Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Composite models”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Lepton-flavor-violating ALPs at the Electron-Ion Collider: a golden opportunity

Axion-like particles (ALPs) arise in a variety of theoretical contexts and can, in general, mediate flavor violating interactions and parity non-conservation. We consider lepton flavor violating ALPs with GeV scale or larger masses which may, for example, arise in composite dark sector models. We show that a future Electron-Ion Collider (EIC) can uncover or constrain such ALPs via processes of the type e A Z → τ A Z a, where A Z is a nucleus of charge Z and a is an ALP in the range m τ ≤ m a ≲ 20 GeV. The production of the ALP can have a large Z 2 enhancement from low Q 2 electromagnetic scattering of the electron from a heavy ion. Using the gold nucleus (Z = 79) as an example, we show that the EIC can explore e – τ flavor violation, mediated by GeV-scale ALPs, well beyond current limits. Importantly, the EIC reach for this interaction is not sensitive to the lepton-flavor conserving ALP couplings, whose possible smallness can render searches using τ decays ineffective. We also discuss how the EIC electron beam polarization can provide a powerful tool for investigating parity violating ALPs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Dark showers from sneaky dark matter

We present a minimal composite dark matter model, based on a SU(Nd) dark sector with nf dark quarks and a heavy t-channel mediator. For nf ≥ 4, the dark flavor symmetry guarantees the stability of a subset of the dark pions, which serve as our dark matter candidates. Their relic abundance is determined by dark sector annihilation with the remaining dark pions, which are unstable and decay. Due to their degenerate masses, the annihilation cross section is suppressed at low temperatures, thereby avoiding stringent constraints from indirect detection and opening up the GeV mass window. The decaying dark pions are naturally long lived. We obtain limits on the model from semi-visible or emerging jet searches and estimate the reach of future probes.

ALPs↗
DOE OSTI2026

A framework and tool for designing cost-effective, resilient, and circular net-zero supply chains under uncertainty with an application to multilayer plastic films

While 55% of Fortune 500 companies have committed to achieving net-zero emissions and/or zero-waste operations by 2035, only 2% are currently on track, revealing a critical gap between ambition and action. Designing supply chains that reduce both emissions and waste is a complex non-intuitive, multi-objective challenge, compounded by the high costs of new technologies and the need for resilient, profitable solutions. This paper aims to address this challenge by presenting a generic framework and multi-objective optimization formulation for designing cost-effective, circular, and resilient supply chains under uncertainty, implemented through a user-friendly decision-support tool with intuitive data visualization capabilities, enabling communication of results to both technical and non-technical stakeholders. We demonstrate the application of this framework in the context of multilayer plastic films (barrier films), which are widely used in food packaging and composite materials. The model quantifies trade-offs across three objectives: minimizing global warming potential, maximizing circularity, and minimizing cost. A key contribution of this work is the explicit modeling of technological resilience, the ability of supply chains to maintain function under disruption. In the cost-minimization case, the resilience constraint makes the design approximately three times more expensive in the short-term metric, but shifts the system from relying on a single recovery pathway to a portfolio of four recovery pathways, improving the robustness of the optimization solution under uncertainty. Lastly, we introduce TranZero, a decision-support tool that integrates material flow analysis, hotspot identification, and optimization-based scenario planning to support net-zero and circularity decisions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

From biowaste to BioPave: Biological pathways for sequestration of anthropogenic CO 2 and enhancing durability of roadway infrastructures

Biomass-derived bio-oils are emerging as sustainable, low-carbon alternatives for construction materials, particularly in innovative pavement applications, 'BioPave'. Here, this study evaluates bio-oils from various sources, including algae and wastewater biomass, revealing variations in carbon, nitrogen, and sulfur contents, along with viscosity. We focused on their application in outdoor construction, assessing their resistance to thermal and solar radiation, and moisture. The study also examines their interaction with siliceous surfaces and their influence on asphalt adhesion in BioPave systems under moisture conditions. Laboratory experiments and computational modeling demonstrated molecular composition significantly influenced bio-oils' responses to thermal and UV exposure. Bio-oils rich in polar groups showed hardening upon thermal treatment, while those with higher concentrations of saturated aliphatics remained more stable. Furthermore, our findings highlight the significance of dosage control in maximizing beneficial effects of bio-oils in intermolecular interactions at bitumen-aggregate interface in BioPave applications. These findings offer insights into the potential of bio-oils in sustainable construction and the need for dosage control to optimize pavement performance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The Surface Chemistry of Methanol on Cu 3 Pd(111): Effects of Metal Alloying and Reaction with Hydrogen

