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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Design, fabrication, simulation, and testing of additively manufactured lattice-based copper heat sinks

Here, this study investigates the potential advantages of lattice structure-based bound metal material extrusion (MEX) 3D printing for fabricating high-performance copper heat sinks. Copper powder-filled polymer filaments, with a copper content of > 90 wt.%, were developed specifically for the bound metal MEX 3D printing process. Three types of structures—planar, strut, and surface lattices—were 3D printed to facilitate efficient heat transfer pathways within the heat sinks. Subsequent post-processing steps, including polymer removal and sintering, were performed to achieve dense copper parts. Hot isostatic pressing was further employed to enhance the sintered density from 93 to 98%. Finite element analysis (FEA) simulations were conducted to assess the heat transfer efficiency of the designs, and heat transfer experiments were performed using a custom setup to validate the simulation results. Additionally, this research explores the use of extended hold times during pre-sintering and a reduced atmosphere to enhance the %IACS values (electrical conductivity) and thermal performance of the bound metal MEX 3D printed copper heat sinks. The investigation combines experimental analysis, including simulations and heat transfer experiments, to gain insights into the structure-material property relationships and optimize the thermal performance of the printed heat sinks.

Ajjarapu, Kameswara Pavan Kumar [Oak Ridge Nationa↗
DOE OSTI2026

Quantum Computing for AI-based Design and Optimization of Electric Motors

Knowledge-based artificial intelligence and hierarchical fuzzy logic offer an interpretable framework for electricvehicle motor preliminary design, but their computational burden grows with linguistic granularity and coupled design-space size. This paper presents a reduced quantum reformulation of the hierarchical fuzzy inference of air-gap flux density, a representative level-one motor-design parameter. Starting from the published electric-vehicle motor-design framework, a three-term fuzzy prototype is constructed from the original inference structure. The reduced model is then reformulated as a modular quantum register-oracle system, in which each hierarchical subrelation is encoded as a block oracle and evaluated through superpositionbased candidate-label testing. The proposed modular quantum formulation reproduces the reduced classical prototype after block fusion. A resource analysis shows that the reduced modular system requires seven qubits per block and twenty-two qubits in a straightforward four-block implementation. Finally, a crossovercomplexity model is derived to identify the regime in which quantum candidate search may become favorable relative to hierarchical fuzzy inference. The results show that no quantum advantage should be claimed for the present one-output reduced benchmark, but that a plausible crossover emerges for larger joint candidate spaces and higher linguistic granularity. The work therefore establishes a technically consistent starting point for future quantum-assisted electric-vehicle motor-design optimization.

Kumar, Praveen [ORNL] (ORCID:0000000291877857)↗
DOE OSTI2025

Structural Evolution and Stability of Rh/TiO 2 Catalysts under CO 2 Hydrogenation Conditions: Influence of the Initial Rh Structure

Characterizing catalyst stability by identifying the predominant mechanisms, timescales and driving forces of catalyst reconstruction under relevant reaction conditions is necessary for the design and commercialization of new catalysts. Here, in this paper, we study Rh/TiO 2 catalysts under CO 2 hydrogenation conditions (773 K, 75% H 2 , 25% CO 2 ) at high conversion and utilize reactivity studies along with ex-situ and in-situ spectroscopy and microscopy to characterize changes in catalyst activity and structure as a function of time on stream and the initial catalyst structure. This is a prototypical catalyst for CO 2 hydrogenation where Rh structure and Rh-TiO 2 interactions have been proposed to explain reactivity, selectivity (between CO and CH 4 formation) and catalyst stability. The influence of the initial Rh structure (varying from Rh single atoms to Rh nanoparticles), support stability, regeneration and pretreatment(s), and the chemical potential(s) of the reaction environment on reaction selectivity and catalyst stability were explored. The product selectivity between CO and CH 4 was determined to be dependent on the relative fraction of Rh single atoms and Rh nanoparticle-TiO 2 interfacial sites under reaction conditions, each exhibiting distinct stability under prolonged time on stream. Surprisingly, Rh single atoms exhibited stability for the duration of 90 h reactivity measurements, even at high Rh density (≥ 1.8 Rh atoms/nm 2 ) on the support, while Rh nanoparticles sintered under reaction conditions. As a result, all catalysts exhibited increasing selectivity to CO with increasing time on stream (> 10 h). We conclude the distribution of Rh structures evolved over time under reaction conditions through three distinct reconstruction mechanisms (Rh particle fragmentation, Ostwald ripening, and particle migration and coalescence) that occurred on varying timescales. Catalyst stability on the ~90 h time scale was ultimately controlled by the initial Rh structure.

