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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 127 records · Page 7

Effect of feed-rod tilting on friction surfacing of steel

During the friction surfacing process, the forge-axial force, rotation rate, and traverse speed of the consumable feed-rod play crucial roles in determining the deposition rate and layer morphology. Although some researchers have studied the enhancement of deposition by introducing a backward tilt relative to the traverse direction, there has been limited investigation into the effects of other tilt orientations. Therefore, this study aims to provide a more comprehensive understanding of feed-rod tilting in friction surfacing. In this investigation, the consumable feed-rod undergoes tilting in four distinct directions: forward, backward, advancing side, and retreating side, each tested at two different tilt angles (1.5° and 3.0°). The results reveal that the feed-rod tilting can influence the deposition dynamics by altering the location and area of the rubbing interface situated between the feed-rod and the substrate. Moreover, the feed-rod tilting can significantly enhance the bond width, deposition rate, and deposition efficiency. The enhancement in deposition efficiency signifies a successful reduction in flash formation. Furthermore, a distinct layered microstructure is evident within each deposition layer, regardless of tilt conditions, indicating the unique deposition process inherent to friction surfacing. Finally, the innovative approach proposed in this study not only offers a straightforward and feasible means to improve deposition rate and efficiency but also expands the potential for constructing more intricate geometries or authentic surfaces.

36 MATERIALS SCIENCE↗

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗

Integration of the Biot–Gassmann Fluid Substitution Method and Machine Learning-Based Velocity–Stress Relationship for Estimating In Situ Stresses

Recent advancements have shown that in situ stresses can be reliably estimated through an integrated machine/deep learning (ML/DL)-based framework, which relies on models trained and validated using true triaxial ultrasonic velocity (TUV) experimental data that involve measurements of ultrasonic velocity in saturated rocks under varying stress configurations. However, when the goal is to interpret lower frequency measurements, it may be more appropriate to run experiments on dry rocks and then obtain Biot–Gassmann-derived equivalent saturated velocities (low-frequency approximation) and employ these quantities for training ML/DL models to predict in situ stress. Whether the dispersion effect of frequency on the velocity–stress relationship substantially impacts in situ stress prediction is an important and unresolved question. This work presents an enhancement of ML/DL-based workflow by training and implementing ML/DL models using equivalent saturated acoustic velocities (low-frequency) obtained by applying Biot–Gassmann fluid substitution on the ultrasonic velocities of dry cores. The models were trained on TUV data sets derived from three subsurface cores extracted from the geothermal well 16B(78)-32 at the Utah FORGE site. Each core was subjected to 75 unique stress configurations for velocity measurement in the dry state. The ML/DL trained on the TUV data set with equivalent saturated velocities demonstrated promising performance to predict in situ stress in subsurface geological rocks using velocity–stress relationships with R 2 of 0.86, 0.971, and 0.975 and root mean squared error (RMSE) of 2.59, 1.92, and 1.80 for validation/testing phases of vertical, minimum horizontal, and maximum horizontal stress models, respectively. Additionally, interpretation and explanation by Shapley additive explanations (SHAP) analysis further improved scientific validation and model reliability for estimating in situ stresses.

colloids↗

Stability Frontiers in the AM 6 X 6 Kagome Metals: The Ln Nb 6 Sn 6 ( Ln :Ce–Lu,Y) Family and Density-Wave Transition in LuNb 6 Sn 6

