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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 199 records · Page 11

Thermal property characterization of phase change materials in building applications: A systematic review of fundamentals, recent progress, and future directions

Phase change materials (PCMs) can reduce building peak loads and enable demand-responsive thermal energy storage (TES), but their deployment depends on reliable measurement and interpretation of thermal properties across laboratory, intermediate, and application scales. Here, this review systematically examines characterization methods, testing protocols, and recent advances for neat PCMs and PCM composites, emphasizing thermal conductivity, enthalpy-related properties (phase change temperature, latent heat, specific heat), and cycling stability. For thermal conductivity, we compare steady-state and transient techniques and note limitations when phase transition and contact resistance affect measurements. For enthalpy–temperature characterization, we discuss differential scanning calorimetry together with intermediate- and bulk-scale methods, including T-history, heat flow meter testing, and three-layer calorimetry (3LC), to generate application-relevant enthalpy–temperature profiles. Cycling stability is organized into four experimental families: thermoelectric–air, fully thermoelectric, water-bath, and in situ chamber approaches, with attention to separating reversible supercooling from true degradation such as phase segregation. We highlight emerging noncontact diagnostics, including infrared thermography and embedded sensing, for spatially resolved validation and multiscale interpretation. Finally, we review the growing use of AI and machine learning for property prediction, inverse characterization from experimental signals, and real-time state estimation in building-integrated TES. Key needs include harmonized protocols, interlaboratory benchmarking, uncertainty reporting, and metadata-rich datasets to accelerate reproducible PCM qualification for grid-flexible buildings.

AI↗

Influence of Pt-Metal Alloy Catalysts with Various Ionomers on Oxygen Reduction Reaction in Fuel Cell Application

Pt-M/C (M = Co, Ni, Mn, etc.) alloy catalysts exhibit superior oxygen reduction reaction (ORR) activity compared to pure Pt/C, leading to a high energy efficiency in hydrogen fuel cells. However, many Pt-M/C alloy catalysts were synthesized and evaluated at the lab scale in model test-bed systems like rotating disc electrodes, which don't always correlate to performance within a fuel cell system; there is a clear need to evaluate catalysts in electrodes that can be prepared at industrially relevant scales to evaluate how factors like ink formulation can greatly affect device-level of fuel cell performance. Herein, three commercial Pt-M/C alloy catalysts (two Pt-Co/C and one Pt-Ni/C) were comprehensively characterized by various techniques. The results show that the average particle sizes of the three catalysts are close to 5 nm; the atomic ratio of Pt/M is around 4; and the M was successfully embedded into Pt lattice, resulting in the positive shift of Pt 4f in XPS spectra and XRD patterns. These catalytic materials were incorporated into 9 different cathode catalyst layers (CCLs) with three kinds of ionomers (Nafion D2020, high oxygen permeability ionomer (HOPI), and Aquivion D79-25BS), and their performance in proton exchange membrane fuel cells (PEMFCs) were investigated. The results demonstrate that the Pt-Co/C catalysts possess a higher mass activity (MA) than Pt-Ni/C; the cathodes with Nafion ionomer provide the highest MA while electrodes with Aquivion ionomer showed the lowest activity, attributed to poor H+ conductivity resulting from suboptimal ionomer incorporation. Finally, these alloys were shown to exceed DOE targets for MA and H2/Air performance reported in the recent publications at beginning of life and after 90k cycle catalyst AST protocol. This study provides valuable performance benchmarks for these materials guiding future Pt-M/C catalyst design and material integration for heavy duty PEMFC applications.

