategies for studying time dependence. Throughout, we incorporate recent advancements in computer science and applied mathematics that are propelling chemical graph theory into new domains of chemical study. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Structure and Mechanism > Computational Materials Science Structure and Mechanism > Molecular Structures

Leite, Leonardo S. G.↗
DOE OSTI2023

Less Is More: Oligomer Extraction and Hydrothermal Annealing Increase PDMS Adhesion Forces for Materials Studies and for Biology-Focused Microfluidic Applications

Cues in the micro-environment are key determinants in the emergence of complex cellular morphologies and functions. Primary among these is the presence of neighboring cells that form networks. For high-resolution analysis, it is crucial to develop micro-environments that permit exquisite control of network formation. This is especially true in cell science, tissue engineering, and clinical biology. We introduce a new approach for assembling polydimethylsiloxane (PDMS)-based microfluidic environments that enhances cell network formation and analyses. We report that the combined processes of PDMS solvent-extraction and hydrothermal annealing create unique conditions that produce high-strength bonds between solvent-extracted PDMS (E-PDMS) and glass—properties not associated with conventional PDMS. Extraction followed by hydrothermal annealing removes unbound oligomers, promotes polymer cross-linking, facilitates covalent bond formation with glass, and retains the highest biocompatibility. Herein, our extraction protocol accelerates oligomer removal from 5 to 2 days. Resulting microfluidic platforms are uniquely suited for cell-network studies owing to high adhesion forces, effectively corralling cellular extensions and eliminating harmful oligomers. We demonstrate the simple, simultaneous actuation of multiple microfluidic domains for invoking ATP- and glutamate-induced Ca 2+ signaling in glial-cell networks. These E-PDMS modifications and flow manipulations further enable microfluidic technologies for cell-signaling and network studies as well as novel applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Transcriptional network orchestrating regional patterning of cortical progenitors

We uncovered a transcription factor (TF) network that regulates cortical regional patterning in radial glial stem cells. Screening the expression of hundreds of TFs in the developing mouse cortex identified 38 TFs that are expressed in gradients in the ventricular zone (VZ). We tested whether their cortical expression was altered in mutant mice with known patterning defects (Emx2, Nr2f1, and Pax6), which enabled us to define a cortical regionalization TF network (CRTFN). To identify genomic programming underlying this network, we performed TF ChIP-seq and chromatin-looping conformation to identify enhancer–gene interactions. To map enhancers involved in regional patterning of cortical progenitors, we performed assays for epigenomic marks and DNA accessibility in VZ cells purified from wild-type and patterning mutant mice. This integrated approach has identified a CRTFN and VZ enhancers involved in cortical regional patterning in the mouse.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Materials laboratories of the future for alloys, amorphous, and composite materials

In alignment with the Materials Genome Initiative and as the product of a workshop sponsored by the US National Science Foundation, we define a vision for materials laboratories of the future in alloys, amorphous materials, and composite materials; chart a roadmap for realizing this vision; identify technical bottlenecks and barriers to access; and propose pathways to equitable and democratic access to integrated toolsets in a manner that addresses urgent societal needs, accelerates technological innovation, and enhances manufacturing competitiveness. Spanning three important materials classes, this article summarizes the areas of alignment and unifying themes, distinctive needs of different materials research communities, key science drivers that cannot be accomplished within the capabilities of current materials laboratories, and open questions that need further community input. Here, we provide a broader context for the workshop, synopsize the salient findings, outline a shared vision for democratizing access and accelerating materials discovery, highlight some case studies across the three different materials classes, and identify significant issues that need further discussion.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Measurements and Analyses to Enable Science for the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE)

