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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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471 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Resolving root causes of experiment discrepancies guided by machine learning

Abstract Scientists rely on accurate experimental data to explain nature and then harness this knowledge for applications addressing human needs. However, discrepancies between experiments of the same observable can impede scientific progress if one does not understand the underlying causes. Here, we developed a process that unravels data discrepancies by first using Bayesian machine learning to relate discrepancies to few of many, potentially biasing metadata features that encode experiment procedures. This machine learning output guides human experts to study discrepancy causes by simulating suspicious aspects of historical experiments or designing modern ones to address open questions. The study findings then lead to rejecting or correcting historical data on firm scientific bases. This process is demonstrated for the energy spectrum of neutrons emitted promptly (<1 ns) after fission of 252 Cf, a trusted nuclear physics Standard. It reduces the spread in experimental 252 Cf spectra by up to a factor of 6.

Neudecker, D. (ORCID:0000000339200627)↗
DOE OSTI2026

Revealing Hidden Quinones Through Diagnostic MS² Fragmentation of Peptide–Quinone Adducts

Quinones are redox-active components of natural organic matter that mediate electron transfer and influence biogeochemical processes, but many quinones in pyrogenic organic matter (PyOM) remain unresolved because they ionize poorly by mass spectrometry. Here, we present a peptide-tagging approach to improve detection of cysteine-reactive electrophiles in PyOM, with quinones expected to be a dominant subset based on reaction chemistry and selectivity experiments. A cysteine-containing peptide was used to form Michael-addition adducts, enhancing electrospray ionization and enabling untargeted screening by high-performance liquid chromatography-high-resolution tandem mass spectrometry. The method was benchmarked with five quinone standards and applied to extracts from charred plant material as a discovery-level screen for cysteine-reactive targets. We identified 98 quinone-candidate adducts (mean neutral mass ~603 Da), of which more than 70% were not detectable in native MS1 data. Among formula-assigned features, hidden quinone candidates had median (O+N)/C of 0.391 and normalized oxidation state of carbon of -0.281, consistent with relatively low polarity and low oxidation state. These results reveal a previously inaccessible pool of hidden redox-active compounds in PyOM and provide a framework for prioritizing quinone-like electrophiles for confirmation and incorporation into models of fire-driven biogeochemical cycling.

LC-MS/MS↗
DOE OSTI2026

Triggerable adhesives with infinite working life for large area application

Oak Ridge National Laboratory (ORNL) Manufacturing Demonstration Facility (MDF) entered a User Proposal with Perseus Materials in Knoxville, TN. By reinventing how composites are made, we unlock a new era of structural materials: faster to produce, easier to assemble, and strong enough for real-world scale. Perseus Materials was targeting the wind turbine industry to make large adhesive joints for composite turbine blades without the limitations of cure time and room temperature cure without the needs to have work times. The triggerable aspect would increase manufacturing rates for composite wind turbine blades.

36 MATERIALS SCIENCE↗
DOE OSTI1998

Fusion Safety Program Peer Review (August 31 and September 1, 1999) [Slides]

The Fusion Safety Program Peer Review conference, held on August 31 and September 1, 1999, focuses on advancing the understanding and management of radioactive and hazardous materials within deuterium-tritium (D-T) fusion machines. The conference aims to investigate the behavior of significant sources of radioactive materials, such as activation products, dust, tritium, and beryllium. Additionally, it seeks to comprehend how various energy sources in fusion facilities—such as magnets, plasma, decay heat, and chemical reactions—can mobilize these materials. A key objective of the conference is to develop integrated, state-of-the-art analytic tools to demonstrate the safety and environmental potential of fusion technology. Furthermore, the conference assesses and evaluates safety and environmental issues associated with emerging fusion concepts, including those in the ARIES, ALPS, APEX, and IFE projects. This comprehensive approach aims to ensure the safe and sustainable advancement of fusion energy.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Storing Affordability: Battery Storage as an Asset to Reduce Data Center Cost Shifts

