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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 145 records · Page 8

Bridging paradigms: Designing for HPC-Quantum convergence

Here, this paper presents a comprehensive software stack architecture for integrating quantum computing (QC) capabilities with High-Performance Computing (HPC) environments. While quantum computers show promise as specialized accelerators for scientific computing, their effective integration with classical HPC systems presents significant technical challenges. We propose a hardware-agnostic software framework that supports both current noisy intermediate-scale quantum devices and future fault-tolerant quantum computers, while maintaining compatibility with existing HPC workflows. The architecture includes a quantum gateway interface, standardized APIs for resource management, and robust scheduling mechanisms to handle both simultaneous and interleaved quantum–classical workloads. Key innovations include: (1) a unified resource management system that efficiently coordinates quantum and classical resources, (2) a flexible quantum programming interface that abstracts hardware-specific details, (3) A Quantum Platform Manager API that simplifies the integration of various quantum hardware systems, and (4) a comprehensive tool chain for quantum circuit optimization and execution. We demonstrate our architecture through implementation of quantum–classical algorithms, including the variational quantum linear solver, showcasing the framework’s ability to handle complex hybrid workflows while maximizing resource utilization. This work provides a foundational blueprint for integrating QC capabilities into existing HPC infrastructures, addressing critical challenges in resource management, job scheduling, and efficient data movement between classical and quantum resources.

97 MATHEMATICS AND COMPUTING↗

BIL High Speed Fuel Cell Stack Manufacturing

General Motors LLC (GM) was awarded a project to develop and implement technologies for manufacturing 20,000 units of Fuel Cell Stacks per year on two shifts per day basis. GM leveraged prior in-house expertise in designing the Fuel Cells, deploying the manufacturing process steps in the laboratory environment as well as the deployment in the industrial environment on a smaller scale. The project focus was to design, build, and deploy a manufacturing line consisting of an anode and cathode electrode processing, unitized electrode assembly, fuel cell stacking, compression, testing, and final assembly of the fuel cell stack. The project was terminated in the first budget period.

08 HYDROGEN↗

Membrane Electrode Assembly Manufacturing Automation Technology for the Electrochemical Compression of Hydrogen: Cooperative Research and Development (Final Report)

Electrochemical compression has the possibility to outcompete mechanical compression for hydrogen end- use applications. While HyET has a compressor that can output JO kilograms (kg)/day (fully scalable from home-to-industrial application) at up to 700 bar, the energy demand and reliability require top-quality electrochemical hydrogen compression (EHC) membrane electrode assemblies (MEAs), preferably prepared by cost-effective high-capacity manufacturing. High pressure requires a special MEA design, deviating from typical proton exchange membrane fuel cell (PEMFC) MEAs with adapted catalyst layer substrates, asking for a modified coating process. The National Renewable Energy Laboratory (NREL) will help HyET by developing an automated catalyst coating process fit for EHC MEA manufacturing. In addition, inline quality inspection methods will be developed/selected to improve the MBA quality as it is used for EHC stack assembly. In a joint effort, NREL and HyET will even design an automated manufacturing process for the EHC MEA and approach potential United States (US) suppliers of manufacturing equipment.

30 DIRECT ENERGY CONVERSION↗

Linac to BAR/RCS transfer line design for EIC electron injection system

A transfer line has been designed for the Electron-Ion Collider (EIC) to transport electron bunches from the linac to the Rapid Cycling Synchrotron (RCS). In its initial operational stage, the line accommodates 1 nC electron bunches directly from the linac. To support a future upgrade involving a Beam Accumulator Ring (BAR), which will stack individual bunches to form high-charge 28 nC bunches, the design incorporates two switching dipoles enabling injection into and extraction from the BAR. Additionally, a beam dump has been included for operational flexibility and safety. The final segment of the line interfaces with the RCS through a modified Penner bend, preserving beam quality while satisfying geometric constraints. This layout ensures compatibility with both current and future operational modes of the EIC injection system.

Accelerator Physics↗

Redox Activity Modulation in Extended Fluorenone-Based Flow Battery Electrolytes with π-π Stacking Effect

Redox flow battery shows promise for grid-scale energy storage. Aqueous organic redox flow batteries are particularly popular due to their potentially low material cost and safe water-based electrolyte. Commonly, redox active molecules used in this field feature aromatic rings, and increasing π-aromatic conjugation has been a popular strategy to achieve high energy density, high power density, and reduced crossover in new material design. However, this approach can inadvertently hinder redox activity depending on redox mechanism. This study reveals the underlying π-π stacking effect in extended aromatic redox active compounds, where aromatic radical intermediates are involved in the redox process. We report a molecular design strategy to mitigate the negative effect of π-π stacking by altering solvation dynamics and introducing molecular steric hindrance.