25 ENERGY STORAGE↗
DOE OSTI2025

Diffusion Model-Guided Inverse Design of Bimetallic Catalysts for Ammonia Decomposition

In the past decade, artificial intelligence and deep learning have played increasingly prominent roles in materials design and discovery. Among these, generative AI models, known for their ability to create unique and complex structures, have emerged as state-of-the-art tools for materials screening due to their high efficiency and low computational cost. In catalysis, one of the major challenges is identifying promising material candidates within an immense chemical space. This challenge can be addressed using generative approaches, such as diffusion-based inverse design models. In this study, we present a machine learning-guided workflow that employed a diffusion model for the inverse design of bimetallic alloy catalysts for low-carbon ammonia decomposition, a key reaction for ammonia emission control and sustainable hydrogen production. Catalyst candidates were evaluated using nitrogen adsorption energy as the key descriptor, inspired by multiscale modeling. The proposed workflow identified low-cost, environmentally friendly catalysts with excellent catalytic performance, which have been validated theoretically and experimentally. Our framework decoupled the generative and property-prediction components, enhancing both flexibility and accuracy in the catalytic material design process.

Adsorption↗
DOE OSTI2025

Flux Synthesis of Lattice‐Engineered Rutile Solid Solutions for Acidic Oxygen Evolution

Developing efficient and stable electrocatalysts for the acidic oxygen evolution reaction (OER) is vital for advancing proton exchange membrane water electrolysis (PEMWE) technologies. Here, in this study, we report a flux synthesis of nitrogen-doped Ti–Ru rutile-type solid-solution oxides (M-TiRu 4 ) using molten NaNO 3 as the flux medium. The flux medium promotes the low-temperature conversion of TiN to rutile TiO 2 , while in situ-formed RuO 2 nanoparticles facilitate lattice templating and couple with interfacial ion migration, enabling the formation of homogeneous solid solutions with abundant lattice heterogeneity. Simultaneously, nitrogen atoms are stably incorporated into the lattice of solid solutions, inducing bandgap narrowing, which enhances electronic conductivity. The developed M-TiRu 4 catalyst exhibits exceptional acidic OER performance, delivering a low overpotential of 194 mV at 10 mA cm −2 , superior durability over 600 h, and a Ru mass activity 7.8 times that of commercial RuO 2 . At the device level, M-TiRu 4 enables PEMWE operation at 1.64 V @ 2 A cm −2 and maintains stable performance at 500 mA cm −2 for 200 h with a minimal degradation rate of 20 µV h −1 . This work demonstrates a robust approach for designing high-performance, durable acidic OER catalysts via synergistic lattice and electronic structure engineering, paving the way for next-generation water-splitting technologies.

Wang, Fan [Univ. of Tennessee, Knoxville, TN (Unit↗
DOE OSTI2025

Tuning the Properties of Lignin‐Derived Deep Eutectic Solvents for Biomass Processing

Lignin-derived deep eutectic solvents (DESs) have been investigated as sustainable green media for biomass processing. However, the properties and processability of DESs have not been fully understood with the chemical structures of their constituents for biomass fractionation. Here, in this article, the properties of the phenolic DESs are discussed with different numbers of functional groups, such as –OCH 3 and –CHO in their hydrogen bond donor (HBD) structures. The formation of DES is significantly related to the hydrogen bond between its constituents, identified by nuclear magnetic resonance (NMR) analysis and density functional theory calculation (DFT). Lower viscosity and net basicity of DES are achieved with fewer –OCH 3 on HBD structures, resulting in enhanced processability and fractionation efficiency. The thermal stability of the DES is also influenced by the –OCH 3 and –CHO of HBD, as indicated by its onset temperature. The recyclability of the phenolic DES is confirmed by the fractionation performance of the recycled DES. Understanding the structural impacts of DES constituents on the properties and performance is crucial for designing solvents in biorefinery applications.

