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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The complex intracluster medium of Abell 1569 and its interaction with central radio galaxies

ABSTRACT We present the first in-depth study of X-ray emission from a nearby (z ∼ 0.0784) galaxy cluster Abell 1569 using an archival Chandra observation. A1569 consists of two unbound subclusters – a northern subcluster (A1569N) hosting a double-lobed radio galaxy 1233+169 at its centre, and a southern subcluster (A1569S) harbouring a wide-angle-tailed (WAT) radio source 1233+168. X-ray emission from A1569N and A1569S extends to a radius r ∼248 kpc and r ∼370 kpc, respectively, indicating that the two gas clumps are group-scale systems. The two subclusters have low X-ray luminosities (∼1042–43 erg s−1), average elemental abundances ∼1/4 Z⊙, low average temperatures (∼2 keV), and lack large (r ≳ 40–50 kpc) cool cores associated with the intracluster gas. We detect a pair of cavities coincident with the radio lobes of 1233+169 in A1569N. The total mechanical power associated with the cavity pair is an order of magnitude larger than the X-ray radiative loss in the cavity-occupied region, providing corroborating evidence for cavity-induced heating of the intragroup gas in A1569N. A1569S exhibits possible evidence for a small-scale cluster-subcluster merger, as indicated by its high central entropy, and the presence of local gas elongation and a density discontinuity in between the bent radio tails of 1233+168. The discontinuity is indicative of a weak merger shock with Mach Number, M ∼ 1.7. The most plausible geometry for the ongoing interaction is a head-on merger occurring between A1569S and a subcluster falling in from the west along the line bisecting the WAT tails.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Organic Rankine Cycle Integration and Optimization for High Efficiency CHP Genset Systems (Final Technical Report)

This project successfully advanced the integration of Organic Rankine Cycle (ORC) technology with reciprocating engine–based combined heat and power (CHP) systems to improve electrical efficiency, total CHP efficiency, and grid-responsive operation. Over three budget periods, the work progressed from high-temperature ORC component development and thermodynamic model validation to next-generation system design, working fluid transition, and techno-economic analysis. Key technical accomplishments include development and validation of a thermodynamic model capable of accurately predicting ORC performance across an expanded temperature and pressure envelope; successful identification and validation of low-global-warming-potential (GWP) working fluids—most notably R1233zd(E)—as viable replacements for R245fa; and demonstration of scalable ORC architectures suitable for integration with 1–20 MW class reciprocating engines. These advances enable flexible CHP configurations that can increase electrical output while maintaining high overall utilization of available thermal energy. The project also produced a clean-sheet design for a next-generation ORC system targeting substantially higher power output per unit, supported by detailed component selection, heat exchanger evaluation, and system-level modeling. Techno-economic analyses indicate that ORC-enabled flexible CHP systems can meet or exceed Department of Energy (DOE) efficiency targets while providing value to both facility operators and the electric grid.. Late-stage testing of the largest next-generation ORC prototype identified limitations related to pump net positive suction head (NPSH) requirements and condenser flooding under certain operating conditions. Although these issues constrained full validation of that configuration within the project timeframe, they provided clear and actionable design guidance for future system refinements. Importantly, validated modeling, smaller-scale testing, and working fluid evaluations confirmed the technical viability of the overall approach. In aggregate, this project met its core objectives by establishing validated design tools, de-risking key ORC technologies for CHP applications, and defining a credible pathway toward commercialization of flexible, high-efficiency CHP systems. The results form a strong foundation for continued development and deployment beyond the conclusion of the DOE-funded effort.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Measuring a Low Horizontal Hydraulic Gradient in a High Transmissivity Aquifer

Abstract High transmissivity aquifers typically have low hydraulic gradients (i.e., a flat water table). Measuring low gradients using water levels can be problematic because measurement error may be greater than the true difference in water levels (i.e., a low signal‐to‐noise ratio). In this study, the feasibility of measuring a hydraulic gradient in the range of 10 −6 to 10 −5 m/m was demonstrated. The study was performed at a site where the depth to water from land surface ranged from 40.1 to 94.2 m and the aquifer transmissivity was estimated at 41,300 m 2 /d (hydraulic conductivity of 18,800 m/d). The goals of the study were to reduce measurement error as much as practicable and assess the importance of factors affecting water level measurement accuracy. Well verticality was the largest source of error (0.000 to 0.168 m; median of 0.014 m), and geodetic survey of casing elevations was the next most important source of error (0.002 to 0.013 m; median of 0.005 m). Variability due to barometric pressure fluctuations was not an important factor at the site. Hydraulic heads were measured to an accuracy of ±0.0065 m, and the average hydraulic gradient was estimated to be 8.0 × 10 −6 (±0.9 × 10 −6 ) m/m. The improvement in accuracy allowed for two reversals in the groundwater flow direction to be identified, after which the gradient averaged 2.5 × 10 −5 (±0.4 × 10 −5 ) m/m. This study showed it is possible to sufficiently control sources of error to measure hydraulic gradients in the 10 −6 to 10 −5 m/m range.