This report examines how battery energy storage systems (BESS) can help utilities accommodate large load growth while protecting affordability for existing ratepayers. Rapid growth in electricity demand from artificial intelligence (AI) data centers is straining the U.S. grid. Furthermore, many new data centers are entering rural markets, which could offer economic benefits but may also pose implementation challenges for smaller utilities. At the same time, retail electricity prices are increasing faster than inflation, elevating customer affordability as a key challenge. While data centers have not been the primary driver of increases in residential prices to date, they have pushed wholesale energy and capacity prices higher in several markets. Fundamental utility cost-allocation principles show that data center growth can be rate-positive for existing customers only if new peak demand grows faster than the costs a utility must incur to serve it. Several factors, including a utility’s degree of wholesale market exposure, forecast uncertainty and stranded-asset risk, and tariff design can determine the outcome of load growth on retail rates. Energy storage can make several affordability contributions in the face of this landscape of uncertainty and market volatility, including deferral of higher-cost grid investments through improved utilization of existing assets and flexibility of new large loads, insulation from volatile wholesale prices through peak shaving, and reliability support to address grid risks stemming from the behavior of AI data center loads. Different potential BESS deployment pathways—utility-scale front-of-the-meter systems, aggregated small-scale storage installations, and data center-sited behind-the-meter storage—are compared against each other and against conventional capacity alternatives. This framework is intended as a conceptual resource to utilities, particularly smaller public utilities with rural service territories, who may be considering the role that energy storage can play in insulating existing ratepayers from data center cost shifts.

25 ENERGY STORAGE↗
DOE OSTI2026

Tunable magnetic excitations in the honeycomb antiferromagnet (Co,Ni)⁢TiO3

The solid solution of the honeycomb antiferromagnet (AFM) Co0.5⁢Ni0.5⁢TiO3 (CNTO) was synthesized by mixing a 1:1 molar ratio of CoTiO3 (CTO) and NiTiO3 (NTO). Powder neutron scattering was used to determine the structure and magnetic spectrum, where the nuclear and magnetic structures resemble those of the end members. The Néel temperature (T𝑁 = 27 ± 1 K), the ordered magnetic moment (M = 2.29 ± 0.03 𝜇𝐵 per magnetic ion), and lattice parameters are intermediate between those of the two. From inelastic neutron scattering, it is observed that the magnon density of states (MDOS) extends up to 13 meV, and the interaction can be described by an XXZ-type magnetic Hamiltonian. Above 15 meV, spin-orbit excitons (SOEs) are observed similarly to those in CTO, but with modified spin-orbit crystal-field splitting because of the substitution of Ni at Co sites, and the disorder induced by the Ni substitution modifies the spin-orbit crystal field. Thus, the magnetic dynamics of the CNTO cannot be described as a simple average of the two parent compounds.

Rathnayaka, Srimal [University of Virginia, Charlo↗
DOE OSTI2026

How efficiently can AI recognize Wireless Devices?

This poster presents a hardware benchmarking methodology for a 3-layer CNN waveform classifier deployed using ONNX Runtime on an NVIDIA Jetson AGX Orin. The dataset consist of 9 signal types, -30 to +30 dB SNR with 5dB increments. Benchmarking on the Jetson AGX Orin gave an accuracy of 91.9% and GPU throughput of 107,120 predictions/sec (23× faster than CPU). The Jetson GPU reached approximately 27M samples/sec with stable performance but fell below the 40 MHz rate needed for real-time radio feeds. Sustained testing of 5 minutes confirmed stable performance with no memory leaks, establishing a reproducible benchmarking baseline for future edge-deployment optimization.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Heterogeneous Solid Electrolyte Interphase Interactions Dictate Interface Instability in Sodium Metal Electrodes

Sodium (Na) metal batteries have attracted recent attention due to their low cost and high abundance of Na. However, the advancement of Na metal batteries is impeded due to key challenges such as dendrite growth, solid electrolyte interphase (SEI) fracture, and low Coulombic efficiency. This study examines the coupled electro‐chemo‐mechanical interactions governing the electrodeposition stability and morphological evolution at the Na/electrolyte interface. The SEI heterogeneities influence transport and reaction kinetics leading to the formation of current and stress hotspots during Na plating. Further, it is demonstrated that the heterogeneity‐induced Na metal evolution and its influence on the stress distribution critically affect the mechanical overpotential, contributing to a faster SEI failure. The analysis reveals three distinct failure mechanisms—mechanical, transport, and kinetic—that govern the onset of instabilities at the interface. Finally, a comprehensive comparative study of SEI failure in Na and lithium (Li) metal anodes illustrates that the electrochemical and mechanical characteristics of the SEI are crucial in tailoring the anode morphology and interface stability. This work delineates mechanistic stability regimes cognizant of the SEI attributes and underlying failure modes and offers important guidelines for the design of artificial SEI layers for stable Na metal electrodes.