08 HYDROGEN↗

Aligning lithium metal battery research and development across academia and industry

Successful integration of metallic lithium anodes into secondary batteries could enhance energy density and enable new forms of electrified transportation. However, the outlook for widespread lithium metal adoption in energy storage devices remains mixed. This comes in part from existing gaps in our understanding of the relationships connecting the initial state of lithium, its evolution with cycling, and end-of-life state. It remains important to develop standardized protocols for material and cell characterization, cycling performance, safety, and recycling procedures for lithium metal-based batteries. In February 2023 a cohort of scientists and engineers from academia, national laboratories, and industry gathered to converge on a list of critical challenges and action items to provide better understanding of lithium metal evolution and to enhance academic, governmental, and industrial partnerships to address these challenges. Here, we highlight the major discussion topics revolving around the manufacturing of lithium metal, its related metrology and integration into battery form factors, and best practices testing its electrochemical performance relevant to automotive applications. We introduce a power-controlled discharge testing protocol for research and development cells, in alignment between major automotive stakeholders, that may reveal lithium metal battery dynamics closer to practical driving behavior.

25 ENERGY STORAGE↗

Driven Majorana modes: A route to synthetic $p_x +ip_y$ superconductivity

We propose a protocol to realize synthetic $p_x +ip_y$ superconductors in one-dimensional topological systems that host Majorana fermions. By periodically driving a localized Majorana mode across the system, our protocol realizes a topological pumping of Majorana fermions, analogous to the adiabatic Thouless pumping of electrical charges. Importantly, similar to the realization of a Chern insulator through Thouless pumping, we show that pumping of Majorana zero modes could lead to a $p_x +ip_y$ superconductor in the two dimensions of space and synthetic time. The Floquet theory is employed to map the driven one-dimensional system to a two-dimensional synthetic system by considering frequency as a new dimension. We demonstrate such Floquet $p_x +ip_y$ superconductors using the Kitaev $p$-wave superconductor chain, a prototypical 1D topological system, as well as its more realistic realization in the 1D Kondo lattice model as examples. We further show the appearance of Majorana $π$ mode at the Floquet zone boundary in an intermediate drive frequency region. Our work suggests a driven magnetic spiral coupled to a superconductor as a promising platform for the realization of novel topological superconductors.

36 MATERIALS SCIENCE↗

Hybrid classical-quantum communication networks

Over the past several decades, the proliferation of global classical communication networks has transformed various facets of human society. Concurrently, quantum networking has emerged as a dynamic field of research, driven by its potential applications in distributed quantum computing, quantum sensor networks, and secure communications. This prompts a fundamental question: rather than constructing quantum networks from scratch, can we harness the widely available classical fiber-optic infrastructure to establish hybrid quantum–classical networks? This paper aims to provide a comprehensive review of ongoing research endeavors aimed at integrating quantum communication protocols, such as quantum key distribution, into existing lightwave networks. This approach offers the substantial advantage of reducing implementation costs by allowing classical and quantum communication protocols to share optical fibers, communication hardware, and other network control resources—arguably the most pragmatic solution in the near term. In the long run, classical communication will also reap the rewards of innovative quantum communication technologies, such as quantum memories and repeaters. Accordingly, our vision for the future of the Internet is that of heterogeneous communication networks thoughtfully designed for the seamless support of both classical and quantum communications.

Fiber-optic communication↗

Synthesis of Perdeuterated Alkyl Amines/Amides with Pt/C as Catalyst under Mild Conditions

A convenient method for the synthesis of perdeuterated alkyl amides/amines is disclosed. Perdeuterated acetyl amides can be achieved by a hydrogen–deuterium (H/D) exchange protocol with Pt/C as a catalyst and D 2 O as a deuterium source under mild conditions. Further, after removal or reduction of the acetyl group, this protocol can provide perdeuterated primary, secondary, and tertiary amines, which are difficult to achieve via other methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surprising Relationship between Silicon Anode Calendar Aging and Electrolyte Components in a Localized High-Concentration Electrolyte System