Ryu, Jiae [State University of New York (SUNY), Sy↗
DOE OSTI2025

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗
DOE OSTI2026

Impact of Cation Insertion on Semiconducting Polymer Thin Films toward Electrochemical Energy Conversion

Semiconducting polymers are being explored for electrochemical and photoelectrochemical energy transformation and storage applications. For these applications, it is critical to understand how ion insertion from the electrolyte into polymer electrodes modulates the polymer electronic structure and electron doping levels. Here, this study explores electrochemical cation insertion in the n-type conjugated redox polymer P90, composed of alternating naphthalene diimide (NDI) acceptor and bithiophene (T2) donor units, where the NDI units are functionalized with heptaethylene glycol (HEG, 90%) and 2-octyl dodecyl (OD, 10%) side chains. By combining in situ techniques (UV-vis absorption and Raman spectroscopies with electrochemistry), structural analysis using ex situ grazing-incidence wide-angle X-ray scattering (GIWAXS), and density functional theory (DFT) calculations, we reveal that dications enable negative polaron and bipolaron formation in the P90 at less reducing potentials while supporting more bipolaron formation than the monocations; moreover, larger dications with smaller hydrated radii increase the maximum P90 electron doping level. We also determine that the monocations lead to more thermodynamically stabilized polarons compared with the dications. These findings highlight the critical role of cation identity in tuning electrochemical charging, charge stabilization, and electronic structure of n-type conjugated redox polymers, providing guidance on the rational design of polymer-based (photo)electrochemical applications.

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

Single-Molecule Electron Transport in Peptoids

Peptoids are structural analogs of peptides in which side chains are appended to the backbone nitrogen rather than the α-carbon. The sequence-defined modularity of peptoids enables precise control over structure−function relationships, enabling applications in energy storage and biomedical materials. Despite recent progress, the role of sequence and conformation on electron transport in peptoid molecules is not fully understood. Here, we synthesize a library of peptoid oligomers and characterize their molecular electronic properties using the scanning tunneling microscope-break junction (STM-BJ) technique. Our results show well-defined electron transport behavior for peptoid sequences containing aromatic side groups lacking hydrogen bonds (H-bonds) and without chemical substitutions at the N−C α position. This behavior fundamentally differs from electron transport in peptides, where H-bond interactions give rise to higher conductance states. All-atom molecular dynamics (MD) simulations are used to understand the conformational heterogeneity of peptoids, and molecular conformations obtained from MD simulations are used in quantum mechanical calculations based on the nonequilibrium Green’s function−density functional theory (NEGF-DFT) formalism. In all cases, computational results are in reasonable qualitative agreement with experiments. Our work demonstrates that the conductance behavior of peptoids depends on monomer identity, including side-chain aromaticity and substitution at the N−C α position. Overall, this work provides new insights into the structure−function relationships governing electron transport in peptoid-based materials and establishes design rules for peptoid-based molecular junctions.

Charge transport↗
DOE OSTI2026

Scalable Hot-Water-Repellent Superhydrophobicity via Thermal Insulation

Superhydrophobic surfaces, which rely on a combination of surface texture and chemistry, often lose their repellent behavior when contacted by hot water (≳40 °C) because the impinging hot water replaces the requisite air layer within the surface texture via evaporation and recondensation. In contrast to previous approaches targeting this condensation-induced failure mode that rely on intricately tailored surface structures or complex chemical treatments, we present a scalable approach based on thermal design: the multilayered insulated superhydrophobic (MISH) coating mitigates condensation-induced failure by preventing heat transfer. Superhydrophobicity is retained at impinging water temperatures up to 90 °C, with durability demonstrated via long-term (>1 million impacts) droplet impingement experiments. We explain the mechanism for this approach with a detailed thermal model; the model reveals that the underlying physical behavior is self-similar across coating parameters and impinging fluid temperatures. Finally, the MISH coating accommodates curved geometries and large surfaces, and it is over 4 orders of magnitude less expensive than cleanroomnanofabricated alternatives, indicating promise for practical use in the energy sector, chemical processing, and the food and medical industries.

