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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 361 records · Page 20

Systematic discovery of new nano-scale metastable intermetallic eutectic phases in laser rapid solidified Aluminum-Germanium alloy

Laser surface remelting of as-cast Al-Ge eutectic alloy is shown to produce ultrafine lamellar eutectic morphology with interlamellar spacing refined up to ∼60 nm and composed of FCC Al solid solution and unusual Al x Ge y intermetallic phases that do not form during near-equilibrium solidification. The microstructures are characterized and analyzed using a combination of selected area electron diffraction, high-resolution scanning transmission electron microscopy, energy dispersive X-ray spectroscopy to obtain high-resolution elemental maps, and atomistic modeling using density functional theory followed by atomic-scale image simulation. Depending on the local solidification conditions, the crystallography of the Al x Ge y intermetallic phases in the eutectic microstructure is either monoclinic (C 2/c) or monoclinic (P 2 1 ), with high densities of defects in both cases. This is in sharp contrast to the as-cast alloys that showed nominally pure Al and Ge phases with significant solute partitioning and equilibrium FCC and diamond cubic crystal structures, respectively. Corresponding kinetic phase diagrams are proposed to interpret the evolution of nano-lamellar eutectic morphologies with equilibrium Al and metastable Al x Ge y phases, and to explain increased solid solubility in the Al phases manifested by precipitation of ultrafine clusters of Ge. Furthermore, the reasons for the formation of these metastable eutectics under laser rapid solidification are discussed from the perspective of the competitive growth criterion.

Al-Ge eutectic↗

Fundamental Insights into Cathode Stability: Linking Compositional Tuning and Local Coordination in Complex Metal Oxides under Aqueous Transformations

Compositional tuning of complex metal oxides in Li-ion battery materials influences their performance as well as their end-of-life behavior, in particular, the tendency to release toxic metal cations in aqueous solution. We modeled ternary variants of a parent LiCoO 2 delafossite structure by varying the metal identity and relative amounts. This yielded ten model formulations of Li(A 4/6 B 1/6 C 1/6 )O 2 , where the material is enriched with the A metal and doped with B and C, with Ni, Mn, Co, Fe, Al, V, and Ti as constituent metals. To assess their stability in aqueous conditions, metal release energetics were calculated using a combination of Density Functional Theory calculations and thermodynamics. Metal release in ternary oxides is dictated by subtle variations in the coordination environment of the leaving group. To identify governing chemical features across diverse compositions with varying local coordination environments, we leverage random forest regression and descriptor importance analysis. A key result is that metal–oxygen orbital hybridization, quantified using a projected density-of-states-derived descriptor, H d/p , provides a physically grounded measure of interaction strength that governs metal release energetics. This refined perspective goes beyond conventional oxidation state considerations and offers more robust insights for materials science. Finally, we model defect surface-bound O 2 dimer formation as a proxy for reactive oxygen species (ROS) generation. The results show that Ni-rich compositions more readily stabilize spin-polarized O 2 dimers, corroborating experimental reports of an increased ROS-driven biological response. In conclusion, our results establish a compositional and electronic basis for metal release and surface oxygen reactivity that form a rationale for complex metal oxide design principles.