Although localized high-concentration electrolytes (LHCEs) have been shown to improve the calendar lifetime of silicon anodes, the roles of the electrolyte constituents in calendar aging are not well understood. Here, in this work, we utilize a voltage hold protocol and an LHCE with varying molar ratios of lithium bis(fluorosulfonyl)imide (LiFSI), tetramethylene sulfone (TMS), and 1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropyl ether (TTE) to probe the component roles during aging. Interestingly, the estimated calendar lifetime and irreversible lithium losses from the V-hold experiments are independent of the electrolyte formulations. Contrarily, the solid electrolyte interphase (SEI) composition depends on the electrolyte formulation. X-ray photoelectron spectroscopy shows that TMS-coordinated species decompose to form insoluble alkanes and lithium hydroxide (LiOH), while lithium fluoride (LiF) originates from the anion-coordination complex. The SEI composition does not appear to play a significant role in the silicon anode passivity, as measured by parasitic current, suggesting that the SEI-electrolyte interactions dictate the calendar aging mechanisms.

Si anode↗

Cooperative Role of Mixed Solvent in the Evaporation-Induced Self-Assembly of Polypeptoid Nanocrystals

Peptoids, or polypeptoids, are biomimetic polymers that can self-assemble into nanocrystals for biomedical and biotechnological applications. Polypeptoid nanocrystals can be prepared by evaporation-induced self-assembly, but the roles of solvent components for this process have long been overlooked at the molecular level, leaving a tunable parameter for improving self-assembly protocols. This work utilized molecular dynamics simulations to study the effects of water and the commonly used tetrahydrofuran (THF) on the assembly of nanosheets from molecules of acetylated diblock polypeptoid, poly-(N-decylglycine)-b-poly-(N-2-(2-(2-methoxyethoxy)-ethoxy) ethylglycine), abbreviated as Ac-Ndc10-Nte10. To probe the stages of self-assembly, isolated molecules and preassembled nanofibers/nanosheets were simulated in pure THF, water, and their mixtures, respectively. The assembly energies show that the THF/water mixture has a greater tendency to form nanosheets than pure water. In a THF/water mixture, polypeptoids were found more uncoiled in isolated states, less compact in disordered agglomerates, and with reduced requirement for the Nte block to cover hydrophobic Ndc surfaces in the nanocrystals. Mixed solvent is vital to initiating self-assembly, as THF assists in the opening of coiled polypeptoid molecules, while water provides the thermodynamics to aggregate and ultimately form nanocrystals. To obtain wider nanosheets, it is recommended that some THF be maintained in the aqueous solvent before it becomes exhausted by evaporation. Near the nanosheet surface, the THF concentration is higher than that in bulk solution (3-4 times in 4 M THF/water). The strong adsorption of THF indicates the self-assembly in a de facto mixed solvent. These results are expected to guide the refinement of evaporation-induced self-assembly protocols for polypeptoid nanocrystals.

Luo, Xubo↗

Low-Rate Cycling Regeneration Sustains NMC811–Graphite Battery Performance through Extreme Ultrafast Charging

Urban air mobility (UAM) systems, such as electric vertical takeoff and landing (eVTOL) aircraft, require batteries capable of extreme ultrafast charging to support high-frequency operations. Here, in this work, we evaluate the electrochemical stability of NMC811–graphite full cells using a complex mixed-modal protocol designed to simulate the aggressive turnaround demands of UAM missions. We demonstrate that incorporating a periodic low-rate (0.3C) “regeneration” cycle enables cells to maintain 96% capacity retention over 900 cycles, despite repeated exposure to ultrafast pulses. To validate the efficacy of this regeneration mechanism, we performed simplified control experiments comparing continuous 10C charging against a 10C–0.3C interleaved protocol. Advanced characterization reveals that while mechanical particle fracture is pervasive at these rates, the regeneration cycles decelerate the electrochemical degradation by resolving spatially heterogeneous Ni oxidation states and relaxing lithium-ion concentration gradients. These findings provide a vital mechanistic framework for battery operation, proving that restorative charging can effectively delay and mitigate failure in demanding UAM applications.

batteries↗

Carbamoylation as an Effective Tool in the Analysis of the Soman Nerve Agent Marker Pinacolyl Alcohol in Soil Matrices by EI-GC-MS and LC-HRMS