McDonald, John P.↗
DOE OSTI2022

Supergravity black holes, Love numbers, and harmonic coordinates

A problem which has now come to a head in general relativity, primarily as a result of the many recent detections of gravitational waves from the coalescence of compact binaries, is that there are very few viable theories against which to “test” it. To perform realistic tests of theories of gravity, we need to be able to look beyond general relativity and evaluate the consistency of a parametrized, physically acceptable, family of black hole metric alternatives with observational data from, especially, gravitational wave detections using, for example, an agnostic Bayesian approach. In this paper we further examine properties of one class of such metrics, which in fact arise as solutions of ungauged supergravity. In particular, we examine the massless, neutral, minimally coupled scalar wave equation in a general stationary, axisymmetric background metric such as that of a charged rotating black hole, when the scalar field is either time independent or in the low-frequency, near-zone limit, with a view to calculating the Love numbers of tidal perturbations, and of obtaining harmonic coordinates for the background metric. For a four-parameter family of charged asymptotically flat rotating black hole solutions of ungauged supergravity theory known as STU black holes, which includes Kaluza-Klein black holes and the Kerr-Sen black hole as special cases, we find that all time-independent solutions, and hence the harmonic coordinates of the metrics, are identical to those of the Kerr solution. In the low-frequency limit we find the scalar fields exhibit the same SL(2,R) symmetry as holds in the case of the Kerr solution. We point out extensions of our results to a wider class of metrics, which includes solutions of Einstein-Maxwell-dilaton theory.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

An isolated water droplet in the aqueous solution of a supramolecular tetrahedral cage

Water under nanoconfinement at ambient conditions has exhibited low-dimensional ice formation and liquid–solid phase transitions, but with structural and dynamical signatures that map onto known regions of water’s phase diagram. Using terahertz (THz) absorption spectroscopy and ab initio molecular dynamics, we have investigated the ambient water confined in a supramolecular tetrahedral assembly, and determined that a dynamically distinct network of 9 ± 1 water molecules is present within the nanocavity of the host. The low-frequency absorption spectrum and theoretical analysis of the water in the Ga 4 L 6 12– host demonstrate that the structure and dynamics of the encapsulated droplet is distinct from any known phase of water. A further inference is that the release of the highly unusual encapsulated water droplet creates a strong thermodynamic driver for the high-affinity binding of guests in aqueous solution for the Ga 4 L 6 12– supramolecular construct.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Pumped Storage Hydropower Augmented with Pressurized Air: The Ground-Level Integrated Diverse Energy Storage (GLIDES) System — GLIDES System Configurations and Use Cases

Energy storage is essential for cost-effective integration of variable renewable energy sources to support a low-carbon grid. It is also a key enabler of a modern grid infrastructure for demand management. However, several main challenges remain for different kind of energy storage technologies in grid scale deployment. Currently, the largest source of utility-scale storage and long-duration storage in the US is pumped storage hydropower (PSH). Prospect of growth in conventional PSH faces challenges that have limited its deployment over the last three decades, including high capital costs and long deployment timelines. Batteries have high energy densities and are the primary technology of choice for small-scale energy storage. Compressed air energy storage (CAES) is another large-scale energy storage technology, but there are few plants deployed worldwide. They suffer from their low round trip efficiency (RTE) due to the use of high-pressure air compressors. To address some of the challenges associated with these various storage technologies, the Ground-Level Integrated Diverse Energy Storage (GLIDES) is a modular PSH technology that was invented in 2015 at Oak Ridge National Laboratory. It utilizes gas compression to store electric energy. GLIDES stores energy by compressing gas using a liquid piston in high-pressure vessels. In doing so the vessels act as the upper reservoir in conventional PSH. Initially, the vessels are filled with gas to a prescribed pressure. To store energy, GLIDES uses a hydraulic piston pump to pump water into the pressurized vessels. As the water volume increases inside the vessels, water acts as a hydraulic piston compressing the gas on top of it. This process can be thought of as pumping water from the lower reservoir to the higher reservoir in PSH, increasing the water head. To dispatch the stored energy, the high-head water in the vessel is discharge through a high head Pelton hydraulic turbine that is connected to an electric generator. Employing high-pressure vessels enables GLIDES to reach water heads ~10-80 times higher than conventional PSH, achieving ~40 times higher energy densities, and overcomes the geographic limitation of conventional PSH. Although its energy density is much lower than that of batteries, GLIDES holds the potential advantages of having long service life, ease of system integration and being less hazardous over batteries. GLIDES prospective scalability could make it suitable for wide range of applications from behind the meter storage in buildings to grid-scale storage. It also makes it suitable for installations in densely populated urban areas where energy storage is most needed and real estate is limited. Over the last 5 years, work has focused on increasing GLIDES’ energy density, decreasing its initial capital cost of the system, and increasing its revenue potential. Several designs were developed and prototyped to verify and demonstrate the improvement in energy density. The latest prototype achieved energy density of 1.21 kWh/m 3 . Our analysis showed that it could achieve up to 1.7 kWh/m 3 with a mixture of air and carbon dioxide as the gas being compressed.