Coastal cities provide the opportunity to characterize the substantial effects of manmade particles on marine cloud properties and processes. La Jolla lies to the north of San Diego, California, but it is often about a day directly downwind of the major pollution sources located in the ports of Los Angeles and Long Beach. The large dynamic range of aerosol particle concentrations combined with the multi-hour to multi-day persistence of stratocumulus cloud layers makes the site ideal for investigating the seasonal changes in cloud and aerosol properties as well as the quantitative relationships between cloud and aerosol properties. The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) characterized the extent, radiative properties, aerosol interactions, and precipitation characteristics of stratocumulus clouds in the Eastern Pacific across all four seasons at two coastal sites in La Jolla. This project was designed to enhance and expand the scientific uses of the ARM AMF1 measurements from EPCAPE. The goal was to ensure meaningful observations were collected that would enable science. The project included the following objectives: (1) Reviewing the ARM AMF1 measurements [ARM, 2021a; b] and circulating a summary of the measurements each week, (2) Comparing AMF1 measurements to those provided by collaborators (including filter measurements at the pier), (3) Collecting and analyzing filter samples from Scripps Pier by Fourier Transform Infrared spectroscopy (FTIR) and X-ray Fluorescence (XRF), (4) Assisting in operations of instruments provided by Guest PIs when possible, and (5) Providing an initial compilation of EPCAPE aerosol and cloud seasonal differences. The expected outcomes of these objectives were enhanced proposals and publications using EPCAPE measurements by helping to identify instrument issues, expanded data access and awareness by distributing weekly plots and related summaries, improved source-related attribution of aerosols with elemental tracers, additional observations provided by Guest PIs, and accelerated ACI studies enabled by the compiled seasonal summaries of aerosol and cloud properties. Three examples of the science enabled by this project are findings that (i) aerosol and cloud aqueous production contributes more than half of sulfate particle mass concentration, (ii) upwind sources make chemical composition very similar at nearby sites despite local differences in meteorology, and (iii) most of the large mass concentration of semi-volatile organic components is co-emitted and co-evaporated with nitrate. Together these findings illustrate how ARM extended field campaigns in coastal regions can be used to constrain ACI processes with direct observations. By using the unique ARM suite of cloud radiative products in addition to the measured aerosol properties at a coastal location, we were able to address the more specific question of which aerosol particles cause how much of the effects on clouds. Identifying this signature in coastal areas provides an opportunity to test the representation of aerosol sources by global models in a range of clean and urban-influenced conditions.

Russell, Lynn [Univ. of California, San Diego, CA ↗
DOE OSTI2025

High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. Consequently, the role of enhanced horizontal resolution in improved process representation in all components of the climate system continues to be of great interest. Recent simulations suggest the possibility of significant changes in both large-scale aspects of the ocean and atmospheric circulations and in the regional responses to climate change, as well as improvements in representations of small-scale processes and extremes, when resolution is enhanced. The first phase of the High-Resolution Model Intercomparison Project (HighResMIP1) was successful at producing a baseline multi-model assessment of global simulations with model grid spacings of 25–50 km in the atmosphere and 10–25 km in the ocean, a significant increase when compared to models with standard resolutions on the order of 1° that are typically used as part of the Coupled Model Intercomparison Project (CMIP) experiments. In addition to over 250 peer-reviewed manuscripts using the published HighResMIP1 datasets, the results were widely cited in the Intergovernmental Panel on Climate Change report and were the basis of a variety of derived datasets, including tracked cyclones (both tropical and extratropical), river discharge, storm surge, and impact studies. There were also suggestions from the few ocean eddy-rich coupled simulations that aspects of climate variability and change might be significantly influenced by improved process representation in such models. The compromises that HighResMIP1 made should now be revisited, given the recent major advances in modelling and computing resources. Aspects that will be reconsidered include experimental design and simulation length, complexity, and resolution. In addition, larger ensemble sizes and a wider range of future scenarios would enhance the applicability of HighResMIP. Therefore, we propose the High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) to improve and extend the previous work, to address new science questions, and to further advance our understanding of the role of horizontal resolution (and hence process representation) in state-of-the-art climate simulations. With further increases in high-performance computing resources and modelling advances, along with the ability to take full advantage of these computational resources, an enhanced investigation of the drivers and consequences of variability and change in both large- and synoptic-scale weather and climate is now possible. With the arrival of global cloud-resolving models (currently run for relatively short timescales), there is also an opportunity to improve links between such models and more traditional CMIP models, with HighResMIP providing a bridge to link understanding between these domains. HighResMIP also aims to link to other CMIP projects and international efforts such as the World Climate Research Program lighthouse activities and various digital twin initiatives. It also has the potential to be used as training and validation data for the fast-evolving machine learning climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Editorial: Functionalization of porous materials for sustainable energy applications