The kagome motif is a versatile platform for condensed matter physics, hosting rich interactions between magnetic, electronic, and structural degrees of freedom. In recent years, the discovery of a charge density wave (CDW) in the AV 3 Sb 5 superconductors and structurally-derived bond density waves (BDW) in FeGe and ScV 6 Sn 6 have stoked the search for new kagome platforms broadly exhibiting density wave (DW) transitions. Here, in this work, we evaluate the known AM 6 X 6 chemistries and construct a stability diagram that summarizes the structural relationships among the >125 member family. Subsequently, we introduce our discovery of the broader LnNb 6 Sn 6 (Ln:Ce–Nd,Sm,Gd–Tm,Lu,Y) family of kagome metals and an analogous DW transition in LuNb 6 Sn 6 . Our X-ray scattering measurements clearly indicate a (1/3, 1/3, 1/3) ordering wave vector (√$\bar{3}$ x √$\bar{3}$ x $3$ superlattice) and diffuse scattering on half-integer L-planes. Our analysis of the structural data supports the “rattling mode” DW model proposed for ScV 6 Sn 6 and paints a detailed picture of the steric interactions between the rare-earth filler element and the host Nb–Sn kagome scaffolding. We also provide a broad survey of the magnetic properties within the HfFe 6 Ge 6 -type LnNb 6 Sn 6 members, revealing a number of complex antiferromagnetic and metamagnetic transitions throughout the family. This work integrates our new LnNb 6 Sn 6 series of compounds into the broader AM 6 X 6 family, providing new material platforms and forging a new route forward at the frontier of kagome metal research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Light-Promoted C(sp 3 )–C(sp 3 ) Reductive Elimination from Dialkyl NiII Complexes

Ni-catalyzed cross-coupling is a powerful strategy to forge C(sp 3 )–C(sp 3 ) bonds. Typically, to do so requires overcoming a challenging C–C bond-forming reductive elimination, often enabled by the intermediacy of highly oxidized Ni species or outer-sphere processes. While direct C(sp 3 )–C(sp 3 ) reductive elimination from the Ni II base oxidation state is normally thermally inaccessible, light-activation provides an avenue to affect such transformations. Here, we investigate the mechanism of light-induced C(sp 3 )–C(sp 3 ) bond formation from dialkyl bipyridine Ni II complexes through a variety of organometallic, spectroscopic, and computational studies. Wavelength-dependent quantum yields, ligand electronics–reactivity relationships, excited-state lifetimes, computed barriers, and product distributions from crossover studies support a photolysis/radical rebound mechanism. Furthermore, this reactivity paradigm complements existing strategies in the literature to promote reductive elimination from Ni II , such as the use of destabilizing, sterically hindered ligands and reduction of electron density at Ni through the binding of electron-deficient olefins. Hence, we envision that light-induced reductive elimination may enable the development of challenging C(sp 3 )–C(sp 3 ) couplings.

Alkyls↗

Fault Slip and Fluid Flow: Seismic Source Analysis to Assess Role of Multiple Slip Patches in Fault Permeability

The relationship between fault reactivation, microearthquakes (MEQs), and permeability evolution during fluid injection plays a critical role in energy harvesting and waste disposal. Recent studies have demonstrated the possibility of predicting fault permeability using cumulative seismic moments of MEQs quantitatively. To understand the underlying physical processes, we conduct fault reactivation experiments using Utah FORGE granitoid and analyze acoustic emission (AE) signals generated during stepwise increases in fluid injection pressure. Frequency analysis of thousands of calibrated AE signals reveals that fault reactivation produces multiple AE source patches with millimeter-scale radii—smaller than the sample fault radius. The cumulative area of the reactivated patches covers the fault multiple times over (∼10x–50x area) for each pressure step. These findings provide mechanistic insight that measured permeability enhancement is not driven by a single large slip event, but by the sequential and interacting activation of multiple slip patches that create a continuous flow pathway.

Nurshal, M. E. M. [Pennsylvania State University, ↗

Ternary molecular switching in a single-crystal optical actuator with correlated crystal strain