coating materials↗
DOE OSTI2026

Hierarchical Epoxy Structures via Tunable Polymerization-Induced Phase Separation Combined with Additive Manufacturing

Polymerization-induced phase separation (PIPS) allows for the control of thermoset morphologies and properties, enabling the tuning of domain sizes and thermomechanical response. However, its use in generating substructural features in additively manufactured materials has been limited. In this work, we combine epoxy PIPS with UV curable acrylate and rheological modifiers to print nano- to macro-phase separating materials via a two-step, dual-cure approach. This method enables direct ink write printing of hierarchical structures with both controlled morphologies through phase separation and macroscale architecture through print design. We find that formulations for phase-separating materials require judicious incorporation of additives to enable printability and to provide sufficient green strength. Atomic force microscopy-nano infrared mapping reveals tunable, reticulated nano- to micron-scale domains of the resultant multiphase materials and their morphology changes due to additives, resulting in alterations to thermomechanical and tensile properties. Shape memory behavior is also demonstrated through multimaterial additive manufacturing of epoxies with functionally graded internal morphology using active mixing techniques, highlighting this method’s ability to fabricate complex architectures with controlled morphologies and thermomechanical response.

Van Meter, Kylie E [Organic Materials Science, San↗
DOE OSTI2025

Autonomous Multistate Nanoencoding Using Combinatorial Ferroelectric Closure Domains in BiFeO 3

Recent advances in ferroic materials have identified topological defects as promising candidates for enabling additional functionalities in future electronic systems. The generation of stable and customizable polar topologies is needed to achieve multistates that enable beyond-binary device architectures. Here, in this study, we show how to autonomously pattern on-demand highly tunable striped closure domains in pristine rhombohedral-phase BiFeO 3 thin films through precise scanning of a biased atomic force microscopy tip along carefully designed paths. By employing this strategy, we generate and manipulate closed-loop structures with high spatial resolution in an automated manner, allowing the creation of highly tunable and intricate topological domain structures that exhibit distinct polarization configurations without the need for electrode deposition or complex heterostructure growth. As a proof-of-concept for ferroelectric beyond-binary memory devices, we use such topological domains as multistates, engineering an alphabet and automating the symbolic writing/reading process using autonomous microscopy. The resulting information density is compared with that of current commercially available memory devices, demonstrating the potential of ferroelectric topological domains for multistate information storage applications.

BiFeO3↗
DOE OSTI2025

Orbital inversion and emergent lattice dynamics in infinite layer CaCoO 2

The layered cobaltate CaCoO 2 exhibits a unique herringbone-like structure. Serving as a potential prototype for a new class of complex lattice patterns, we study the properties of CaCoO 2 using X-ray absorption spectroscopy (XAS) and resonant inelastic X-ray scattering (RIXS). Our results reveal a significant inter-plane hybridization between the Ca 4s- and Co 3d- orbitals, leading to an inversion of the textbook orbital occupation of a square planar geometry. Further, our RIXS data reveal a strong low energy mode, with anomalous intensity modulations as a function of momentum transfer close to a quasi-static response. These findings indicate that the newly discovered herringbone structure exhibited in CaCoO 2 may serve as a promising laboratory for the design of materials having strong electronic, orbital and lattice correlations.

