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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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424 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Fingerprinting Superconductors by Disentangling Andreev and Quasiparticle Currents Across Tunable Tunnel Junctions

Tunneling Andreev reflection (TAR) spectroscopy provides a new approach to identify superconducting pairing symmetry at the atomic scale. Using atomistic superconducting transport simulations, we reveal the mechanism by which TAR can distinguish between pairing symmetries, which is complementary to traditional conductance-based techniques. In particular, owing to the additivity of the excess tunneling decay rate, the TAR spectrum is a weighted average of the contributions from quasiparticle currents, Andreev reflection, and higher-order scattering processes, and their relative weights depend on both the superconducting order parameter and the coupling strength. Within the local tunneling model, TAR dominates mid-gap conductance for s-wave superconductors, is suppressed for d-wave, and coexists with quasiparticle tunneling in sign-changing symmetries if the expectation value for the superconducting gap remains finite. Meanwhile, higher-order processes generally enhance the TAR signal when GN exceeds approximately 0.1G0. As a result, TAR provides a rich spectral fingerprint of the underlying pairing symmetry and electronic structure, enabling atomically resolved identification of unconventional superconducting states.

Maksymovych, Petro [Clemson University]↗
DOE OSTI2026

Formation of Bimetallic Nanoparticles via Exsolution Using a Reducible Metal Oxide Capping Layer

Bimetallic nanoparticles are promising catalysts that can improve performance in heterogeneous catalysis and solid-state electrochemistry. Exsolution is a useful method for forming such nanoparticles; however, it is limited by the elements present within the host oxide lattice. Here, in this work, we develop and demonstrate a strategy to form bimetallic particles from La 0.5 Sr 0.5 Ti 0.94 Ni 0.06 O 3 (LSTN) exsolution and using a reducible SnO 2 capping layer, expanding the range of elements available for bimetallic nanoparticle formation. Using this capping layer strategy, we formed nickel–tin (Ni 0 –Sn 0 ) bimetallic nanoparticles via exsolution. We used in situ near-ambient pressure X-ray photoelectron spectroscopy to monitor surface chemical changes during exsolution, showing that first, SnO 2 volatilized. This SnO 2 loss exposed the perovskite surface of LSTN to reducing conditions, which induced Ni exsolution, and compounded with SnO 2 reduction led to the formation of bimetallic Ni 0 –Sn 0 particles. To evaluate the associated microstructural evolution, we measured grazing incidence small-angle X-ray scattering (GISAXS), which confirmed the loss of the SnO 2 capping layer, and scattering simulations suggested the formation of bimetallic particles. We confirmed the bimetallic nanoparticle composition and morphology by Auger spectroscopy and scanning transmission electron microscopy. The resulting bimetallic nanoparticles were smaller and more thermally stable than the monometallic Ni counterparts on LSTN. This capping layer and exsolution approach allow synthesizing multimetallic nanoparticles and can be applied to other reducible metal oxides and perovskite hosts, broadening the compositional space for advanced catalytic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Time-Resolved Stochastic Dynamics of Quantum Thermal Machines

Steady-state quantum thermal machines are typically characterized by a continuous flow of heat between different reservoirs. However, at the level of discrete stochastic realizations, heat flow is unraveled as a series of abrupt quantum jumps, each representing an exchange of finite quanta with the environment. Here, in this work, we present a framework that resolves the dynamics of quantum thermal machines into cycles classified as enginelike, coolinglike, or idle. We analyze the statistics of individual cycle types and their durations, enabling us to determine both the fraction of cycles useful for thermodynamic tasks and the average waiting time between cycles of a given type. Central to our analysis is the notion of intermittency, which captures the operational consistency of the machine by assessing the frequency and distribution of idle cycles. Our framework offers a novel approach to characterizing thermal machines, with significant relevance to experiments involving mesoscopic transport through quantum dots.