Pinacolyl alcohol (PA) is a Schedule 2 chemical commonly featured in most proficiency tests (PTs) administered by the Organisation for the Prohibition of Chemical Weapons (OPCW) due to its direct as well as forensic link to the nerve agent Soman. Therefore, its detection by Chemical Weapons Convention (CWC) inspection teams during on-site investigations is a strong indicator of the past or latent presence of Soman in the environment. Its small molecular weight (102), early elution time, and poor ionization profile make PA a challenging analyte to detect particularly at low concentrations (∼1–10 μg/g). In this work, 1,1′-carbonyldimidazole (CDI) has been used to effectively modify PA for the first time in two different soil matrices (Virginia type A soil and silt sediment) at two separate concentrations (1 and 10 μg/g) for its subsequent detection by EI-GC-MS and LC-HRMS methods. For the EI-GC-MS analysis, the PA carbamate derivative (PIC) exhibits improved chromatography relative to PA such as improved peak shape, increased molecular weight (196 for PIC and 102 for PA) and increased retention time (16.9 min for PIC and ∼4.1 min for PA). In addition, the derivatization also improves the detection of PA by LC-HRMS as the PIC product possesses protonation sites (i.e., imidazole ring) relative to none exhibited by PA. More importantly, the carbamoylation proceeds under mild conditions (55 °C, no base) and rapidly (3 h), characteristics that make it an appealing protocol for the analysis of PA during OPCW PTs or real case scenarios particularly in instances where it is present at low concentrations. It is anticipated that the protocol can be applied to the forensic analysis of this important Soman marker in various environmental matrices.

Chemistry↗

Reliable p K a Prediction through Efficient Incorporation of Anharmonicity within the Nuclear–Electronic Orbital Framework

Accurate pK a prediction is critical for understanding chemical reactivity and molecular properties across a wide range of applications. Computational approaches usually invoke a harmonic treatment of the vibrational modes for zero-point energies, as well as thermal and entropic contributions. Herein, we present a general protocol for relative pK a prediction that incorporates the significant anharmonic effects using nuclear–electronic orbital (NEO) theory. This protocol is validated against experimental data for a range of molecules in acetonitrile, including protonated nitrogen bases, nitrophenols, anilines, and diamines, as well as cobalt electrocatalysts. For simple acids, the NEO approach offers only a slight improvement over conventional density functional theory with the standard harmonic vibrational treatment, whereas for hydrogen-bonded acids, the NEO approach offers more significantly improved performance at a comparable computational cost. This accessible methodology provides a practical route for accurate pKa prediction in challenging systems and is extendable to related thermodynamic properties such as hydricities and proton-coupled redox potentials.

Density functional theory↗

Implementation and Evaluation of Emission‐Driven Land‐Atmosphere Coupled Simulation in E3SMv2.1

Emissions-driven (prognostic CO 2 ) simulations are essential for representing two-way carbon-climate feedback in Earth System Models. We present an emissions-driven land–atmosphere coupled biogeochemistry (BGC) configuration (BGCLNDATM_progCO2) in version 2.1 of the Energy Exascale Earth System Model (E3SMv2.1). This is the first E3SM configuration that performs land-atmosphere emission-hindcasts. Here, we document its implementation, evaluate the model's performance against observations and other models, and propose a structured evaluation protocol for such emissions-driven simulations. We conducted transient historical simulations (1850–2014) with BGCLNDATM_progCO2 and compare them to reference simulations—a land-atmosphere coupled simulation without BGC and a standalone land simulation with BGC, both using prescribed CO 2 concentrations—and to observations. BGCLNDATM_progCO2 overestimates atmospheric CO 2 concentrations by 11–23 ppm yet stays within the 40-ppm spread CMIP6 emission-driven models and retains physical climate properties comparable to the reference runs. The CO 2 biases are partly attributed to underrepresented oceanic CO 2 uptake and inadequate representations of some terrestrial processes. In general, introducing prognostic CO 2 did not change physical climate metrics at the global scale but had larger regional effects, particularly over land where spatially heterogeneous CO 2 and prognostic leaf area index influenced surface energy balance. Finally, we propose a general evaluation protocol including spin-up assessment, atmospheric CO 2 benchmarking, physical climate evaluation, and land biogeochemical analysis to support scientific rigor and facilitate inter-model comparisons. The new configuration lays the groundwork for future enhancements, including improved terrestrial biogeochemical processes, integrated marine biogeochemistry, and additional human–Earth system interactions. These developments advance E3SM toward fully coupled emissions-driven simulations, enabling more accurate carbon–climate feedback projections and informing mitigation policy by providing physically consistent carbon-budget metrics for mitigation scenarios.