25 ENERGY STORAGE↗

Bipolar plate flow channel designs for vanadium redox flow battery: a review

Vanadium redox flow battery is one of the preferred systems for grid scale energy storage due to long service life (>20000 cycles), higher efficiency (>85 %), deep discharge capability (>95 % DoD), and inherent scalability and safety. Among system components, flow field is most critical as it governs electrolyte distribution, mass transport and hydraulic performance. Here, this review examines emerging flow channel geometries, highlighting the impact of channel width (0.66 to 1.5 mm), depth (1 to 1.5 mm) and land width (0.5 to 1.5 mm) can reduce pressure drop to <10 kPa while enabling power densities above 600 mW.cm -2 . A key finding is that low channel width to depth ratio (<1) enhances voltage and energy efficiencies by improving under rib convection. The review also provides an overview of progress and perspective in bipolar plate materials, manufacturability, and shunt current mitigation strategies for stack scaling up. Cost analysis emphasizes the influence of flow field designs on the levelized cost of storage and pathways towards the US DOE's $\$$0.05 per kWh energy generation cost target. In addition, opportunities for AI/ML/DT tools assisted design and data driven optimization strategies are also outlined to accelerate next generation flow field development.

Efficiency optimization↗

Parametric dynamic mode decomposition for reduced order modeling

Dynamic Mode Decomposition (DMD) is a model-order reduction approach, whereby spatial modes of fixed temporal frequencies are extracted from numerical or experimental data sets. The DMD low-rank or reduced operator is typically obtained by singular value decomposition of the temporal data sets. For parameter-dependent models, as found in many multi-query applications such as uncertainty quantification or design optimization, the only parametric DMD technique developed was a stacked approach, with data sets at multiple parameter values were aggregated together, increasing the computational work needed to devise low-rank dynamical reduced-order models. Here in this paper, we present two novel approach to carry out parametric DMD: one based on the interpolation of the reduced-order DMD eigen-pair and the other based on the interpolation of the reduced DMD (Koopman) operator. Numerical results are presented for diffusion-dominated nonlinear dynamical problems, including a multiphysics radiative transfer example. All three parametric DMD approaches are compared.

97 MATHEMATICS AND COMPUTING↗

CO2 Handling & Electrolyzer Efficiency Scaling Evaluator

CHEESE is an interactive dashboard tool for estimating the performance and material requirements of carbon dioxide electrolysis systems. It helps users evaluate how electrode area, current density, product selectivity, gas flow, cell voltage, and the number of cells in a stack affect system operation. The dashboard provides simple and advanced modes so it can be used for both quick estimates and more detailed engineering analysis. Users can estimate product output, carbon dioxide use, electrical power, electrode area, gas and liquid flow rates, energy efficiency, material cost per test, and the effect of scaling from a single cell to a multi cell stack. It also includes tools for examining carbon balance, equipment durability, component replacement, and changes in performance over time. This is intended to help both academia and industry researchers who are either getting into CO2 electrolysis on lab-scale or are trying to establish a larger footprint. CHEESE presents results through tables, charts, and simplified cell and stack diagrams. It is intended to support research planning, experimental design, comparison of operating conditions, and early stage scale up studies.

Prajapati, Aditya [Lawrence Livermore National Lab↗

Towards stacking fault energy engineering in FCC high entropy alloys

Stacking Fault Energy (SFE) is an intrinsic alloy property that governs much of the plastic deformation mechanisms observed in fcc alloys. While SFE has been recognized for many years as a key intrinsic mechanical property, its inference via experimental observations or prediction using, for example, computationally intensive first-principles methods is challenging. This difficulty precludes the explicit use of SFE as an alloy design parameter. In this work, we combine DFT calculations (with necessary configurational averaging), machine-learning (ML) and physics-based models to predict the SFE in the fcc CoCrFeMnNiV-Al high-entropy alloy space. The best-performing ML model is capable of accurately predicting the SFE of arbitrary compositions within this 7-element system. Finally, this efficient model along with a recently developed model to estimate intrinsic strength of fcc HEAs is used to explore the strength–SFE Pareto front, predicting new-candidate alloys with particularly interesting mechanical behavior.

36 MATERIALS SCIENCE↗

Reimagining Codesign for Advanced Scientific Computing: Report for the ASCR Workshop on Reimagining Codesign

In March 2021, the U.S. Department of Energy’s Advanced Scientific Computing Research program convened the Workshop on Reimagining Codesign. The workshop, also known as ReCoDe, was organized around discussions on eight topic areas: (1) codesign for traditional high-performance computing workloads; (2) codesign of memory/storage systems; (3) codesign of machine learning, neuromorphic, quantum, and other non-von Neumann accelerators; (4) codesign for edge computing and processing at experimental instruments; (5) codesign for security and privacy; (6) hardware design tools and open-source hardware for high-productivity codesign; (7) tools, software stack, and programming languages for high-productivity codesign; and (8) quantitative tools and data collection for modeling and simulation for codesign. The panels identified four Priority Research Directions from these deliberations: (1) breakthrough computing capabilities with targeted heterogeneity and rapid design; (2) software and applications that embrace radical architecture diversity; (3) engineered security and integrity, from transistors to applications; and (4) design with data-rich processes.