Synchrotron-based ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) was used to study the adsorption and surface chemistry of methanol on a Cu 3 Pd(111) model surface. The composition and morphological properties of the pristine Cu 3 Pd(111) substrate were analyzed using a combination of low-energy electron diffraction (LEED), scanning tunneling microscopy (STM), and low-energy ion scattering (LEIS). The results of ion scattering showed segregation of Pd toward the surface, with a Pd/Cu ratio close to 0.5, a larger value than the ratio of 0.33 expected for a Cu 3 Pd bimetallic structure. The surface of the alloy exhibited a good LEED pattern with three-fold long-range periodicities. In STM, clusters of palladium with hexagonal arrays and Pd- Pd distances of 2.7-2.8 Å were detected. Bonding to copper perturbed the electronic properties of the atoms in the Pd clusters, shifting their 4d states toward higher binding energy with respect to the Fermi level. Further, the valence band spectrum of Cu 3 Pd(111) exhibited a line shape that was very different from those displayed by Cu(111) or Pd(111). At low pressures, the adsorption of methanol on Cu 3 Pd(111) at 300 K mainly produced CH 3 O, CO and CH x species. AP-XPS showed that most Pd atoms in the surface of the Cu 3 Pd(111) alloy interacted with the decomposition products of methanol. No significant changes were observed in the core levels of copper upon the adsorption and dissociation of methanol, suggesting that the molecule mainly interacted with Pd sites of the alloy. Reaction with hydrogen led to fast removal of CH x , C and PdC x species from Cu 3 Pd(111) at moderate (< 450 K) temperatures and prevented a CH x → C transformation. If the stability of adsorbed CH 3 O is used as a descriptor for the hydrogenation of CO 2 to methanol, Cu 3 Pd should be a much better catalyst than monometallic palladium. This may be a consequence of electronic and ensemble effects in the alloy that moderate the reactivity of Pd sites.

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

Accurate Prediction of Voltage of Battery Electrode Materials Using Attention-Based Graph Neural Networks

Performing first-principles calculations to discover electrodes’ properties in the large chemical space is a challenging task. While machine learning (ML) has been applied to effectively accelerate those discoveries, most of the applied methods ignore the materials’ spatial information and only use predefined features: based only on chemical compositions. Here, we propose two attention-based graph convolutional neural network techniques to learn the average voltage of electrodes. Our proposed methods, which combine both atomic composition and atomic coordinates in 3D-space, improve the accuracy in voltage prediction significantly when compared to composition-based ML models. The first model directly learns the chemical reaction of electrodes and metal ions to predict their average voltage, whereas the second model combines electrodes’ ML predicted formation energy (E form ) to compute their average voltage. Our E form -based model demonstrates improved accuracy in transferability from our subset of learned Li ions to Na ions. Moreover, we predicted the theoretical voltage of 10 Na x MPO 4 F (M = Ti, Cr, Fe, Cu, Mn, Co, and Ni) fluorophosphate battery frameworks, which are unavailable in the Material Project database. It could be shown that we can expect average voltages higher than 3.1 V from those Na battery frameworks except from the NaTiPO 4 F and TiPO 4 F pair of electrodes, which offer an average voltage of 1.32 V.

25 ENERGY STORAGE↗
DOE OSTI2020

Urban Scaling as Validation for Predictions of Imperviousness From Population

Abstract Strategies for creating quantitative projections for human systems, especially impervious surfaces, are necessary to consider the human drivers of climate and ecosystem change. There are models that generate predictions of how impervious surfaces may change in response to different potential futures, but few tools exist for validating those predictions. We seek to fill that gap. We demonstrate a statistically robust sublinear scaling relationship between population and urban imperviousness across a 15 year history. We show that Integrated Climate and Land‐Use Scenarios (ICLUS) urbanization projections are also consistent with theory. These results demonstrate a theory that can be used to validate other models' predictions of urban growth and land cover change, analogous to the ways in which allometric scaling laws in biology have been used to validate process‐based models of ecosystem composition under different climate scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Near-canopy horizontal concentration heterogeneity of semivolatile oxygenated organic compounds and implications for 2-methyltetrols primary emissions