54 ENVIRONMENTAL SCIENCES↗

An active learning framework for the rapid assessment of galvanic corrosion

The current present in a galvanic couple can define its resistance or susceptibility to corrosion. However, as the current is dependent upon environmental, material, and geometrical parameters it is experimentally costly to measure. To reduce these costs, Finite Element (FE) simulations can be used to assess the cathodic current but also require experimental inputs to define boundary conditions. Due to these challenges, it is crucial to accelerate predictions and accurately predict the current output for different environments and geometries representative of in-service conditions. Machine learned surrogate models provides a means to accelerate corrosion predictions. However, a one-time cost is incurred in procuring the simulation and experimental dataset necessary to calibrate the surrogate model. Therefore, an active learning protocol is developed through calibration of a low-cost surrogate model for the cathodic current of an exemplar galvanic couple (AA7075-SS304) as a function of environmental and geometric parameters. The surrogate model is calibrated on a dataset of FE simulations, and calculates an acquisition function that identifies specific additional inputs with the maximum potential to improve the current predictions. This is accomplished through a staggered workflow that not only improves and refines prediction, but identifies the points at which the most information is gained, thus enabling expansion to a larger parameter space. The protocols developed and demonstrated in this work provide a powerful tool for screening various forms of corrosion under in-service conditions.

36 MATERIALS SCIENCE↗

Heisenberg-limited Hamiltonian learning for interacting bosons

We develop a protocol for learning a class of interacting bosonic Hamiltonians from dynamics with Heisenberg-limited scaling. For Hamiltonians with an underlying bounded-degree graph structure, we can learn all parameters with root mean square error ϵ using ${\mathcal{O}}(1/\epsilon )$ total evolution time, which is independent of the system size, in a way that is robust against state-preparation and measurement error. In the protocol, we only use bosonic coherent states, beam splitters, phase shifters, and homodyne measurements, which are easy to implement on many experimental platforms. A key technique we develop is to apply random unitaries to enforce symmetry in the effective Hamiltonian, which may be of independent interest.

computer science↗

Certified randomness using a trapped-ion quantum processor

Although quantum computers can perform a wide range of practically important tasks beyond the abilities of classical computers, realizing this potential remains a challenge. An example is to use an untrusted remote device to generate random bits that can be certified to contain a certain amount of entropy. Certified randomness has many applications but is impossible to achieve solely by classical computation. Here we demonstrate the generation of certifiably random bits using the 56-qubit Quantinuum H2-1 trapped-ion quantum computer accessed over the Internet. Our protocol leverages the classical hardness of recent random circuit sampling demonstrations: a client generates quantum ‘challenge’ circuits using a small randomness seed, sends them to an untrusted quantum server to execute and verifies the results of the server. We analyse the security of our protocol against a restricted class of realistic near-term adversaries. Using classical verification with measured combined sustained performance of 1.1 × 10 18 floating-point operations per second across multiple supercomputers, we certify 71,313 bits of entropy under this restricted adversary and additional assumptions. Our results demonstrate a step towards the practical applicability of present-day quantum computers.