36 MATERIALS SCIENCE↗

Harvesting Subsea Water Motion to Provide Clean Electrical Power

This TEAMER project had three main objectives related to characterizing the performance of a vortex-induced vibration (VIV) marine energy harvesting device called the Whatever Input To Torsion (WITT). The first was to characterize the motion of the WITT device as it vibrates on top of a pipe in a natural tidal flow. The second was to measure how much electricity the WITT device generates when it is deployed on top of a pipe that is secured to the seabed with a lander. The third objective was to measure how much electricity the WITT device generates in the same configuration but with a longer pipe. This TEAMER project succeeded in satisfying the first objective by measuring the motion of the WITT device with an inertial measurement unit (IMU) mounted in the WITT housing. The motion was described by examining changes in the acceleration, pitch, roll, and yaw, and displacement. The frequency of the motion was characterized using spectral analysis. The TEAMER project succeeded in reaching the second objective by measuring the power produced by the WITT. It is reported here as the average and maximum power in hourly intervals. WITT Energy decided to not have us pursue the third objective of testing a longer pipe because the first test was unexpectedly successful at having the system vibrate at the target frequency. A longer pipe would have resulted in a decreased frequency and therefore not have been a useful test. Based on these findings, the decision was made to keep the same pipe length for both tests and improve on other aspects of the test structure that had failed during the first test. The key finding of this TEAMER project is that the WITT is capable of generating electricity in moderate flow speeds when it is in a housing that is attached to a 2.5 m pipe and secured to the seabed by a lander. This report contains the first power values for a VIV instrument that generates electricity from a pendulum swinging at the top of a long pipe. The experiment demonstrated that the vibration frequency of the device varied with the tidal current speed, which changed throughout a given tidal cycle. This meant that the desired peak frequency was not sustained for more than one hour. The success of this TEAMER test provides evidence that continued research in the area of electricity generation from VIV holds promise as a source of marine energy for offshore applications. Future tests should focus on refining the pipe length equations and improving the power take off system of the WITT power electronics. In addition, experiments aimed at expanded testing and evaluation (e.g. longer than one month) are needed to measure the power production at higher tidal current speeds and test the system's durability.

Branch, Ruth A. (ORCID:0000000202356719)↗

Elucidating microstructural evolution and hardness variation across friction self-piercing riveted Al-7055 using synchrotron X-ray scattering and advanced microscopy techniques

Friction self-piercing riveting (FSPR) is a unique hybrid joining technique that combines the advantages of mechanical interlocking, frictional heat, and solid-state joining (if metallurgically compatible) to produce crack free joints in high strength and/or low-ductility alloys at room temperature. Here, in the current study, Al-7055 sheets were joined using FSPR for lightweight automotive applications and significant microhardness variations were observed across the joint cross-section. A detailed microstructural characterization at multiple length scales was carried out using advanced electron microscopy and X-ray scattering techniques to provide a fundamental understanding of the process-structure-property relationships. The relative contributions of microstructural characteristics at various length scales (i.e., grain size, dislocation density, solute concentration, precipitate nature) to strengthening were estimated using existent formulations (i.e., Hall-Petch, Taylor, precipitate bypass/shear equations) and correlated to the observed microhardness values across different regions. Small-angle X-ray scattering and scanning transmission electron microscopy revealed significant changes in the size and volume fraction of precipitate species, i.e., GP-I Zones, η′, and Mg/Zn solute co-clusters, depending on the process region. It was observed that the dissolution of the small η′/GP-I zones (T ∼ 150–200 °C) in the heat-affected zone were the key reason for the hardness drop. Further, it was shown that solid-solution, dislocation, grain size and solute co-cluster strengthening played a key role in the thermo-mechanically affected zone and grain-refined zone (GRZ). Finally, these observations were leveraged along with the Zener-Holloman relationship and grain size in the GRZ to estimate the peak joining temperature of the GRZ (∼ 350 °C) near the steel rivet.

aluminum 7xxx alloy↗

Robust Implicit Adaptive Low Rank Time-Stepping Methods for Matrix Differential Equations

In this work, we develop implicit rank-adaptive schemes for time-dependent matrix differential equations. The dynamic low rank approximation (DLRA) is a well-known technique to capture the dynamic low rank structure based on Dirac–Frenkel time-dependent variational principle. In recent years, it has attracted a lot of attention due to its wide applicability. Our schemes are inspired by the three-step procedure used in the rank adaptive version of the unconventional robust integrator (the so called BUG integrator) (Ceruti et al. in BIT Numer Math 62(4):1149–1174, 2022) for DLRA. First, a prediction (basis update) step is made computing the approximate column and row spaces at the next time level. Second, a Galerkin evolution step is invoked using an implicit solves for the small core matrix. Finally, a truncation is made according to a prescribed error threshold. Since the DLRA is evolving the differential equation projected on to the tangent space of the low rank manifold, the error estimate of the BUG integrator contains the tangent projection (modeling) error which cannot be easily controlled by mesh refinement. This can cause convergence issue for equations with cross terms. To address this issue, we propose a simple modification, consisting of merging the row and column spaces from the explicit step truncation method together with the BUG spaces in the prediction step. In addition, we propose an adaptive strategy where the BUG spaces are only computed if the residual for the solution obtained from the prediction space by explicit step truncation method, is too large. Here, we prove stability and estimate the local truncation error of the schemes under assumptions. We benchmark the schemes in several tests, such as anisotropic diffusion, solid body rotation and the combination of the two, to show robust convergence properties.