13 HYDRO ENERGY↗
DOE OSTI2026

Movement Models to Predict Low‐Altitude Flight of Soaring Birds Using Look‐Ahead Environmental Factors

Advances in fine-scale movement modeling of soaring birds can aid efforts to understand and resolve the impacts of anthropogenic activities on such birds. Soaring birds often rely on underlying terrain and low-altitude updrafts to govern their flights at rotor-swept altitudes (≤ 200 m above ground level), which puts them at risk of collision with wind turbines. We developed a data-driven Markov model at 1-s resolution that predicts the fine-scale flight behavior of golden eagles (Aquila chrysaetos) as a function of ecological covariates at the current location as well as those within an eagle's line of sight. We only considered ecological covariates that are readily available in real-time (ground elevation and wind conditions). Latent factors (age, sex, species, behavioral intent, migratory status) were intentionally left out of the model. We calibrated the model using golden eagle telemetry data collected in two different ecoregions of the United States. Given a starting location, the calibrated model simulates multiple stochastic 3D paths to produce a time-explicit and spatially explicit risk map of turbine collisions. We discovered an empirical relation between the rate of change of heading and the orographic updraft conditions within an eagle's line of sight. Our model performed most effectively when predicting predominantly-soaring flights at rotor-swept altitudes during wind conditions in which turbines are likely to be operational. The calibrated model could be used in concert with automated eagle detection and turbine curtailment technologies. Specifically, once an eagle is detected by those systems, our model could then provide accurate predictions of turbines the eagle is likely to interact with in the near term.

17 WIND ENERGY↗
DOE OSTI2025

Enhancing Unknown Waveform Detection by Learning Intra and Inter-domain Dependencies with Advanced Attention Fusion Mechanisms

Detection of unknown waveforms in mission-critical communications is a crucial area of interest for the Department of Energy (DoE). Traditional methods and recent deep learning-based approaches often assume that the training set includes all possible classes, which is impractical for detecting new waveforms. This limitation gives rise to the problem of open-set recognition (OSR), which involves correctly identifying known classes while detecting and rejecting unknown or unseen classes. To address this limitation, we propose a novel dual-domain complex-valued neural architecture that jointly processes time-domain and frequency-domain signal representations using transformer mechanisms. A transformer model is a deep learning architecture that uses self-attention mechanisms to process and learn relationships in sequential data. Our model employs a cosine similarity loss to extract domain-specific features and incorporates a transformer architecture in the latent space to weigh the importance of different features from the time and frequency domains. The transformer layer includes stacked self-attention and cross-attention modules to learn intra-domain and inter-domain dependencies, creating a more holistic signal representation. An attention-based fusion module intelligently combines the time and frequency-domain features using multi-head attention, enabling the network to learn the optimal feature for each domain in each input signal. Quantitative results demonstrate the impact of these architectural choices on overall performance, showing significant improvement after incorporating self and cross-attention modules and using complex attention fusion over simple weighted fusion. Our ongoing work will focus on addressing the limitations of threshold-based OSR methods by developing a novel generative framework that integrates a conditional diffusion probabilistic model (DPM). DPM is a generative framework that learns to synthesize complex data by reversing a gradual noising process using a neural network trained to denoise step-by-step. Our goal is to leverage the inherent strengths of DPMs for identifying unknown signals more robustly. One primary advantage of using a DPM is its ability to provide a more reliable anomaly score based on the model's reconstruction error, rather than relying solely on classifier confidence. Additionally, the iterative denoising process of DPMs makes this approach naturally resilient to low Signal-to-Noise Ratio (SNR) conditions, where traditional methods often fail. By implementing this generative framework, we aim to enhance the model's capability to accurately detect unknown waveforms and maintain performance in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