A growing portfolio of single-crystal optical actuators is forging a new class of photonic materials that hold prospects for quantum technologies. Ruthenium-based complexes that exhibit this phenomenon via SO 2 -linkage photoisomerisation are of particular interest since they display multiple metastable states, once induced by green light; yet, complete photoconversion into each SO 2 -isomeric state is rarely achieved. We discover a new complex, trans-[Ru(SO 2 )(NH 3 ) 4 (4-bromopyridine)]tosylate 2 , that produces 100% photoconverted η 1 -OSO isomeric crystal structures at 90 K, which fully transition into η 2 -(OS)O photoisomers upon warming to 100 K, while the dark-state η 1 -SO 2 structure is wholly recovered by heating the crystal to room temperature. Crystal structures and optical-absorption profiles of each state are captured via in-situ light-induced single-crystal X-ray diffraction and optical-absorption spectroscopy. Results show that both photoisomeric species behave as optical switches, but with distinct optical properties. The photoisomerisation process causes thermally-reversible micro- and nanoscopic crystal strain, as characterised by optical microscopy and in-situ light-induced atomic-force microscopy.

actuators↗

Hydrogen-based ore-to-part manufacturing of near-net-shape stainless steel

Decarbonizing iron and steelmaking, combined with global disruptions to raw material supply chains, necessitates novel approaches to iron and steel production. In this work, we demonstrate a direct ore-to-part manufacturing route using a mixture of ore-derived oxide powders of Fe 2 O 3 , Cr 2 O 3 , NiO, and MoO 3 as feedstock for additive manufacturing, combined with sintering under H 2 to produce a near-net-shape austenitic stainless-steel. Complete reduction of all constituent oxides, including MoO 3 and Cr 2 O 3 , is achieved in-situ at 1300 °C, resulting in dense, crack-free bulk alloy. The fabricated part retains geometric fidelity while undergoing substantial volumetric shrinkage inherent to redox and sintering. Thermodynamic calculations elucidate the co-reduction mechanisms and alloying pathways that enable complete metallization. This work is the first demonstration of net-shaping metal parts directly from ore derived oxides, and this ore-to-part approach can minimize the emissions and lead time for manufacturing associated with downstream processing such as rolling, forging, and machining.

Yang, Mingzhang [Univ. of Waterloo, ON (Canada); F↗

Incubating advances in integrated photonics with emerging sensing and computational capabilities

As photonic technologies grow in multidimensional aspects, integrated photonics holds a unique position and continuously presents enormous possibilities for research communities. Applications include data centers, environmental monitoring, medical diagnosis, and highly compact communication components, with further possibilities continuously growing. Herein, we review state-of-the-art integrated photonic on-chip sensors that operate in the visible to mid-infrared wavelength region on various material platforms. Among the different materials, architectures, and technologies leading the way for on-chip sensors, we discuss the optical sensing principles that are commonly applied to biochemical and gas sensing. Our focus is on passive optical waveguides, including dispersion-engineered metamaterial-based structures, which are essential for enhancing the interaction between light and analytes in chip-scale sensors. We harness a diverse array of cutting-edge sensing technologies, heralding a revolutionary on-chip sensing paradigm. Our arsenal includes refractive-index-based sensing, plasmonics, and spectroscopy, which forge an unparalleled foundation for innovation and precision. Furthermore, we include a brief discussion of recent trends and computational concepts, incorporating Artificial Intelligence & Machine Learning (AI/ML) and deep learning approaches over the past few years to improve the qualitative and quantitative analysis of sensor measurements.

Jain, Sourabh (ORCID:0000000279923275)↗

Image plate multi-scan response to fusion protons in the range of 1–14 MeV

Image plates (IPs) are a quickly recoverable and reusable radiation detector often used to measure proton and x-ray fluence in laser-driven experiments. Recently, IPs have been used in a proton radiography detector stack on the OMEGA laser, a diagnostic historically implemented with CR-39, or radiochromic film. The IPs used in this and other diagnostics detect charged particles, neutrons, and x-rays indiscriminately. IPs detect radiation using a photo-stimulated luminescence (PSL) material, often phosphor, in which electrons are excited to metastable states by ionizing radiation. Protons at MeV energies deposit energy deeper into the IP compared with x rays below ∼20 keV due to the Bragg peak present for protons. This property is exploited to discriminate between radiation types. Doses of mono-energetic protons between 1.7 and 14 MeV are applied to IPs using the MIT linear electrostatic ion accelerator. This paper presents the results from consecutive scans of IPs irradiated with different proton energies. The PSL ratios between subsequent scans are shown to depend on proton energy, with higher energy protons having lower PSL ratios for each scan. This finding is separate from the known energy dependence in the absolute sensitivity of IPs. The results can be compared to complimentary work on x rays, showing a difference between protons and x rays, forging a path to discriminate between proton and x-ray fluence in mixed radiation environments.