97 MATHEMATICS AND COMPUTING↗

Unpacking model inadequacy: The quantification of silver release from TRISO fuel by considering empirical and mechanistic approaches

Increasing adoption of the proposed tristructural isotropic (TRISO) particle fuel for both advanced and existing reactors makes it critical to assess and address any uncertainties and inadequacies of TRISO fission product release models. Model inadequacy stems from simplifications made to the computational model when compared to the experiments. The modeling and simulation efforts conducted using the BISON fuel performance code, along with the experimental campaigns carried out under the Advanced Gas Reactor Fuel Development and Qualification Program, afford a unique opportunity to conduct a rigorous modeling inadequacy assessment within the Bayesian uncertainty quantification (UQ) framework. Here, this study compares the standard Bayesian framework against the Kennedy-O'Hagan (KOH) framework, which explicitly represents modeling inadequacy, in regard to UQ for TRISO silver release models. For this purpose, both the traditional Arrhenius equation fitted to experimental data and the more advanced lower-length-scale (LLS)-informed model, which considers microstructure information, are independently considered. Applying the inverse UQ process on the AGR-2 and -3/4 datasets revealed modeling inadequacy to be the most dominant source of uncertainty. Experimental noise uncertainty is also significant; however, model parameter uncertainty can be considered negligible. Interestingly, both the Arrhenius equation and the LLS-informed model demonstrated similar levels of modeling inadequacy. For the forward predictive UQ, the KOH framework improved both the accuracy and quality of quantified uncertainties in comparison to the standard Bayesian framework. This is true for both the Arrhenius equation and the LLS-informed model. In comparing these modeling approaches, both demonstrated similar performance at the engineering scale, while the LLS-informed model expectedly outperformed the Arrhenius equation at the mesoscale. These conclusions highlight the importance of explicitly accounting for modeling inadequacy in the UQ process, and reinforce the need for continuous refinement of physics-based models in order to address the modeling inadequacy.

Advanced reactors↗

Absolute efficiency response of the γ-ray spectrometer GRETINA for high-energy γ rays up to 6 MeV

GRETINA (Gamma-Ray Energy Tracking In-beam Nuclear Array), a state-of-the-art γ-ray tracking spectrometer, has been instrumental in advancing nuclear structure studies, particularly in experiments using fast beams of rare isotopes where the γ rays emitted in flight are subject to large Doppler shifts. This work presents an experimental determination of the γ-ray detection efficiency of GRETINA at energies up to 6 MeV. The high-energy γ rays originated from states that were populated in nucleon-removal reactions from a projectile beam at an intermediate beam energy of about 85 MeV/nucleon. Utilizing γ-γ coincidences, efficiency values were extracted in-beam and translated into a source efficiency at rest employing GEANT4 Monte Carlo simulations. A systematic discrepancy in the efficiency of the forward-positioned detectors was identified which is attributed to specific dead-time effects caused by high-energy light-particle events prevalent at forward angles, generating signals in the Ge crystals that saturate the preamplifier’s first stage. Furthermore, this study provides refined efficiency benchmarks for in-beam experiments, improving the accuracy of quantitative γ-ray spectroscopy analyses with GRETINA and GRETA (Gamma Ray Energy Tracking Array) in the future.

GRETINA↗

Convective Biases in the US DOE Global Storm‐Resolving Model: Insights From Regionally Refined Simulations During the CACTI Campaign