An improved guess for the variational calculation of charge-transfer excitations in large systems

Ab initio quantum-chemical methods that perform well for computing the electronic ground state are not straightforwardly transferable to electronically excited states, particularly in large molecular systems. Wave function theory offers high accuracy, but is often prohibitively expensive. Methods based on time-dependent density functional theory (TD-DFT) are crucially sensitive to the chosen exchange-correlation functional (XCF) parameterization, and system-specific tuning protocols were therefore proposed to address the method's robustness. Methods based on the variational relaxation of the excited-state electron density showcased promising results for the calculation of charge-transfer excitations, but the complex shape of the electronic hypersurface makes convergence to a specific excited state much more difficult than for the ground state when standard variational techniques are applied. We address the latter aspect by providing suitable initial guesses, which we obtain by two separate constrained algorithms. Combined with the squared-gradient minimization algorithm for all-electrons relaxation in a freeze-and-release scheme (FRZ-SGM), we demonstrate that orbital-optimized density functional theory (OO-DFT) calculations can reliably converge to the charge-transfer states of interest even for large molecular systems. We test the FRZ-SGM method on a phenothiazine-anthraquinone CT excitation in a supramolecular Pd(II) coordination cage complex as a function of the cage conformation. This compound has been studied experimentally prior to our work. We compare this freeze-and-release scheme to two XCF reparameterizations, which were recently proposed as low-cost TD-DFT-based alternatives to variational methods. Two dye-semiconductor complexes, which were previously investigated in the context of photovoltaic applications, serve as a second example to investigate the convergence and stability of the FRZ-SGM approach. Our results demonstrate that FRZ-SGM provides reliable convergence for charge-transfer excited states and avoids variational collapse to lower-lying electronic states, whereas time-dependent DFT calculations with an adequate tuning procedure for the range-separation parameter provide a computationally efficient initial estimate of the corresponding energies, with a computational cost comparable to that of configuration-interaction singles (CIS) calculations.

Bogo, Nicola↗
DOE OSTI2026

Measuring changes in environmental radiological background from construction of an advanced nuclear reactor testing facility

We present a method to survey and track changes in the environmental radiological background during the construction and operation of advanced nuclear reactor facilities. We discuss the results of two surveys of the environmental gamma-radiation background at NEXT Lab, an advanced nuclear reactor research facility on the campus of Abilene Christian University, prior to the introduction of radioactive material. In both surveys, the observed radiation dosage rates are low, with the highest rates at 15% of the average total radiation dosage rate for the United States. We observe ≈20% changes in the radiological background of the property in locations where the environment was changed by construction and ≈20% variations within the facilities correlated with variations in building materials.

Environment↗
DOE OSTI2020

Grain Refinement Effect on the Hot-Tearing Resistance of Higher-Temperature Al–Cu–Mn–Zr Alloys

The hot-tearing resistance of Al-Cu-Mn-Zr (ACMZ) alloys was investigated as a step toward introducing these new cast alloys for severe duty, higher-temperature applications, such as cylinder heads for down-sized, turbocharged automotive engines. Alloy Cu compositions were varied from 5 to 8 wt.%. Targeted Ti levels were 0.02, 0.1, and 0.2 wt.% via additions of the Al–5Ti–1B master alloy. Hot-tearing resistance was assessed by visual examination and ranking of the cracking severity in a multi-arm permanent mold casting. It was found that at high impurity contents (Fe and Si of 0.2 wt.% each), the Al–Cu–Mn–Zr alloy with 4.95 wt.% Cu exhibited the poorest hot-tearing resistance, irrespective of the grain refining amount. Microstructural analysis indicated an effective reduction in the grain size, as the Ti additions were increased to 0.02 and 0.1 wt.% Ti via the Al–Ti–B grain refiner. The finest grain size was attained with a 0.1 wt.% Ti. Based on the hot-tearing evaluation, it was found that the additional grain refining via the Al–5Ti–1B master alloy at 0.1 wt.% Ti significantly reduces the hot-tearing susceptibility at Cu contents greater than 7.3 wt.% for ACMZ alloys with low Fe and Si. These findings indicate that the best hot-tearing resistance was observed at a grain refiner level of 0.1 wt.% Ti and high Cu content (greater than 7.3 wt.%). This study to indicates that these Al–Cu–Mn–Zr alloys, which possess excellent microstructural stability and mechanical properties at elevated temperatures, can also possess excellent hot-tearing resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Low-Oxidized Siloxene Nanosheets with High Capacity, Capacity Retention, and Rate Capability in Lithium-Based Batteries