Instruments & Instrumentation↗

Approaching hydro-equivalent ignition in laser direct-drive via target design optimization using novel statistical modeling

Laser direct-drive offers significant advantages in terms of target simplicity, improved energy coupling, and large fuel masses over indirect drive. However, performance degradations from hydrodynamic and laser-plasma instabilities seeded and driven by the direct illumination pose limitations on the parameter space available for achieving ignition. In this paper, new design improvements are identified to forge a path forward for a hydro-equivalent ignition demonstration. The first is related to a new formulation of the statistical model (SM) used to accurately predict target performance directly from input parameters such as laser pulse shape and target specifications. This new SM formulation provides direct guidance on target dimensions and laser beam-to-target radius to achieve the highest fusion yield on the OMEGA laser. The second improvement comes from cooling the deuterium–tritium (DT) ice layer below the triple point right before shot time leading to lower DT vapor densities and higher convergence. Guided by these design improvements, a Bayesian optimization algorithm was used to design an implosion that is predicted to closely approach a Lawson triple product that hydrodynamically scales to ignition if equivalent laser–target coupling is achieved at laser energies typical of the National Ignition Facility.

Deuterium↗

GEOS-DEV/FORGE

This dataset is a repository that provides the input deck for numerical models associated with two Utah FORGE research projects: "Closing the Loop Between In situ Stress Complexity and EGS Fracture Compexity" (Project Number: 2-2446) and "Coupled Investigation of Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior" (Project Number: 5-2428). Three kinds of simulation decks are included: (i) hydraulic fracturing simulation (HydroFrac folder), (ii) phase-field simulation (PhaseField folder), and (iii) thermo-hydro-mechanical simulation (ThermoHydroMech folder).

Cusini, Matteo [Lawrence Livermore National Labora↗

Fusion Energy Sciences Network Requirements Review: Mild-cycle Update

The US Department of Energy (DOE) Office of Science (SC) world-class research infrastructure provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance core DOE mission science for its sponsor SC program and to stimulate a rich discovery and innovation ecosystem. Research communities gather and flourish around each user facility, bringing together diverse perspectives. The continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

5-2428: Fracture Permeability Impact on Seismic Slip Behavior

Our goal is to develop, apply and validate a holistic thermal, hydrologic, mechanical, and chemical (THMC) workflow that includes evaluation of induced seismic slip in EGS reservoirs. We will integrate experimental and modeling approaches to reduce parameter uncertainty and better predict/mitigate seismic hazard at EGS sites. Our novel approach couples 3D physics-based earthquake simulations with THMC models (THMc+E). This capability will enable improve engineering decisions at Utah-FORGE and move EGS operations toward repeatable, robust, economically viable, and socially accepted development. For example, our THMC+E models will predict circulation scenarios and related seismic hazard for a suite of flow rates and under uncertainty, thus enabling evaluation of optimal circulation strategy. Laboratory experiments will be performed to constrain key model parameters and Bayesian techniques will provide a probabilistic evaluation of parameters used in models. THMC+E simulations will enable exploration various circumstances that may hinder EGS success and develop mitigation strategies.

58 GEOSCIENCES↗

5-2428: Coupled Investigation of Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior [Slides]

Our goal is to develop, apply and validate a holistic thermal, hydrologic, mechanical, and chemical (THMC) workflow that also includes evaluation of induced seismic slip in EGS reservoirs. We will integrate experimental and modelling approaches to reduce parameter uncertainty and better integrate friction constitutive laws for faults to improve our ability to predict and mitigate seismic hazard at Utah FORGE and future EGS sites. We propose a novel approach that incorporates 3D physics-based Earthquake simulations in THMC models, using lab measurements of friction parameters, herein referred to as “THMC+E” models. These simulations will enable exploration of various circumstances that may hinder EGS success and develop mitigation strategies.