computer science↗

Multi-qubit nanoscale sensing with entanglement as a resource

Nitrogen vacancy (NV) centres in diamond are widely deployed as local magnetic sensors, using single-qubit control to measure both time-averaged fields and noise with nanoscale spatial resolution. Moving beyond single qubits to multi-qubit control enables new sensing modalities such as measuring nonlocal spatiotemporal correlators or using entangled states to enhance measurement sensitivity. Here, in this work, we describe protocols for using optically unresolved NV centre pairs and nuclear spins as multi-qubit sensors for measuring correlated noise at nanometre length scales. For noninteracting NV centres, we implement a phase-cycling protocol that disambiguates magnetic correlations from variance fluctuations, leveraging the presence of a third qubit, a 13 C nucleus, to effect coherent single-NV spin flips and enable phase cycling even for co-aligned NV centres that are spectrally unresolved. For length scales around 10 nm, we create maximally entangled Bell states through dipole–dipole coupling between two NV centres and use these entangled states to directly read out the magnetic field correlation, rather than reconstructing it from independent measurements of unentangled NV centres. Importantly, this changes the scaling of sensitivity with readout noise from quadratic to linear. For conventional off-resonant readout of the NV centre spin state (for which the readout noise is roughly 30 times the quantum projection limit), this results in more than an order of magnitude improvement in sensitivity. Finally, we demonstrate methods for detecting high spatial- and temporal-resolution correlators with pairs of strongly interacting NV centres.

condensed-matter physics↗

Interplay between element-specific distortions and electrocatalytic oxygen evolution for cobalt–iron hydroxides

A microscopic understanding of how Fe-doping of Co(OH) 2 improves electrocatalytic oxygen evolution remains elusive. We study two Co 1–x Fex(OH) 2 series that differ in fabrication protocol and find composition alone poorly correlates to catalyst performance. Structural descriptors extracted using X-ray diffraction, X-ray absorption spectroscopy, and Raman spectroscopy reveal element-specific distortions in Co 1–x Fe x (OH) 2 . These structural descriptors are composition-dependent within individual sample series but inconsistent across fabrication protocols, revealing fabrication-dependence in catalyst microstructure. Correlations between structural parameters from different techniques show that Fe–O resists bond length changes, forcing distortion of Co environments. We find the difference in O–M–O bond angles between Co and Fe sites to correlate with electrocatalytic behavior across both sample series, which we attribute to asymmetric distortion of potential energy surfaces for the Co(III) to Co(IV) oxidation. A Tafel slope consistent with a rate-limiting step without electron transfer emerges as the O–Co–O angle decreases, implying a distortion-induced transition in the rate-limiting step. The fabrication dependence of electronic and bonding structure in the catalysts should be considered in theoretical and high-throughput analyses of electrocatalyst materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

FL‐ADS: Federated learning anomaly detection system for distributed energy resource networks

Abstract With the ongoing development of Distributed Energy Resources (DER) communication networks, the imperative for strong cybersecurity and data privacy safeguards is increasingly evident. DER networks, which rely on protocols such as Distributed Network Protocol 3 and Modbus, are susceptible to cyberattacks such as data integrity breaches and denial of service due to their inherent security vulnerabilities. This paper introduces an innovative Federated Learning (FL)‐based anomaly detection system designed to enhance the security of DER networks while preserving data privacy. Our models leverage Vertical and Horizontal Federated Learning to enable collaborative learning while preserving data privacy, exchanging only non‐sensitive information, such as model parameters, and maintaining the privacy of DER clients' raw data. The effectiveness of the models is demonstrated through its evaluation on datasets representative of real‐world DER scenarios, showcasing significant improvements in accuracy and F1‐score across all clients compared to the traditional baseline model. Additionally, this work demonstrates a consistent reduction in loss function over multiple FL rounds, further validating its efficacy and offering a robust solution that balances effective anomaly detection with stringent data privacy needs.

Purohit, Shaurya [Iowa State University Ames Iowa ↗