Accurately simulating convective processes in complex terrain remains a critical challenge for global storm-resolving models (GSRMs). This study systematically evaluates moist convective biases in the Regionally Refined Mesh configuration of the U.S. Department of Energy Simple Cloud-Resolving E3SM Atmosphere Model (RRM-SCREAM) using comprehensive observations and large-eddy simulations from the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign in the mountainous area of central Argentina. Comparisons of simulations with high-resolution observations and reanalysis data indicate that RRM-SCREAM effectively captures large-scale meteorological patterns, including regional atmospheric gradients and diurnal variability. However, RRM-SCREAM disproportionately produces smaller precipitation clusters referred to as “popcorn convection,” and exaggerated rainfall intensities compared to observations and reference models. Detailed examination of a representative orographic shallow-to-deep convective transition case shows that RRM-SCREAM delays initial shallow convection growth due to lower-tropospheric dryness and sustained convective inhibition, but once triggered, deep convection becomes overly vigorous with excessively strong vertical velocities and elevated cloud ice content, linked to a thermodynamic structure characterized by suppressed low-level moistening and excessive upper-level moisture retention. Our results highlight specific deficiencies in the model representation of convective vertical velocity, cloud microphysical processes, and convective precipitation organization within RRM-SCREAM. Addressing these biases is essential for improving the predictions of convective clouds and precipitation in the global high-resolution atmospheric models.

Su, Tianning [Lawrence Livermore National Laborato↗

Aberration corrected RF flipper for high resolution neutron spectroscopy

Project Summary Company: Adelphi Technology, Inc. Title: Aberration-corrected High Frequency RF Flipper for High-Resolution Neutron Spectroscopy PI: Dr. Jay Theodore Cremer Topic: C55-11 Enhancement of Scattering Instrumentation Technology Used at Pulsed and Continuous Sources Subtopic: d. Other Statement of the problem or situation that is being addressed. The quest to understand heterogeneous and hierarchical materials is gathering momentum, as described in a 2015 report by the Basic Energy Sciences Advisory Committee on Challenges at the Frontiers of Matter and Energy. For the past 40 years a technique called neutron spin echo (NSE) has been used to probe molecular motions in such non-crystalline materials over time scales from 10’s of picoseconds to 100’s of nanoseconds. The method has provided unique information about the dynamics of soft heterogeneous materials, including confirmation of the de Gennes model of polymer reptation and quantitative measurement of bending constants of biologically relevant lipid membranes. However, scientists continue to clamor for even higher resolution than NSE can provide. Biomaterials, polymers, glasses, and artificially nanostructured materials all manifest slow molecular motions because of weak or competing interactions between subunits and are amenable to study with neutrons, provided sufficiently long dynamical correlation times can be achieved. All these materials have important applications to advanced technologies so understanding them is key to technological progress. General statement of how this problem is being addressed. We will address the need for high-resolution neutron spectroscopy by using a technique called Neutron Resonance Spin Echo (NRSE). While similar to NSE in many respects, this method has the potential to exceed the NSE capabilities, if 2 technical hurdles can be overcome. The major impediments to successful high-resolution NRSE are the availability of two technologies: a very high frequency, efficient, radiofrequency (rf) flipper for neutrons and a method to correct certain magnetic aberrations. Based on previous STTR support and follow-on research we have developed a suitable rf flipper and we have invented a method to correct the magnetic aberrations. Both technologies need refinement to make them suitable for implementation at a neutron source such as the Oak Ridge National Laboratory nuclear reactor. In this proposal we seek to perfect the two technologies and to combine them into a single, operationally convenient device. Commercial Applications and Other Benefits In view of the increasing demand for the unique scientific information that high resolution neutron spectroscopy can provide, we expect several major instrumentation upgrades at both U.S. and foreign neutron centers will require make use of the NRSE method over the coming decade, creating a market for the devices we will design. These components will enhance scientists’ abilities to probe the time dependence of density fluctuations in a wide range of hierarchical and heterogeneous materials many of which are vital to existing and future technologies. Key Words – Polarized Neutrons, Neutron Spin Echo, Neutron Scattering, advanced materials. Summary for Members of Congress Neutron beams are a powerful materials-science probe that provide unique information about the structure of matter. The proposed devices will accelerate scientific discoveries required to achieve national goals for new technological materials.