58 GEOSCIENCES↗

Collaborative Research: Louis Stokes Regional Center of Excellence: Louis Stokes Midwest Regional Center of Excellence (LSMRCE) for Broadening Participation in STEM

The Louis Stokes Midwest Regional Center of Excellence (LSMRCE) for Broadening Participation in STEM, a partnership of Chicago State University (CSU), aimed to increase the number of underrepresented minority (URM) students graduating with science, technology, engineering, and math (STEM) degrees and matriculating into graduate STEM programs. As a member institution of the LSMRCE, Fermi Research Alliance, LLC, (Fermilab) looked to support its continued mission of increasing URM student participation in its Summer Internship in Science and Technology (SIST) internship program. The program provided URMs with access to research skills development, mentoring and professionalization activities via paid, summer research internships at Fermilab. Students received instruction and mentoring while gaining exposure to a global laboratory workforce and community with diverse academic and professional expertise. In addition, students established professional relationships and networked with senior researchers, early career scientists, technical professionals, post-docs and other undergraduate interns to help forge collaboration, innovation and mentoring opportunities at Fermilab and LSMRCE partner institutions

99 GENERAL AND MISCELLANEOUS↗

Connecting In Situ Stress and Wellbore Deviation to Near-Well Fracture Complexity Using Phase-Field Simulations

The interactions among in situ stress, rock fabric, wellbore geometry, natural fractures, and other natural or man-made defects create highly complex fracture trajectories in the near-wellbore region, far more intricate than those in the far-field. These near-wellbore complexities are critical for the Utah FORGE project and Enhanced Geothermal Systems (EGS) in general. Frictional pressure loss in the near-wellbore region during stimulation can significantly influence the growth of far-field fractures, while pressure losses during circulation serve as a major source of energy dissipation. Near-wellbore fracture complexities are often observable through image logs, offering valuable insights into in situ stress characteristics. However, leveraging this information requires a high-fidelity model capable of capturing the interplay among the diverse factors influencing fracture behavior.

58 GEOSCIENCES↗

Floating Offshore Wind US Manufacturing and Commercialization: Cooperative Research and Development (Final Report)

NREL assessed the supply chain and workforce considerations for the OCG-Wind floater technology, a floating semi-submersible offshore wind substructure, as well sharing vessel needs to inform their installation strategy. This technical assistance was in support of the FLoating Offshore Wind ReadINess (FLOWIN) Prize Phase 2 submission. NREL provided an assessment of domestic supplier capabilities for the main components of their floating offshore wind platform design and analyzed US regional and national supply chain constraints and gaps. Thirteen interviews with companies including steel distributors, forges, foundries, ports, large component fabricators, subcomponent fabricators, and secondary suppliers provided key insights such as 1) assembly ports are the key infrastructure barrier standing in the way of unlocking the domestic assembly and component fabrication for steel-based FOW platforms, 2) domestic steel producers can supply the types and quantities of steel necessary for FOW platforms, and 3) coordination between stakeholders will be a vital part of successfully developing the supply chain and infrastructure needed to domestically produce FOW platforms. In the workforce assessment, NREL documented a step-by-step approach to conduct a place-based assessment of the foundational workforce consideration for recruiting, upskilling, and retaining a workforce, such as supportive local and state policy, nearby education and training programs, and existing relevant industry. This approach was applied to Tacoma, Washington. Tacoma was indicated to have the potential be a successful location for fabrication and assembly of floating offshore wind energy in terms of workforce development. To share data on vessel requirements to install the OCG-Wind floater, NREL compiled resources that help answer the questions related to anchor handling tug vessels, shared a database of cable laying vessels, and answered questions on complying with the Jones Act.

17 WIND ENERGY↗