Semivolatile oxygenated organic compounds (SV-OVOCs) are important atmospheric species, in particular for the production and chemistry of atmospheric particulate matter and related impacts on air quality and climate. In this study, SV-OVOCs were collected in the horizontal plane of the roughness layer over the tropical forest in the central Amazon during the wet season of 2018. A sampler mounted to a copter-type, hovering unmanned aerial vehicle was used. Underlying the collection region, a plateau forest transitioned into a slope forest across several hundred meters. The concentrations of pinonic and pinic acids, which are monoterpene oxidation products, had no statistical difference over the two forests. By comparison, across the study period, differences in the concentration of 2-methyltetrols, which are products of isoprene oxidation, ranged from -70% to +480% over the two forests. The chemical lifetime of 2-methyltetrols in the atmosphere is sufficiently long that heterogeneity in the isoprene emission rate from the two forests followed by atmospheric oxidation does not explain the concentration heterogeneity of 2-methyltetrols. Standing waves and local meteorology also cannot account for the heterogeneity. Of the possibilities considered, the most plausible explanation is the direct emission from the forest of 2-methyltetrols produced through biological processes within the plants. Under this explanation, the rate of direct SV-OVOC emissions should be modulated by forest type and related environmental stressors. Direct emissions of SV-OVOCs should be more broadly considered for constraining and improving models of atmospheric composition, transport, and chemistry over tropical forests.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Towards Pareto optimal high entropy hydrides via data-driven materials discovery

The ability to rapidly screen material performance in the vast space of high entropy alloys is of critical importance to efficiently identify optimal hydride candidates for various use cases. Given the prohibitive complexity of first principles simulations and large-scale sampling required to rigorously predict hydrogen equilibrium in these systems, we turn to compositional machine learning models as the most feasible approach to screen on the order of tens of thousands of candidate equimolar high entropy alloys (HEAs). Critically, we show that machine learning models can predict hydride thermodynamics and capacities with reasonable accuracy (e.g. a mean absolute error in desorption enthalpy prediction of ~5 kJ mol H 2 –1 ) and that explainability analyses capture the competing trade-offs that arise from feature interdependence. We can therefore elucidate the multi-dimensional Pareto optimal set of materials, i.e., where two or more competing objective properties can't be simultaneously improved by another material. This provides rapid and efficient down-selection of the highest priority candidates for more time-consuming density functional theory investigations and experimental validation. Various targets were selected from the predicted Pareto front (with saturation capacities approaching two hydrogen per metal and desorption enthalpy less than 60 kJ mol H 2 –1 ) and were experimentally synthesized, characterized, and tested amongst an international collaboration group to validate the proposed novel hydrides. Finally, additional top-predicted candidates are suggested to the community for future synthesis efforts, and we conclude with an outlook on improving the current approach for the next generation of computational HEA hydride discovery efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A sample of dust attenuation laws for Dark Energy Survey supernova host galaxies

Type Ia supernovae (SNe Ia) are useful distance indicators in cosmology, provided their luminosity is standardized by applying empirical corrections based on light-curve properties. One factor behind these corrections is dust extinction, which is accounted for in the color–luminosity relation of the standardization. This relation is usually assumed to be universal, which can potentially introduce systematics into the standardization. The “mass step” observed for SN Ia Hubble residuals has been suggested as one such systematic. We seek to obtain a more complete view of dust attenuation properties for a sample of 162 SN Ia host galaxies and to probe their link to the mass step. We inferred attenuation laws toward hosts from both global and local (4 kpc) Dark Energy Survey photometry and composite stellar population model fits. We recovered a relation between the optical depth and the attenuation slope, best explained by differing star-to-dust geometry for different galaxy orientations, which is significantly different from the optical depth and extinction slope relation observed directly for SNe. We obtain a large variation of attenuation slopes and confirm these change with host properties, such as the stellar mass and age, meaning a universal SN Ia correction should ideally not be assumed. Analyzing the cosmological standardization, we find evidence for a mass step and a two-dimensional “dust step”, both more pronounced for red SNe. Although comparable, the two steps are not found to be completely analogous. We conclude that host galaxy dust data cannot fully account for the mass step, using either an alternative SN standardization with extinction proxied by host attenuation or a dust-step approach.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Benchmark of the Chlorine Worth Study Experiments in Support of Chlorine Nuclear Data Validation for Nuclear Criticality Safety