97 MATHEMATICS AND COMPUTING↗

Dry etching of epitaxial InGaAs/InAlAs/InAlGaAs structures for fabrication of photonic integrated circuits

A dry etching process to transfer the pattern of a photonic integrated circuit design for high-speed laser communications is described. The laser stack under consideration is a 3.2-µm-thick InGaAs/InAlAs/InAlGaAs epitaxial structure grown by molecular beam epitaxy. The etching was performed using Cl2-based inductively-coupled-plasma and reactive-ion-etching (ICP-RIE) reactors. Four different recipes are presented in two similar ICP-RIE reactors, with special attention paid to the etched features formed with various hard mask compositions, in-situ passivations, and process temperatures. The results indicate that it is possible to produce high-aspect-ratio features with sub-micron separation on this multilayer structure. Additionally, the results of the etching highlight the tradeoffs involved with the corresponding recipes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A cryogenic muon tagging system based on kinetic inductance detectors for superconducting quantum processors

Ionizing radiation has emerged as a potential limiting factor for superconducting quantum processors, inducing quasiparticle bursts and correlated errors that challenge fault-tolerant operation. Atmospheric muons are particularly problematic due to their high energy and penetration power, making passive shielding ineffective. Therefore, monitoring the real-time muon flux is crucial to guide the development of alternative error-correction or mitigation strategies. We present the design, simulation, and first operation of a cryogenic muon-tagging system based on kinetic inductance detectors (KIDs), developed as a stand-alone cryogenic particle-tagging module for superconducting quantum processors. The system consists of two KIDs arranged in a vertical stack and operated at ∼20 mK. Monte Carlo simulations based on Geant4 guided the prototype design and provided reference expectations for muon-tagging efficiency and accidental coincidences due to ambient γ-rays. We observed a muon-induced coincidence rate among the top and bottom detectors of (192 ± 9) $\times\,10^{-3}$ events s$^{−1}$, in excellent agreement with the Monte Carlo prediction. The prototype achieves a muon-tagging efficiency of about 90% with negligible dead time. These results demonstrate the feasibility of operating a muon-tagging system at millikelvin temperatures and represent a key step toward the integration of cryogenic veto systems with multi-qubit chips to mitigate muon-induced errors.

Mariani, Ambra [INFN, Rome] (ORCID:000000028184857↗

Neural network interatomic potential-driven analysis of phase stability in Ti–V alloys at the atomistic scale

The evolution of the ω phase in titanium–vanadium (Ti–V) alloys is critical for their mechanical properties, particularly in aerospace and biomedical applications. Here, this study employs a Rapid Artificial Neural Network (RANN) potential to model the ω phase evolution at the atomistic level, demonstrating a high degree of consistency with experimental observations, unlike the Modified Embedded Atom Method (MEAM), which fails to capture this phase transformation accurately. RANN simulations replicate key phenomena such as the nucleation of α precipitates at ω/β interfaces and accurate lattice orientations, enhancing our understanding of phase stability and transformation kinetics. The findings affirm that RANN potentials can significantly improve the prediction accuracy of complex material behaviors, offering a powerful tool for designing advanced materials with tailored properties such as solute effect in various stacking fault energies. This approach not only bridges the gap between theoretical predictions and empirical data but also sets a new direction for future research in materials science, emphasizing the integration of machine learning techniques in the development and optimization of new alloys.

36 MATERIALS SCIENCE↗

Pressure Heterogeneity and Material Utilization in Thin-Film Solid-State Cathodes

Intimate interfacial contact between the solid electrolyte and the cathode active material is critical for maximizing cathode utilization in solid-state batteries. However, volume changes during electrochemical cycling induce internal stresses that drive interfacial degradation, particularly under nonuniform stack pressure. In this study, we employ in situ energy-dispersive X-ray diffraction tomography to visualize and quantify reaction heterogeneities across a 3 mm-diameter solid-state cathode with a well-defined interface. Our results reveal that regions under a lower stack pressure exhibit reduced material utilization and reversibility, which negatively affect the high-pressure regions. Interfacial degradation further impedes lithium-ion transport and amplifies microscale reaction heterogeneity. These findings highlight the critical role of stack pressure distribution in governing interfacial stability and electrochemical performance, offering important design insights into practical solid-state battery systems.