The mechanical degradation experienced by Si electrodes during Li (de)alloying reactions can potentially be mitigated by using Si-based materials with layered 2D geometries. Such materials are expected to exhibit favorable mechanical properties and be capable of buffering the volume change associated with (de)lithitation. In this work, 2D siloxene nanosheets are synthesized using a facile topotactic reaction followed by ultrasonication as an exfoliation step. Here, detailed structural and chemical characterization via electron microscopy, X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy is conducted, revealing a low-oxidized siloxene nanosheet material with only 15% surface Si-oxide. The obtained siloxene nanosheets are tested as Li-ion negative electrodes in lithium-based electrochemical cells. The cells exhibit high rate capability with a capacity of 935 mAh g –1 at 3200 mA g –1 and ≈99.5% coulombic efficiency. The inclusion of fluoroethylene carbonate (FEC) in the electrolyte improves capacity retention over 200 cycles from 13% to 77% at 1000 mA g –1 . This behavior is attributed to the FEC decomposition forming a solid electrolyte interphase (SEI) with higher ion conductivity and robust LiF/Li x PO y F z content, as characterized via XPS Raman spectroscopy.

25 ENERGY STORAGE↗
DOE OSTI2025

Magnetic mesh generation and field line reconstruction for scrape-off layer and divertor modeling in stellarators

The design of divertor targets and baffles for optimal heat and particle exhaust from magnetically confined fusion plasmas requires a combination of fast, low-fidelity models (such as EMC3-Lite (Feng 2022 Plasma Phys. Control. Fusion 64 125012)) for scoping studies and high-fidelity ones (such as EMC3-EIRENE (Feng et al 2014 Contrib. Plasma Phys. 54 426–31)) for verification. Both of those approaches benefit from a magnetic flux tube mesh for fast interpolation and mapping of field line segments (Feng et al 2005 Phys. Plasmas 12 052505). A new automated mesh generator for unstructured quadrilateral flux tubes with adaptive refinement is presented and integrated into FLARE (Frerichs 2024 Nucl. Fusion 64 106034). For HSX with an extended first wall, it is found that several layers of flux tubes can span the entire half field period before splitting is required. This is an advantage over the traditional setup of the EMC3-EIRENE mesh where careful construction of several sub- domains is required already for the much tighter present first wall. In particular, there is no longer the need to manually construct a suitable outer boundary for the mesh. The divide and conquer paradigm with unstructured mesh layout offers a powerful alternative for fast head load approximation that is suitable for integration into optimization workflows. Further examples for W7-X and CTH demonstrate the versatile application range.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Biomass yield improvement in switchgrass through genomic prediction of flowering time

The seasonal timing of the transition from vegetative to reproductive growth has a major impact on biomass accumulation in switchgrass. Late-flowering switchgrass cultivars produce greater biomass, a critical trait for sustainable bioenergy production. Genomic prediction (GP) may allow rapid selection of late-flowering individuals with reduced time and expense for field evaluations. To evaluate GP, two flowering time traits (heading date and anthesis date) were collected on 1532 genotypes from four breeding populations: Midwest, Gulf, Atlantic, and Hybrid. These were sequenced using genotype-by-sequencing (530,792 single-nucleotide polymorphisms). Predictive ability of single-trait and multi-trait models were evaluated by cross-validation, by prediction of a progeny trial (n = 122), and through prediction of yield performance in a parallel experiment (n = 52). Predictive ability was not improved by sharing information among breeding groups. Overall, multi-trait models provided an advantage during cross-validation, but a smaller advantage during progeny prediction. Within populations, GP resulted in lower per-cycle progress than previously reported field evaluations (3.1 vs. 5.0 day –1 cycle –1 ). However, GP cycles are potentially much faster than field evaluations. When directly predicting biomass yield, the Hybrid training population had a predictive ability of 0.54–0.63. This reinforces the strong linkage between biomass yields in swards and flowering time. Furthermore, these results highlight the value of GP for rapid yield improvement in switchgrass, particularly in a breeding program designed to share information between biomass yield trials and low-cost flowering time evaluations.