25 ENERGY STORAGE↗
DOE OSTI2023

Self‐Propelling Macroscale Sheets Powered by Enzyme Pumps

Nanoscale enzymes anchored to surfaces act as chemical pumps by converting chemical energy released from enzymatic reactions into spontaneous fluid flow that propels entrained nano‐ and microparticles. Enzymatic pumps are biocompatible, highly selective, and display unique substrate specificity. Utilizing these pumps to trigger self‐propelled motion on the macroscale has, however, constituted a significant challenge and thus prevented their adaptation in macroscopic fluidic devices and soft robotics. Using experiments and simulations, we herein show that enzymatic pumps can drive centimeter‐scale polymer sheets along directed linear paths and rotational trajectories. In these studies, the sheets are confined to the air/water interface. With the addition of appropriate substrate, the asymmetric enzymatic coating on the sheets induces chemically driven, buoyancy flows that controllably propel the sheet's motion on the air/water interface. The directionality and speed of the motion can be tailored by changing the pattern of the enzymatic coating, type of enzyme, and nature and concentration of the substrate. This work highlights the utility of biocompatible enzymes for generating motion in macroscale fluidic devices and robotics and indicates their potential utility for in vivo applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Probing the atomic dynamics of ultrafast melting with femtosecond electron diffraction

Melting is an every-day phase transition that is determined by thermodynamic parameters like temperature and pressure. In contrast, ultra-fast melting is governed by the microscopic response to a rapid energy input and, thus, can reveal the strength and dynamics of atomic bonds as well as the energy flow rate to the lattice. Accurately describing these processes remains challenging and requires detailed insights into transient states encountered. Here, we present data from femtosecond electron diffraction measurements that capture the structural evolution of copper during the ultrafast solid-to-liquid phase transformations. At absorbed energy densities 2-4 times the melting threshold, melting begins at the surface slightly below the nominal melting point followed by rapid homogeneous melting throughout the volume. Molecular dynamics simulations reproduce these observations and reveal a weak electron-lattice energy transfer rate for the given experimental conditions. Both simulations and experiments show no indications of rapid lattice collapse when its temperature surpasses proposed limits of superheating, providing evidence that the inherent dynamics limits the speed of disordering in ultrafast melting of metals.

FOS: Physical sciences↗
DOE OSTI2026

Paleotribological models using preserved fossil tissue properties reveal functional significance of Eurasian mammoth dental evolution

Eurasian mammoths (Mammuthus) underwent substantial modifications in molar morphology as later-diverging species evolved progressively thinner enamel and increased enamel crest complexity. These features have been hypothesized to reduce whole-tooth wear and extend dental longevity as increasingly graze-dominated diets evolved within the lineage. This hypothesis has yet to be directly tested. Here, in this study, we developed an in-silico wear model using experimentally derived wear rates from fossil and extant proboscidean dental tissues. The models revealed that shifts in tissue topology do not affect whole-tooth wear rate, as inverse trends in lamellar frequency and enamel thickness preserve a consistent surface enamel area fraction; the determining factor of wear. Rather, topological shifts produce a wear-emergent secondary occlusal surface with greater numbers of triturating crests that create a regular, low-relief, file-like shearing pavement. These changes in occlusal architecture likely directly impacted the mastication capacity of Mammuthus dentitions, facilitating their dietary expansion to incorporate fibrous, lower-nutrient graze.

Dental wear↗
DOE OSTI2026

Computational discovery of a tetragonal MBene phase: diamond-shaped boron lattices, viable MAB precursors, and selective CO 2 reduction

MBenes are a class of two-dimensional transition-metal borides derived from layered MAB phases. Here, we use first-principles calculations to predict a new tetragonal MB (1 : 1) MBene phase featuring a diamond-shaped B–B lattice and systematically assess its phase stability, synthetic accessibility, and catalytic performance towards the CO 2 reduction reaction (CO 2 RR). Four tetragonal configurations are benchmarked against known hexagonal and orthorhombic phases, and a multi-tier screening identifies six robust members (CrB, FeB, MoB, WB, IrB, and PtB). Exploration of the I4/mmm MAB space reveals 11 viable precursors, including the experimentally synthesized Ir 2 ZnB 2 , which validates our screening approach. CO 2 RR free-energy diagrams show that CrB favors CH 3 OH while FeB, MoB, WB, IrB, and PtB preferentially yield HCOOH. The corresponding limiting potentials are competitive with, and in some cases superior to, those reported for state-of-the-art orthorhombic and hexagonal MBenes. These findings expand the MBene landscape by establishing a tetragonal phase with structural, synthetic, and catalytic promise.