The Chlorine Worth Study (CWS) was a critical experiment to address an urgent need for thermal chlorine nuclear data validation in plutonium systems. This urgent need is tied directly to plutonium recycle and recovery operations in the plutonium facility at Los Alamos National Laboratory, where exceptionally conservative criticality safety limits are used because no credit is taken for the neutron capture by chlorine. The experiment used weapons-grade plutonium metal plates clad in stainless steel, known as the PANN (plutonium aluminum no nickel) ZPPR (zero power physics reactor) plates. The plutonium was reflected and moderated by high-density polyethylene and included combinations of polyvinyl chloride (PVC) and chlorinated polyvinyl chloride (CPVC) as absorbers. The experiment and benchmark included three configurations mimicking 30 g 239 Pu/L plutonium, 300 g 239 Pu/L plutonium, and 600 g 239 Pu/L plutonium in an aqueous chloride solution. Uncertainties in the benchmark included five broad categories: (1) criticality measurement, (2) mass and density, (3) dimensions, (4) material compositions, and (5) positioning. The largest contribution to the overall uncertainties for all three cases came from the material compositions, in particular the PVC and CPVC absorber compositions. A detailed model was created to be a near match (that is within expectations of transport code users) and a simplified model was created to minimize offset dimensions and expedite modeling for code validation. Sample calculations were completed in MCNP6.3 with ENDF/B-VIII.0 and ENDF/B-VII.1 nuclear data. For the detailed and simplified models, the average difference between the computed and experimental k eff was 951 pcm. CWS will serve as the key validation experiment for nuclear criticality safety in support of aqueous chloride operations. The sensitivity to the chlorine capture cross section is orders of magnitude greater than other existing benchmarks. The current limits, as defined by nuclear criticality safety, are 520 g Pu per batch, i.e. the minimum critical mass of the Pu solution infinitely reflected by water [Criticality Handbook: Volume II, (1969)]. This extremely conservative critical mass limit does not credit any neutron capture by chlorine (in particular neutron capture by 35 Cl) and greatly impedes the throughput required for current and future operations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

High-quality composite Pati-Salam axion

We present a composite QCD axion model where the Peccei-Quinn symmetry emerges as a high-quality, accidental symmetry. The axion potential is only modified by eight-fermion, dimension-12 operators, which if present at the Planck scale, allow for axion dark matter from misalignment while solving the strong 𝐶⁢𝑃 problem. The model is an SU⁡(𝑁 𝑐 ) gauge theory with ten flavors where the Pati-Salam unified subgroup SO⁡(6) × SO⁡(4) ⊂ SU⁢(10)𝐿 and Sp⁡(10) ⊂ SU⁢(10) 𝑅 are weakly gauged. The dynamics breaks SU⁢(10) 𝐿 × SU⁢(10) 𝑅 → SU⁢(10) 𝑉 and the weakly gauged groups to U⁡(3) × U⁡(2) ⊃ SU⁢(3) 𝑐 × SU⁢(2) 𝐿 × U⁡(1) 𝑌 , with the QCD axion identified as one of the Nambu-Goldstone bosons. This axion has a relatively large coupling to photons while a residual $\bar{𝜃}$ eff may be just below the current limit on the neutron electric dipole moment. If the dimension-12 operators are present near the grand unified theory scale, they can cause domain wall networks to decay, allowing for axion dark matter even for the postinflationary scenario.

Gherghetta, Tony [University of Minnesota, Minneap↗
DOE OSTI2021

Numerical Simulations of Time-Resolved Photoluminescence in CdSexTe1-x/CdTe Solar Cells

We present initial time-resolved photoluminescence (TRPL) simulations in graded CdSexTe1-e thin-film solar cells to quantify the front-interface recombination velocity, S int,front . Our model includes several composition dependences: bandgap energy, absorption coefficient, electron affinity, and carrier lifetime. Cathodoluminescence spectrum imaging measurements on bevels provide an estimate of the bandgap and the CdSe x Te 1-x alloy composition through the absorber thickness. TRPL decays are simulated as a function of the laser power, S int,front , front-interface band offset, and bulk Shockley-Read-Hall lifetime. We find the impact of S intf,ront on the PL decay increases as the band offset shifts from a "spike" to a "cliff". Recombination rate analysis shows that back-interface recombination could potentially dictate the later part of the TRPL decay "t 2" in high-lifetime CdSe x Te 1-x cells. We briefly discuss ongoing work to determine TRPL measurement conditions that maximize sensitivity to S itnt,front.