09 BIOMASS FUELS↗
DOE OSTI2021

Xenon Trapping in Metal-Supported Silica Nanocages

Xenon (Xe) is a valuable and scarce noble gas used in various applications, including lighting, electronics, and anesthetics, among many others. It is also a volatile byproduct of the nuclear fission of uranium. In this work, a novel material architecture consisting of silicate nanocages in contact with a metal surface and an approach for trapping single Xe atoms in these cages is presented. The trapping is done at low Xe pressures and temperatures between 400 and 600 K, and the process is monitored in situ using synchrotron-based ambient pressure X-ray photoelectron spectroscopy. Release of the Xe from the cages occurs only when heating to temperatures above 750 K. A model that explains the experimental trapping kinetics is proposed and tested using Monte Carlo methods. Density functional theory calculations show activation energies for Xe exiting the cages consistent with experiments. This work can have significant implications in various fields, including Xe production, nuclear power, nuclear waste remediation, and nonproliferation of nuclear weapons. The results are also expected to apply to argon, krypton, and radon, opening an even more comprehensive range of applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Smooth Dispersion Is Physically Appropriate: Assessing and Amending the D4 Dispersion Model

The addition of dispersion corrections to density functionals is essential for accurate energy and geometry predictions. Among them, the D4 scheme is popular due to its low computational cost and high accuracy. However, due to its design, the D4 correction can occasionally lead to anomalies, such as unphysical curvature and bumps in the potential energy surface. We find these anomalies are common in the D4 model, although observable consequences are rarer than in the D3 model for reasons we explain. Nevertheless, we uncover instances of unphysical local minima and stationary points with the D4 scheme and propose two solutions that yield smoother dispersion energy as a function of nuclear position. One is trivial to implement, based on a smoother reparametrization of Gaussian weighting (D4S) to find the effective coordination number. The other replaces Gaussian weighting with soft linear interpolation (D4SL). These new approaches usually remove artificial extremum points, while maintaining accuracy.

Tkachenko, Nikolay V↗
DOE OSTI2022

Methanol Decomposition on Copper Surfaces under Ambient Conditions: Mechanism, Surface Kinetics, and Structure Sensitivity

Here, we study the adsorption of methanol vapor under ambient pressure and temperature conditions on low-index Cu surfaces using surface-sensitive infrared (IR) and X-ray spectroscopy techniques. The first step of methanol decomposition, i.e. , breaking of the O—H bond to form surface-bound methoxy, readily occurs under ambient conditions. Time-lapse IR spectra clearly indicate a gradually decreasing methoxy coverage, which does not obey well established kinetic models. We rationalize the initial temperature-independent, high, nonequilibrium coverage of methoxy by a H-bonded methanol assembly in the precursor state. A temperature-dependent equilibrium coverage is achieved as the excess methoxy is eliminated gradually via further dehydrogenation to CO that desorbs to the gas phase. The kinetics of this process displays a significant structure sensitivity with considerably faster kinetics on the Cu(110) surface compared to Cu(111) and Cu(100) surfaces.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Gold-Standard Chemical Database 137 (GSCDB137): A Diverse Set of Accurate Energy Differences for Assessing and Developing Density Functionals

We present GSCDB137, a rigorously curated benchmark library of 137 data sets (8377 entries) covering main-group and transition-metal reaction energies and barrier heights, (intra- and intermolecular) noncovalent interactions, dipole moments, polarizabilities, electric-field response energies, and vibrational frequencies. Legacy data from GMTKN55 and MGCDB84 have been updated to today's best reference values; redundant or low-quality points were removed, and many new, property-focused sets were added. Testing 29 popular density functional approximations (DFAs) confirms the expected Jacob's-ladder hierarchy overall but also reveals notable exceptions: functional performance for frequencies and electric-field properties correlates poorly with that for other ground-state energetics. ωB97M-V and ωB97X-V are the most balanced hybrid meta-GGA and hybrid GGA, respectively; B97M-V and revPBE-D4 lead the meta-GGA and GGA classes. Double hybrids lower mean errors by about 30% versus their hybrid analogues but demand careful frozen-core, basis set, and spin contamination treatment. GSCDB137 offers a comprehensive, openly documented platform for rigorous validation of DFA and universal machine learning potentials, and training of the next generation of exchange-correlation functionals.

Liang, Jiashu [University of California, Berkeley,↗