Lu, Linguo [University of Puerto Rico, San Juan, P↗
DOE OSTI2025

High‐Performance Rechargeable Lithium‐Chlorine Batteries with ALD Conformal Starburst Porous Graphene Positive Electrodes

Abstract Rechargeable alkali metal‐chlorine batteries are emerging as a promising high‐energy‐density solution. However, they confront significant challenges, including the primary issue stemming from the weak binding affinity of cathode materials for Cl 2 , which leads to a sluggish and inadequate supply of Cl 2 during the redox reactions, resulting in a shortened cycle life and low Coulombic efficiency (CE), particularly when operating at ultrahigh specific capacity outputs. Herein, an Al 2 O 3 ‐skinned heterostructured starburst porous graphene with conformal metasurfaces (Al 2 O 3 @rGO) is reported, crafted from a hierarchical porous starburst graphene arranged in a unique layered structure by the PTFE microemulsion skin effect, leveraging subsequent fluidized bed atomic layer deposition (FBALD) of Al 2 O 3 groups. Al 2 O 3 @rGO features superhydrophilicity, effective adsorption, fast kinetics from stable dynamic respiratory interface, high electrical and thermal conductivity anisotropy, intelligent thermal management and safe operation over a wide temperature range. Consequently, the Li‐Cl 2 @Al 2 O 3 @rGO battery achieves an ultrahigh discharge specific capacity of 5000 mAh g −1 at ≈100% CE, and even delivers stable cycling over 200 cycles with 2000 mAh g −1 at an average CE of 99.8% under low temperature environment of ‐40 °C. The scalable heterostructure approach offers a sustainable perspective of the development of functionalized metamaterials and metasurfaces for next‐generation safe and energy‐dense batteries and broader applications.

Chemistry↗
DOE OSTI2026

A Full-Induction Magnetohydrodynamics Solver for Liquid Metal Fusion Blankets in Vertex-CFD

Multiphysics modeling of liquid metal fusion blankets, which produce tritium and convert energy of neutrons created via fusion reactions into heat, is crucial for predicting performance, ensuring structural integrity, and optimizing energy production. While traditional blanket modeling of liquid metal flows during normal steady operating conditions commonly employs the inductionless approximation of the magnetohydrodynamics (MHD) equations, transient scenarios, when the plasma-confining magnetic field varies on millisecond time scales, require a full-induction MHD approach that dynamically evolves the magnetic field via the time-dependent induction equation. This paper presents the formulation, implementation, and initial verification of a full-induction MHD solver integrated within the open-source Vertex-CFD framework, which aims to achieve tight multiphysics coupling, a flexible software design enabling easy extension and addition of physics models, and performance portability across computing platforms. The solver utilizes finite element spatial discretization, implicit Runge–Kutta time integration, and an inexact Newton method to solve the resulting discrete nonlinear system, leveraging Trilinos packages for efficient computation. Verification against selected benchmark problems demonstrates accuracy and robustness of the solver. Furthermore, when the solver is applied to an idealized blanket model in 2.5D and full 3D, results obtained with Vertex-CFD are in good agreement with recently published quasi-2D simulations. These findings establish a computational foundation for future simulations of transient MHD phenomena in liquid metal blankets with Vertex-CFD, and open avenues for future extensions and performance optimizations.

Endeve, Eirik [ORNL] (ORCID:0000000312519507)↗
DOE OSTI2026

The CP-PAW Code Package for First-Principles Calculations from a User’s Perspective

CP-PAW is a combined electronic structure and ab initio molecular dynamics code to perform mixed quantum and classical simulations of atomistic condensed phase systems, such as solids, liquids, and molecular systems. As the name suggests, the CP-PAW code unifies the all-electron projector augmented-wave (PAW) method with the Car–Parrinello (CP) approach to determine not only the electronic and nuclear ground states of condensed matter but also to study their properties and dynamics. In addition to briefly outlining the underlying theory, the focus will be on the unique aspects of CP-PAW and how to correctly employ them as a user. How to install CP-PAW using the new build system will also be briefly mentioned.