36 MATERIALS SCIENCE↗

Ultrafast Oxygen Conduction in Sillén Oxychlorides

Oxygen ion conductors are crucial for enhancing the efficiency of various clean energy technologies, including fuel cells, solid oxide air batteries, electrolyzers, membranes, sensors, and more. In this study, a structure-similarity analysis of ≈62k oxygen-containing compounds identified the MBi 2 O 4 X (M = rare-earth element, X = halogen element) family as promising candidates for fast oxygen transport. Among these, LaBi 2 O 4 Cl is found as an ultrafast oxygen conductor with an ultralow migration barrier of 0.1 eV based on ab initio studies. Its 2D layered structure, featuring a “triple fluorite” layer, supports diffusion of both oxygen vacancies and interstitials. In addition to vacancy diffusion with a 0.1 eV barrier, ab initio studies show interstitial diffusion exhibits a modest barrier of 0.6–0.8 eV. Frenkel pairs are found to be the dominant defects in intrinsic LaBi 2 O 4 Cl, facilitating significant vacancy-mediated oxygen diffusion at elevated temperatures. With 2.8% oxygen vacancies, LaBi 2 O 4 Cl is predicted to achieve a conductivity of 0.3 S/cm at 25 °C in a single crystal. Experimental synthesis and characterization of polycrystalline LaBi 2 O 4 Cl and Sr-doped LaBi 2 O 4 Cl revealed conductivity exceeding that of YSZ and LSGM below 400 °C, with lower activation energies, achieving a total conductivity of 0.1−0.2 mS/cm at 300 °C. Here, while these results confirm its potential of fast oxygen transport, we suggest further experimental optimization of LaBi 2 O 4 Cl, including aliovalent doping and microstructure refinement, could significantly enhance its performance, facilitating fast oxygen conduction approaching room temperature.

Defects↗

Survey of Thirteen Novel Pseudomonas putida Bacteriophages

Bacteriophages have been widely investigated as a promising treatment of food, medical equipment, and humans colonized by antibiotic-resistant bacteria. Phages pose particular interest in combating those bacteria which form biofilms, such as the medically important human pathogen Pseudomonas aeruginosa and several plant pathogens, including P. syringae . In an undergraduate lab course, P. putida was used as the host to isolate novel anti-pseudomonal bacteriophages. Environmental samples of soil and water were collected, and purified phage isolates were obtained. After Illumina sequencing, genomes of these phages were assembled de novo and annotated. Assembled genomes were compared with known genomes in the literature and GenBank to identify taxonomic relations and to refine their functional annotations. The thirteen phages described are sipho-, myo-, and podoviruses in several families of Caudoviricetes , spanning several novel genera, with genomes ranging from 40,000 to 96,000 bp. One phage (DDSR119) is unique and is the first reported P. putida siphovirus. The remaining 12 can be clustered into four distinct groups. Six are highly related to each other and to previously described Autotranscriptaviridae phages: Waldo5, PlaquesPlease, and Laces98 all belong to the Waldovirus genus, whereas Stalingrad, Bosely, and Stamos belong to the Troedvirus genus. Zuri was previously classified as the founding member of a new genus Zurivirus within the family Schitoviridae . Ebordelon and Holyagarpour each represent different species within Zurivirus , whereas Meara is a more distantly related member of the Schitoviridae . Dolphis and Jeremy are similar enough to form a genus but have only a few distant relatives among sequenced phages and are notable for being temperate. We identified the lysis cassettes in all 13 phages, compared tail spike structures, and found auxiliary metabolic genes in several. Studies like these, which isolate and characterize infectious virions, enable the identification of novel proteins and molecular systems and also provide the raw materials for further study, evaluation, and manipulation of phage proteins and their hosts.

Pseudomonas putida↗

Sockeye Code Validation Against UNIST Heat Pipe - Poster - Internship 2025

Sockeye is an engineering level code being developed under the MOOSE framework for modeling heat pipes. A heat pipe is a sealed tube with a wick structure filled with a working fluid that transfers heat efficiently and passively via phase change of the working fluid. Heat applied to the evaporator end creates a pressure gradient which causes vapor to migrate to the condenser end where the vapor deposits its energy and condenses. Capillary force generated by the wick structure then draws the liquid back to the evaporator. A validation study was performed to compare the Sockeye code against data produced at the Ulsan National Institute of Standards and Technology for a slightly overfilled sodium heat pipe. The heat pipe was operated under natural convection cooling and a decreasing inactive length was observed. The experiment was modeled in Sockeye using the condenser pool model, the front non-condensable gas (NCG) model, and the mixture NCG model separately to reproduce the inactive length phenomenon. Also, a new capability was implemented in MOOSE to allow for conjugate heat transfer from the condenser based on the Churchill-Chu correlation for natural convection. The condenser pool model showed an increasing inactive length, demonstrating that the behavior was likely not caused by a pool of excess liquid. The front NCG model was able to show good agreement with the experiment, but it suffered convergence issues at the front. Finally, the mixture NCG model gave good results when the axial mesh was sufficiently refined. This work culminated in additions to the Sockeye documentation and a contribution to a journal article that will be published later. This poster is a summary of my work which I can take back to my university for presentation.