full counting statistics↗
DOE OSTI2023

Dual atom catalysts for rapid electrochemical reduction of CO to ethylene

Strong CO adsorption and facile CO dimerization are the key challenges in electrochemical CO2 reduction towards multi-carbon (C2+) products. We recently showed that CoPc immobilized on a single-walled carbon nanotube can selectively reduce CO2 to methanol. This is enabled through molecular strain, which dramatically improves the CO adsorption energy to CoPc, which in turn facilitates methanol formation. We now examine the extended Phthalocyanine (PcEx) dual atom catalyst (DAC), which is intrinsically strained and contains two catalyst centers, making it a candidate for reducing CO to C2+ products. Using Quantum Mechanics (QM), we screened 20 elements embedded in the PcEx, seeking catalysts with weak hydrogen binding, strong CO binding, and facile CO dimerization. We identi>ied Fe, Ru, Co, and Ir as the best performers and subsequently evaluated the entire CO to C2H4 mechanism (9 steps) using each of these elements as catalysts. In terms of limiting potential and overall exergonicity, we identi>ied CoPcEx as the best catalyst, followed by IrPcEx. We then examined the full CO to C2H4 mechanism on the bimetallic IrCoPcEx catalyst using grand canonical QM to obtain the reaction energetics as a function of applied potential. We conclude that the bimetallic IrCoPcEx is most promising for ef>iciently converting CO to ethylene.

Musgrave, Charles B.↗
DOE OSTI2024

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys

The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a novice but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting compositionally complex materials. This investigation demonstrates an active learning (AL) approach for optimizing physical vapor deposition synthesis of thin-film alloys with up to five principal elements. We compared AL-based on Gaussian process (GP) and random forest (RF) models. The best performing models were able to discover synthesis parameters for a target quinary alloy in 14 iterations. We also demonstrate the capability of these models to be used in transfer learning tasks. RF and GP models trained on lower dimensional systems (i.e., ternary, quarternary) show an immediate improvement in prediction accuracy compared to models trained only on quinary samples. Furthermore, samples that only share a few elements in common with the target composition can be used for model pre-training. We believe that such AL approaches can be widely adapted to significantly accelerate the exploration of compositionally complex materials.

Chemistry↗
DOE OSTI2025

Tensorized Interior Radiative Heat Transfer for a Scalable and Calibrated Building Energy Simulator

Building energy simulation is a critical tool for developing and testing advanced control strategies, such as Reinforcement Learning (RL), to provide demand flexibility and affordable energy costs. The recently introduced Smart Buildings Control Suite (sbsim) provides a lightweight, scalable, and data-calibrated simulation environment based on a 2D finite-difference model. However, the initial model primarily focused on conductive and convective heat transfer, neglecting the significant impact of long-wave radiative heat exchange between interior surfaces. This paper presents a significant extension to the sbsim framework by incorporating a physically-grounded model for interior radiative heat transfer. Our primary contribution is the development and integration of a fully tensorized radiative heat transfer module, which preserves the computational efficiency and scalability of the original simulator. This was achieved by developing a pipeline for view factor calculation, including an algorithm to identify directly seeing surfaces within complex floor plans, and formulating the net radiation equations for efficient execution on modern hardware accelerators. We validate the numerical accuracy of our tensorized implementation by comparing its results against a traditional iterative approach, demonstrating identical outcomes. This enhancement increases the physical fidelity of sbsim, enabling more accurate training of RL agents for building energy optimization.

Ham, Sang woo↗
DOE OSTI2025

A quality-agnostic combinatoric cost estimation model for large-format directed energy deposition metal additive manufacturing

Directed energy deposition (DED) additive manufacturing (AM) processes are amenable to synergistic combination into multi-process AM systems due to similar requirements for automation and energy sources. This work analyzes the economic performance of such DED AM systems from a quality-agnostic combinatoric standpoint with a model that calculates lowest-cost system combinations based on part geometry and process performance metrics. Common DED AM systems research focuses on a single process and does not consider the process, system, and application in the context of all possible system combinations (e.g., the combined set of process selection(s), motion system(s), and process hardware), leading to limited applicability of the resulting DED AM systems to cost-sensitive components such as those found in energy generation applications. The model developed herein incorporates the capital, material, and energy costs associated with DED AM system combinations into a predictive tool for estimating part and system cost, the output of which is intended to guide deployment of finite research and development resources towards DED AM system combinations with the lowest costs and greatest likelihood of economic impact. The DED AM systems identified by this framework may enable domestic production of the large conventionally cast and forged components necessary for energy generation.

Shanafield, Alexandra [ORNL]↗
DOE OSTI2024

Method for implant and anneal for high voltage field effect transistors

In an example, the present invention provides a method of forming a semiconductor device on a gallium and nitrogen containing material. The method includes providing a substrate member comprising a surface region, the substrate member comprising a gallium and nitrogen bearing material. The method includes causing an implanted species to electrically activate the implant profile while removing one or more crystalline damage from the epitaxial material to change the amorphous state to a single crystalline state, and thereby creating a substantially electrically activated crystalline material.