Blöchl, Peter E [Institute for Theoretical Physic↗
DOE OSTI2026

Insights into mixing of non-isothermal multi-polymer melts for complex plastics recycling

Catalytic recycling or upcycling of plastics is often limited not by catalyst performance, but by transport, arising from highly viscous, non-Newtonian polymer melts. In this work, we develop a reactor-scale framework that integrates rheological measurements, constitutive modeling, computational fluid dynamics (CFD), and experiments to quantify mixing, heat transfer, and dispersion in surrogate hydrocarbon melts representing mixed plastics systems. Temperature- and shear rate-dependent viscosity of low-density polyethylene (LDPE) and high-density polyethylene (HDPE) is measured to create two surrogate polymers (PLD and PHD) that capture the dominant shear-thinning flow behavior while neglecting strong elastic effects, enabling tractable simulation of non-isothermal, polymer-melt mixing using a Carreau-Arrhenius generalized Newtonian framework. Three-dimensional CFD simulations are employed to evaluate impeller performance in PLD using mixing time, cavern volume, thermal uniformity, and interfacial area for regimes in which viscoelastic effects are not dominant. We show that magnetic stir bars commonly used in lab-scale studies produce large thermal gradients (~60 °C) and poor mixing, even under idealized power delivery and polymer flow conditions. In contrast, close-clearance anchor impellers achieve near-isothermal operation, reduce mixing times by up to 5×, and provide >90% active circulation volume. We further demonstrate that, at low pseudo-Deborah number (De*), motor power requirements can be predicted directly from shear rate-dependent rheology using the Carreau-Arrhenius framework, enabling rational selection of operating conditions. Extension to surrogate immiscible multi-polymer systems based on PLD and PHD shows that interfacial area is highly sensitive to operating conditions and impeller design, with coaxial anchor-turbine configurations enhancing dispersion by up to 4 × .

Close-clearance impellers↗
DOE OSTI2026

Application of Ibuprofen Sodium Dihydrate for Thermochemical Energy Storage

Thermochemical energy storage (TCES) offers a transformative approach to address grid instability by harnessing reversible chemical reactions for efficient heat storage and release. Here, we introduce pharmaceutical organic salt hydrates as a class of materials with exceptional performance for low-grade waste heat recovery. We demonstrate ibuprofen sodium dihydrate (ISD) as an example organic hydrate exhibiting a dehydration temperature range of 60-110 °C and a remarkable dehydration enthalpy of up to 59.5 kJ/mol of water, ideally suited for capturing industrial and residential waste heat. Using rigorous multimodal characterization, including thermogravimetric analysis, differential scanning calorimetry, in-situ FTIR, in-situ PXRD, and NMR, we demonstrate ISD's superior thermal, chemical, and structural stability over 150 hydration-dehydration cycles, achieving an unprecedented cycling efficiency of ~99.9%. Compared to conventional inorganic salt hydrates like strontium chloride hexahydrate and calcium oxalate monohydrate, ISD showcases enhanced durability without deliquescence or pulverization, even under high-humidity conditions. In-situ analyses confirm the transition from ISD to ibuprofen sodium anhydrous (ISA) proceeds with structural reorganization, thereby combining the dehydration mechanism with phase transitions, resulting in higher energy storage capacity. Microstructural analyses reveal that repeated water intercalation and structural transitions aid in creating significant porosity that enhances water transport kinetics, further improving the hydration/dehydration performance. By combining the phase change and chemical dehydration mechanisms, ISD paves the way for designing a new class of organic salt hydrates, offering tunable properties to meet diverse thermal energy storage demands and supporting sustainable grid resilience.

Thangaraj, Kavin C.↗
DOE OSTI2025

An evolutionarily conserved tryptophan cage promotes folding of the extended RNA recognition motif in the hnRNPR ‐like protein family

Abstract The heterogeneous nuclear ribonucleoprotein (hnRNP) R‐like family is a class of RNA binding proteins in the hnRNP superfamily with diverse functions in RNA processing. Here, we present the 1.90 Å X‐ray crystal structure and solution NMR studies of the first RNA recognition motif (RRM) of human hnRNPR. We find that this domain adopts an extended RRM (eRRM1) featuring a canonical RRM with a structured N‐terminal extension (N ext ) motif that docks against the RRM and extends the β‐sheet surface. The adjoining loop is structured and forms a tryptophan cage motif to position the N ext motif for docking to the RRM. Combining mutagenesis, solution NMR spectroscopy, and thermal denaturation studies, we evaluate the importance of residues in the N ext –RRM interface and adjoining loop on eRRM folding and conformational dynamics. We find that these sites are essential for protein solubility, conformational ordering, and thermal stability. Consistent with their importance, mutations in the N ext –RRM interface and loop are associated with several cancers in a survey of somatic mutations in cancer studies. Sequence and structure comparison of the human hnRNPR eRRM1 to experimentally verified and predicted hnRNPR‐like proteins reveals conserved features in the eRRM.

Biochemistry & Molecular Biology↗