42 - ENGINEERING↗

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science↗

Feedstock/Pretreatment Screening for Bioconversion of Sugars and Lignin Residues

This project will conduct biomass deconstruction (pretreatment and enzymatic saccharification) on two representative biomass feedstocks and four different pretreatment processes, including three high temperature steam/chemical pretreatments and one low temperature chemical/mechanical pretreatment. A third biomass feedstock will undergo biomass deconstruction with three different pretreatment processes, including two high temperature chemical pretreatments and one low temperature chemical/mechanical pretreatment. Several pretreatment conditions will be performed in a screening study using NLR pilot-scale pretreatment equipment to generate a range of pretreated biomass substrates. A selected number of these substrates will be chosen for enzymatic saccharification evaluation, based on standard compositional analysis of the pretreated substrates as a primary indicator of pretreatment efficacy. Resulting enzymatic hydrolysis slurries will be analyzed to determine overall biomass sugar yields. Additional compositional analysis will be performed to determine oligomeric sugar composition and structure, to analyze structural characteristics of solids fractions on native, pretreated, and enzymatically saccharified biomass residues for one of the biomass feedstocks, corn stover. The enzymatically saccharified materials will undergo 2,3-butanediol fermentation in a shaker flask as bench scale. Using relevant process performance data collected in these various conversion steps, technoeconomic analysis activities will be performed to compare the economic potential of the various biomass feedstock and pretreatment processes and to identify key economic drivers and sustainability metrics.

09 BIOMASS FUELS↗

The scientific case for concurrent neutron and X-ray scattering and spectroscopy

The interrogation of materials with X-rays or neutrons to determine structure, energetics, and dynamics is fundamental to advancing physical and chemical materials science and enabling innovative material technologies. A persistent challenge in materials development is that progress depends on understanding structure and dynamics across multiple length and time scales in increasingly complex, multicomponent systems featuring interfaces, heterogeneity, and hierarchical organization. Despite rapidly growing demands on materials characterization, current experimental approaches are almost exclusively based on isolated X-ray or neutron scattering and spectroscopy, reflecting a paradigm largely unchanged for decades. To assess the scientific need for a new experimental paradigm, a 3-day workshop sponsored by the U.S. National Science Foundation (NSF) was held at the SpringHill Suites, San Jose, California, from June 2 to 4, 2022. The workshop brought together 70 national and international experts who critically evaluated opportunities enabled by concurrent neutron and X-ray (NeX) scattering, spectroscopy, and imaging experiments. The participants reached a clear consensus that establishing NeX capabilities is crucial for advancing the science of complex materials in the United States. This report illustrates the scientific drivers for NeX experiments through representative examples spanning biomaterials, energy materials, soft matter, nanomaterials, quantum materials, geoscience, and applied materials research. The complementarity of neutrons and X-rays is essential for robust model development and refinement, particularly in multiphase and multicomponent systems. While joint refinement of data from separate experiments is valuable, concurrent measurements uniquely eliminate uncertainties arising from sample evolution, environmental drift, and irreproducibility associated with experiments performed at different locations and times. Realizing NeX capabilities will require the development of new instrumentation, data analysis frameworks, and robust sample environments compatible with both neutron and X-ray probes. Addressing these challenges will enable unambiguous interpretation of complex materials behavior and open new frontiers in materials research.