Shealy, James R.↗
DOE OSTI1968

Kryptonate Hydrogen Detection System (Final Report)

A prototype model of a multipurpose instrument which demonstrates the applicability of the Kryptonate® technique for detecting hydrogen gas was developed. This report describes the construction of the instrument and presents a laboratory evaluation of its performance. Performance was excellent. The instrument was designed to detect hydrogen in air at concentrations of 0-3% by volume, and to detect hydrogen in nitrogen or other inert gas at concentrations of 0-10% by volume. Other detection levels (both higher and lower) could be set if required. Ultimate response times can be made of the order of 0.5 seconds. The instrument is an all solid state device operating from 120V 60 Hz power source. The instrument has been designed to enable modifications to be made with a minimum amount of difficulty.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Ferrimagnetism of ultracold fermions in a multiband Hubbard system

Strongly correlated materials feature multiple electronic orbitals, which are crucial to accurately understanding their many-body properties. In such multiband models, quantum interference can lead to flat energy bands with large degeneracy that gives rise to itinerant magnetic phases. Here, we report on signatures of a ferrimagnetic state realized in a Lieb lattice with ultracold fermions, characterized by antialigned magnetic moments with antiferromagnetic correlations, and concomitant with a finite spin polarization. The signatures remain robust when increasing repulsive interactions from the weakly interacting to the Heisenberg regime and emerge when continuously tuning the lattice unit cell from a square to a Lieb geometry. Our flexible approach paves the way toward exploring exotic phases, such as quantum spin liquids in kagome lattices and heavy fermion behavior in Kondo models.

Lebrat, Martin [Harvard Univ., Cambridge, MA (Unit↗
DOE OSTI2024

Method of making thin films of sodium fluorides and their derivatives by ALD

A method of making thin films of sodium fluorides and their derivatives by atomic layer deposition (“ALD”). A sodium precursor is exposed to a substrate in an ALD reactor. The sodium precursor is purged, leaving the substrate with a sodium intermediate bound thereon. A fluorine precursor is exposed to the bound sodium intermediate in the ALD reactor. The fluorine precursor is purged and a sodium fluoride film is formed on the substrate.

Mane, Anil U.↗
DOE OSTI2026

Understanding Discharge‐Driven Growth of Cathode Impedance in Ni‐Rich NMC Cathodes

Degradation of LiNi x Mn y Co 1-x-y O 2 (NMC)-based lithium-ion batteries depends strongly on cut-off voltage ranges. In addition to the high upper cut-off voltage, a high depth of discharge (i.e., lower cut-off voltage) significantly worsens cathode impedance growth and capacity fade during long-term cycling. However, there is currently no consensus on the mechanism behind the negative role of a deep discharge. Here, this phenomenon was investigated in graphite||NMC cells with single-crystal cathodes (LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NMC622) or LiNi 0.76 Co 0.14 Mn 0.10 O 2 (NMC76)) using targeted aging protocols (constant high-voltage holds vs. charge–discharge cycling), while monitoring transition-metal (TM) dissolution, cathode-electrolyte interface (CEI) impedance, and NMC surface composition. We demonstrate a correlation between discharge-driven CEI impedance growth and increased TM dissolution. Furthermore, this degradation pathway is more pronounced in lower-Ni NMC622 than in higher-Ni (NMC76) under comparable delithiation states at charge, with both compositions undergoing the H2→H3 phase transition. X-ray photoelectron spectroscopy (XPS) reveals NMC composition-dependent evolution of surface lattice oxygen and restructured surface layer composition between charged and discharged states. These findings add mechanistic depth to the role of discharge as an active driver of interfacial degradation and provide new insights into its composition dependence.

25 ENERGY STORAGE↗
DOE OSTI2025

Methods and recommendations for large-scale deflagration testing of battery energy storage system enclosures

UL Solutions produced this report as a summary of a test series executed at Sandia National Laboratories that they funded. This report was approved for release by UL Solutions in October 2025 and released in 2026 on their website at https://www.ul.com/insights/methods-and-recommendations-large-scale-deflagration-testing-battery-energy-storage-system.

Gaudet, Benjamin [UL Solutions] (ORCID:00090006419↗