Global energy demands are shifting toward a more sustainable future, with the goal of achieving carbon neutrality by 2050. Emerging technologies are driving this transition. The industry, academia, government, non-profit organizations, and the broader community are collaboratively working to reduce greenhouse gas (GHG) emissions and address climate change to ensure a sustainable future. According to the International Energy Agency, in 2022, the production, transportation, and processing of oil and gas resulted in 5.1 billion tons of CO 2 -equivalent emissions, representing nearly 15% of all energy-related GHG emissions. Moreover, the end-use of oil and gas accounted for an additional 40% of emissions. The IEA’s Net Zero Emissions by 2050 Scenario calls for immediate, collective action from the industry, transportation and other stakeholders to mitigate these emissions. In this effort, the development of energy materials will play a critical role in reducing emissions. Among these, porous materials offer an innovative solution, leveraging their high surface area, adjustable pore sizes, and chemical versatility to address these pressing challenges effectively. By carefully designing their nanostructures, the architecture and properties of these materials can be tailored for specific applications. Key factors such as chemical composition, particle size, pore distribution, and surface area optimization enhance the reactivity and energy conversion efficiency. Additionally, pre- and post-functionalization processes can introduce targeted chemical properties, further improving their performance. This Research Topic explores recent advancements in energy and materials science through four scholarly papers, showcasing innovative solutions for sustainable energy technologies while providing valuable insights into the unique properties and structure of porous materials (Figure 1). Li et al. present their work on highly defective NiFeV layered triple hydroxides, highlighting enhanced electrocatalytic activity and stability for oxygen evolution reactions (OER). Kovalskii et al. contribute a mini-review on hydrogen storage using hexagonal boron nitride (h-BN) and BN-based materials, offering an insightful overview of these promising materials. Chava et al. discuss their recent achievements in ceramic electrolytes used for improvement of performance of solid-state batteries. Lastly, Li et al. review the properties of porous materials with a focus on shrinkage behavior during the drying process, shedding light on key considerations for material design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Improved lipid analysis using a 2D-LC-MS system with a novel injection procedure

The aim of this study was to improve analysis of nonpolar lipidomics sample extracts using reversed phase (RP) chromatography. A 4/3/3 (v/v/v) mixture of methanol/methyl tert-butyl ether/chloroform (MeOH/MTBE/CHCl 3 , MMC) was chosen for sample extraction solvent based on its proven extraction capability for several lipid classes. To avoid carry over, loss of analytes and peak distortion the loops and all capillaries of the presented LC system were flushed and filled up with methanol until the analytical column. Here, the choice of methanol was due to its weak elution strength and being infinitely miscible with MMC and several other nonpolar solvents. This allowed injection of a 100 μl sample that was 20 μl nonpolar extraction solvent diluted fivefold with methanol. All lipids of 25 lipid classes were transferred quantitatively to the column head where the online dilution of methanol was carried out with aqueous eluent for focusing the lipid analytes. The weak elution strength of methanol prevented peak distortions. The consecutive reversed phase elution resulted in remarkably narrow peaks (full width at half maximum was 0.07–0.08 min typically) and enhanced sensitivity (limit of detection usually in sub nM region) because of increased sample injection volume and narrow peaks. Calibration and quality control samples made by diluting commercial lipid standards 200–50000 times confirmed the applicability of this approach both for targeted lipid quantification and for untargeted quantitative comparison of lipids from different sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Ink Casting and 3D‐Extrusion Printing of Yb 14 MnSb 11 for High‐Temperature Thermoelectric Material

Abstract Complex shapes are created from Yb 14 MnSb 11 , a high‐temperature thermoelectric Zintl phase, via a two‐step process: i) layer‐by‐layer 3D‐extrusion of ink containing partially‐reacted powders which are ball‐milled from a blend of Yb, MnSb, and Sb powders; ii) heat treatment to synthesize the ternary compound Yb 14 MnSb 11 and densify the extruded powders. A high phase purity for Yb 14 MnSb 11 (83–94%) is achieved in both cast and 3D‐extruded ink specimens via a solid‐state reaction between Yb, MnSb, and Yb 4 Sb 3 during reactive sintering. Pressure‐free sintering at temperatures of 1200–1400 °C densifies the powders to 82% relative density but can also induce the decomposition of the Yb 14 MnSb 11 phase due to Yb sublimation. A process window with optimized sintering temperature and time is identified, achieving both low porosity and high phase purity and reaching a maximum zT = 0.61 at 1000 °C, about half of the maximum zT value for bulk Yb 14 MnSb 11 made via conventional processes (pressure sintering of precursor powders). The present approach – direct ink writing of ball‐milled powders, combined with reactive sintering – is a scalable and affordable method to fabricate thermoelectric legs with intricate 3D shapes, for enhanced performances in high‐temperature thermoelectric applications.

Chen, Ming [Department of Materials Science &amp, ↗