X-ray↗

Maximizing long-term biohydrogen production with Clostridium thermocellum for high solids conversion of lignocellulosic biomass

Biological hydrogen production from lignocellulosic biomass sustainably couples organic waste reduction with renewable energy generation. Efficient conversion is challenged by the structural complexity of lignocellulose and resulting recalcitrance to enzymatic degradation. Clostridium thermocellum natively breaks down biomass with highly effective hemi-/cellulases systems (i.e., cellulosomes) and generates hydrogen in anaerobic cultivation, creating a compelling platform for lignocellulosic biohydrogen production. Achieving commercially viable production rates requires balancing high biomass loading and throughput against uniform mixing conditions required for enzyme dispersion, pH and temperature control, and efficient hydrogen and metabolite removal in continuous operation. To address these barriers to process intensification, we implemented novel reactor and process designs for high-solids lignocellulosic biomass fermentations using the C. thermocellum KJC19-9 strain, genetically engineered for co-utilization of cellulose and hemicellulose sugars (i.e., xylose). Via computational fluid dynamics (CFD) modeling and experimental validation, we achieved a >50% improvement in biohydrogen production with an improved anchor-type impeller morphology, coupled to a threefold reduction in agitation rate. To further reduce rheological constraints and accumulation of toxic metabolites, we then transitioned the process to sequencing fed-batch operation. The resulting process generated 24.87 L H 2 L −1 from 160 g L −1 of deacetylated and mechanically refined (DMR)-pretreated corn stover biomass over 16 days while solubilizing >95% of influent cellulose and hemicellulose, setting a new performance benchmark for continuous production of biohydrogen from lignocellulose.

08 HYDROGEN↗

Evolution of intermittent filaments in the scrape-off layer of NSTX

Filamentary structures naturally arise from background turbulence in the scrape-off layer (SOL) of plasmas, leading to significant particle and heat transport that can degrade overall plasma confinement. This enhanced transport can contribute to unacceptably high heat loads on plasma-facing components. As such, understanding the physics of SOL plasma filaments is critical for predicting and mitigating their effects in future fusion devices. On the National Spherical Torus Experiment (NSTX), plasma filaments—commonly referred to as “blobs”—were investigated using the gas-puff imaging (GPI) diagnostic in the edge and SOL regions. The analysis involved identifying, segmenting, and tracking the characteristic contours of the blobs in each frame of the GPI video sequences. Their evolution was characterized through shape descriptors, velocity, and angular velocity derived from their contour coordinates. The results indicate that as the blob area increases, their shapes become more concave and less circular, suggesting reduced structural stability in larger blobs. This result aligns with previous theoretical results where it was shown that larger blobs are more susceptible to instabilities [Krasheninnikov et al., J. Plasma Phys. 74, 679–717 (2008) and D'Ippolito et al., Phys. Plasmas 18, 060501 (2011)]. A positive correlation was observed between radial velocity and radial position, suggesting radially outward acceleration of the filaments, potentially driven by decreasing viscous drag toward the far SOL. Interestingly, blobs in background SOL turbulence exhibited minimal spinning in contrast to filaments originating from edge localized modes, which show substantial rotation during their paths [Lampert et al., Phys. Plasmas 29, 102502 (2022)]. Statistical analysis of the solidity and total curvature shape descriptors, along with their temporal evolution, revealed relatively broad, near-Gaussian distributions. This suggests that blob morphology is strongly influenced by stochastic turbulent processes in the surrounding plasma environment. Blob parameters were also compared with bulk plasma and radial profile measurements. Notable trends were found between blob rotation and poloidal velocity with collisionality and line-integrated density. These findings contribute to a deeper understanding of blob dynamics and provide valuable insights for refining SOL turbulence models.

Covariance and correlation↗

Exploring Quantum Materials with Resonant Inelastic X-Ray Scattering

Understanding quantum materials—solids in which interactions among constituent electrons yield a great variety of novel emergent quantum phenomena—is a forefront challenge in modern condensed matter physics. This goal has driven the invention and refinement of several experimental methods, which can spectroscopically determine the elementary excitations and correlation functions that determine material properties. Here we focus on the future experimental and theoretical trends of resonant inelastic x-ray scattering (RIXS), which is a remarkably versatile and rapidly growing technique for probing different charge, lattice, spin, and orbital excitations in quantum materials. We provide a forward-looking introduction to RIXS and outline how this technique is poised to deepen our insight into the nature of quantum materials and of their emergent electronic phenomena. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