Electronic properties and materials↗
DOE OSTI2026

Influence of Surfactants on Noble Metal Liquid-Gas Interface Mass Transfer in Molten Salt Reactors

Noble metals, a group of insoluble fission products (FPs), can accumulate in molten salt reactors (MSRs) and influence system performance and safety through deposition. Upon generation in fission, noble metals are transported by circulating salt and may either deposit on structural surfaces or enter the circulating gas bubble interfaces. While sparging was primarily designed for xenon and krypton removal, the mass transfer of noble metals into bubble interfaces highlights a potential pathway for their transport and partial extraction. The properties of the liquid-gas interface therefore play an important role in noble metal deposition and removal behaviors. Observations from earlier studies suggest that noble metals accumulated at the bubble interface can act as surfactants, making the bubble interface partially immobile. This behavior reduces the mass transfer capacity of circulating bubbles and affects both the overall distribution of noble metals in the loop and their removal efficiency. To investigate the influence of surfactants on noble metal transport, deposition, and extraction behaviors in MSRs, a previously developed and validated species transport model incorporating noble metal interphase mass transfer was used to simulate these behaviors. Two designed cases were studied to predict the distribution of 132Te along the Molten Salt Reactor Experiment (MSRE) loop under different bubble interface conditions. The results show that the mass transfer coefficients at the liquid-gas interface, determined by bubble interface characteristics, significantly influence noble metal distribution within the reactor loop. These findings emphasize the importance of continuously introducing fresh circulating bubbles into the molten salt to improve the removal efficiency of insoluble FPs from the MSR primary loop.

MSR↗
DOE OSTI2025

Architecture-Aware Models of AI Engines for High-Performance Matrix Matrix Multiplication

The AI Engine (AIE) architecture, available in systems from mobile SoCs to server-class FPGAs, aims to efficiently execute AI/ML tasks through a two-dimensional array of compute tiles. Previous work on AIEs has explored different approaches to mapping computation across spatial arrays, but the compute kernel running on each tile has not been the focus. Additionally, the AIE-ML architecture introduces memory tiles and omits programmable logic, requiring new approaches to staging and moving data throughout the array. In this work we update analytical models developed for CPUs to produce the design of high performance kernels while introducing new model considerations such as memory structure, throughput, and latency as required by the AIE hardware. We evaluate our models by developing AIE-ML kernels for matrix multiplication in low-precision data types showing performance up to 95% of compute peak for the kernel when data resides in local memory and above 90% of compute peak when data resides in main memory.

Binder, Elliott D. [Carnegie Mellon University, Pi↗
DOE OSTI2026

Roadrunner

SAND2026-17073O Roadrunner software provides a comprehensive platform for simulating the mechanical behavior of crystalline materials under various loading conditions, allowing users to investigate the effects of dislocation slip hardening and damage evolution. Developed as a fork of the Multiphysics Object Oriented Simulation Environment (MOOSE) software from Idaho National Laboratory, Roadrunner is optimized for high-performance computing and can simulate large-scale problems, enabling researchers to explore complex scenarios. Its applications include material design and optimization in aerospace and automotive industries, investigation of failure mechanisms in structural materials, and development of predictive models for crystalline materials under various loading conditions. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Lim, Hojun [Sandia National Lab. (SNL-CA), Livermo↗
DOE OSTI2025

FuSED Users Manual, 5.24

The Fusion of Simulation, Experiment, and Data (FuSED) team provides a set of tools for solving inverse problems in structural dynamics and thermal physics, and also sensor placement optimization via Optimal Experimental Design (OED). These methods are used for designing experiments, model calibration, and verification/validation analysis of systems. This document provides a user’s guide to the input for the three apps that are supported for these methods. Details of input specifications, output options, and optimization parameters are included.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

The Evolving Role of Demand Charges in Retail Electricity Rates

Retail electricity demand charges refer to a type of retail rate that is based on a metric of kilowatt (kW) demand rather than kilowatt-hour (kWh) energy usage. Demand charges are widely used in the commercial and industrial (C&I) electricity sectors to recover significant portions of utility revenue and are also used in residential rates in a modest but growing number of locations. This paper explores the historical context of and motivations for demand charges, describes their implementation and impacts in today's context, and uses a variety of opinions collected from relevant parties through semi-structured interviews to inform how demand charges align with four widely accepted rate design principles. This project is funded by the Department of Energy's Office of Electricity, which is interested in conducting research to understand the current state of affairs related to demand charges and how the future U.S. electricity grid will help to define retail rates.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