36 MATERIALS SCIENCE↗

Entanglement of Square Nets in Covalent Organic Frameworks

Herein, two entangled 2D square covalent organic frameworks (COFs) have been synthesized from 4,4',4'',4'''-(9,9'-spirobi[fluorene]-2,2',7,7'-tetrayl)-tetrabenzaldehhyde (SFTB) and p -phenylenediamine (PPA) and benzidine (BZD) to form COF-38, [(SFTB)(PPA) 2 ] imine , and its isoreticular form COF-39, [(SFTB)(BZD) 2 ] imine . We also report the single-crystal electron diffraction structure of COF-39 and find that it is composed of mutually entangled 2D square nets ( sql ). These COFs represent the first examples of entangled 2D COF structures, which, as we illustrate, were made possible by our strategy of using the distorted tetrahedral SFTB building unit. SFTB overcomes the propensity of 2D COFs to stack through π-π stacking and allows entanglements to form. This work significantly adds to the design principles of COFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Creating superconductivity in WB 2 through pressure-induced metastable planar defects

High-pressure electrical resistivity measurements reveal that the mechanical deformation of ultra-hard WB 2 during compression induces superconductivity above 50 GPa with a maximum superconducting critical temperature, T c of 17 K at 91 GPa. Upon further compression up to 187 GPa, the T c gradually decreases. Theoretical calculations show that electron-phonon mediated superconductivity originates from the formation of metastable stacking faults and twin boundaries that exhibit a local structure resembling MgB 2 (hP3, space group 191, prototype AlB 2 ). Synchrotron x-ray diffraction measurements up to 145 GPa show that the ambient pressure hP12 structure (space group 194, prototype WB 2 ) continues to persist to this pressure, consistent with the formation of the planar defects above 50 GPa. The abrupt appearance of superconductivity under pressure does not coincide with a structural transition but instead with the formation and percolation of mechanically-induced stacking faults and twin boundaries. The results identify an alternate route for designing superconducting materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A bistable and reconfigurable molecular system with encodable bonds

Molecular systems with ability to controllably transform between different conformations play pivotal roles in regulating biochemical functions. Here, we report the design of a bistable DNA origami four-way junction (DOJ) molecular system that adopts two distinct stable conformations with controllable reconfigurability by using conformation-controlled base stacking. Exquisite control over DOJ’s conformation and transformation is realized by programming the stacking bonds (quasi–blunt-ends) within the junction to induce prescribed coaxial stacking of neighboring junction arms. A specific DOJ conformation may be achieved by encoding the stacking bonds with binary stacking sequences based on thermodynamic calculations. Dynamic transformations of DOJ between various conformations are achieved by using specific environmental and molecular stimulations to reprogram the stacking codes. This work provides a useful platform for constructing self-assembled DNA nanostructures and nanomachines and insights for future design of artificial molecular systems with increasing complexity and reconfigurability.

60 APPLIED LIFE SCIENCES↗

Electrochemically driven carbon dioxide separation

This project explored the viability of a Ni(OH) 2 based hydroxide exchange membrane carbon capture (HEMCC) device for direct air capture. It is built off an H 2 fuel cell based HEMCC previously developed in the Yushan Yan group at University of Delaware. Taking the same membrane-based, electrochemically driven pH gradient concept, similar flux performance was able to be seen in the Ni(OH) 2 system as the H 2 system when using comparable current densities. The project produced two types of membrane electrode assemblies (MEA). The first was a traditional MEA with two electrodes and a membrane, the second was a flow-through membrane MEA. Consistent performance was achieved with the traditional MEA with an energy cost of 1.1 MWh∙ton -1 and flux of 82 kg∙m -2 ∙yr -1 . This was the most stable of the two designs. This project investigated strategies to improve performance with a flow-through membrane design. Two designs were made, one with a cast phase inversion membrane, and one with powdered membrane layer. The template phase inversion membrane achieved low pressure drop but had performance limitations due to a skin layer of membrane limiting CO 2 gas transport. The powdered membrane layer had better performance but higher pressure drop. Finally, using the powdered membrane, commercial battery materials were able to be used in order to achieve higher flux. This showed that the flow through membrane design does have the capability to overcome flux inefficiencies in the traditional MEA. Moreover, the process design of the system is proposed and given in this project. The process mass and energy balances were calculated for a reference plant of 1000 t/yr CO 2 capture, which contains several subsystems, e.g. air processing subsystem, electrical subsystem, and CO 2 purification and compression subsystem is designed and evaluated. Based on our calculation, When the power consumption for stack is 1 MWh t -1 CO 2 , Additional 382 kWh t -1 CO 2 will be consumed by other subsystem of the plant, i.e. The total power consumption of 1.38 MWh t -1 CO 2 , lower than the final milestone of 1.5 MWh t -1 CO 2 in this project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