CdTe solar cells↗
DOE OSTI2020

Assessing the exposure of three diving bird species to offshore wind areas on the U.S. Atlantic Outer Continental Shelf using satellite telemetry

Abstract Aim The United States Atlantic Outer Continental Shelf (OCS) has considerable offshore wind energy potential. Capturing that resource is part of a broader effort to reduce CO 2 emissions. While few turbines have been constructed in U.S. waters, over a dozen currently planned offshore wind projects have the potential to displace marine birds, potentially leading to effective habitat loss. We focused on three diving birds identified in Europe to be vulnerable to displacement. Our research aimed to determine their potential exposure to areas designated or proposed for offshore wind development along the Atlantic OCS. Methods Satellite tracking technology was used to determine the spatial and temporal use and movement patterns of Surf Scoters ( Melanitta perspicillata ), Red‐throated Loons ( Gavia stellata ) and Northern Gannets ( Morus bassanus ), and calculate their exposure to each offshore wind area. We tagged 236 adults in 2012–2015 on the Atlantic OCS from New Jersey to North Carolina; an additional 147 birds tagged in previous tracking studies were integrated into our analyses. Tracking data were analysed in two‐week intervals using dynamic Brownian bridge movement models to develop composite spatial utilization distributions. For each species, these distributions were then used to calculate the spatio‐temporal exposure to each offshore wind area. Results Surf Scoters and Red‐throated Loons were exposed to offshore wind areas almost exclusively during migration because these species were distributed among coastal and inshore waters during winter months. In contrast, Northern Gannets ranged over a much larger area, reaching farther offshore and south in winter, thus exhibited the greatest exposure to extant offshore wind areas. Conclusions Results of this study provide better understanding of how diving birds use current and potential future offshore wind areas on the Atlantic OCS, and can inform permitting, risk assessment and pre‐ and post‐construction impact assessments of offshore energy infrastructure.

Stenhouse, Iain J.↗
DOE OSTI2025

Benchmarking large language models for materials synthesis: The case of atomic layer deposition

In this work, we introduce an open-ended question benchmark, ALDbench, to evaluate the performance of large language models (LLMs) in materials synthesis, and, in particular, in the field of atomic layer deposition, a thin film growth technique used in energy applications and microelectronics. Our benchmark comprises questions with a level of difficulty ranging from the graduate level to domain expert current with the state of the art in the field. Human experts reviewed the questions along the criteria of difficulty and specificity, and the model responses along four different criteria: overall quality, specificity, relevance, and accuracy. We ran this benchmark on an instance of OpenAI’s GPT-4o. The responses from the model received a composite quality score of 3.7 on a 1–5 scale, consistent with a passing grade. However, 36% of the questions received at least one below average score. An in-depth analysis of the responses identified at least five instances of suspected hallucination. Finally, we observed statistically significant correlations between the difficulty of the question and the quality of the response, the difficulty of the question and the relevance of the response, the specificity of the question, and the accuracy of the response as graded by the human experts. Furthermore, this emphasizes the need to evaluate LLMs across multiple criteria beyond difficulty or accuracy.

Artificial intelligence↗
DOE OSTI2021

OpenMC

OpenMC is an open source, community-developed framework for performing Monte Carlo particle transport calculations.It is capable of simulating neutron and photon transport below ~50 MeV and also includes a model for bremsstrahlung production of photons by electrons/positrons. Fixed source, k-eigenvalue, and subcritical multiplication problems can be solved. Problem geometries can be modeled either using constructive solid geometry or a CAD representation. A flexible and efficient tally system enables a wide variety of physical quantities to be tallied and analyzed. OpenMC can run in parallel using a hybrid MPI and OpenMP programming model and has been extensively tested on leadership class supercomputers. A built-in Bateman equation solver enables the modeling of material composition changes due to irradiation. One of the unique features of OpenMC is its rich, extensible Python and C/C++ programming interfaces that enable programming pre- and post-processing, multigroup cross section generation, workflow automation, multiphysics coupling, and the visualization of geometry and tally results. In addition to the core Monte Carlo transport solver and associated APIs, OpenMC includes a Python-based nuclear data interface that enables power users to inspect, modify,and perform various types of nuclear data processing on ENDF, ACE, and OpenMC¿s native HDF5 files

ROMANO, PaulK.↗
DOE OSTI2022

CRADA NO. NFE-22-00001 Between CNS and Northrop Grumman Systems Corporation

Consolidated Nuclear Security, LLC (CNS) and Northrop Grumman Systems Corporation (NGC) have established a partnership through the subject Cooperative Research and Development Agreement (CRADA) in three areas of collaboration: (1) Additive Manufacturing (AM) of manufactured carbon-carbon composite materials, (2) modeling and simulation, and (3) specialized chip and circuit board manufacturing for supply chain assurance.

36 MATERIALS SCIENCE↗