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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Correlating processing variables to material properties in recycled polypropylene: A data‐driven approach

Abstract Polypropylene (PP) is one of the most widely used plastics, yet its recycling remains limited, with less than 1% of solid waste PP being reprocessed. Mechanical recycling through extrusion is the most practical method, but inconsistent reprocessing conditions introduce variability in material properties. While temperature, screw speed, and residence time influence the thermomechanical stress applied during reprocessing, there are no standardized guidelines for optimizing these parameters. This study examines how these factors shape the properties of recycled PP, using conditions designed to mimic post‐industrial recycled (PIR) scrap. Residence time was measured using colorimetric tracking and correlated with molecular weight, viscosity, and mechanical properties over multiple extrusion cycles. Data‐driven modeling, including response surface methodology, support vector machines, and artificial neural networks, identified processing temperature as the dominant factor in material degradation, followed by residence time. Mechanical properties remained stable, while viscosity decreased predictably with increasing residence time. By linking reprocessing conditions to property evolution, this study provides a method to optimize processing parameters and reduce variability in recycled PP. These findings help manufacturers improve process control, making recycled PP more predictable for reuse in manufacturing. Highlights Study of PIR‐quality PP without additives or compatibilizers. Residence time analysis shows processing temperature drives PP property changes. Mark‐Houwink enables quick molecular weight checks for quality control. Models predict mechanical and rheological shifts in reprocessing. Optimized processing parameters minimize property degradation in recycling.

Estela‐García, John E. [Polymer Engineering Center↗
DOE OSTI2026

PlantCV v4: Image analysis software for high‐throughput plant phenotyping

PlantCV is an open-source Python project aimed at developing tools to address a range of image-based, plant phenotyping questions. PlantCV has been used for more than 10 years to automate trait collection from image data, and the newest release, PlantCV version 4, continues to lower the barrier to entry for users without substantial coding experience through extensive example use-case tutorials and simplified installation. In addition to usability, we document added functionality since the release of PlantCV v2, including support for more image types such as fluorescence, thermal, and hyperspectral data. Finally, we describe the development of a new subpackage focused on morphological trait measurements like leaf angle, and demonstrate its utility as compared to more manual methods of data collection.

Schuhl, Haley [Donald Danforth Plant Science Cente↗
DOE OSTI2026

A New Electrode Paradigm Enabled by Co-Axial Electrospinning

A conventional electrode in a polymer electrolyte membrane fuel cell (PEMFC) often imposes competing requirements on the ionomer, which must enable efficient proton conduction while allowing sufficient oxygen transport. To address these material-level requirements, a co-axial electrospun electrode comprising of a pristine ionomer core and a multifunctional platinum-carbon-ionomer shell is introduced. By decoupling proton and oxygen transport pathways, this architecture enables independent tailoring of core and shell chemistries and their interfaces. The core-shell structure of the electrospun fibers is confirmed by microscopy, while electrochemical and transport properties are quantified using electrochemical impedance spectroscopy and limiting-current diagnostics. The co-axial fibers in their current version meet or exceed the performance of conventional ultrasonically sprayed electrode at relative humidities above 75%, enabled by improvements in non-Fickian diffusion processes. This work establishes co-axial electrospun electrodes as a versatile platform for advanced PEMFC electrodes and a wide range of electrochemical applications, including CO2 electrolysis, water electrolysis, and critical mineral separations.

08 HYDROGEN↗
DOE OSTI2024

Metal Oxide vs Organic Semiconductor Charge Extraction Layers for Halide Perovskite Indoor Photovoltaics

Halide perovskite indoor photovoltaics (PVs) are highly promising to autonomously power the billions of microelectronic sensors in the emerging and disruptive technology of the Internet of Things (IoT). However, how the wide range of different types of hole extraction layers (HELs) impacts the indoor light harvesting of perovskite solar cells is still elusive, which hinders the material selection and industrial–scale fabrication of indoor perovskite photovoltaics. In the present study, new insights are provided regarding the judicial selection of HELs at the buried interface of halide perovskite indoor photovoltaics. This study unravels the detrimental and severe light–soaking effect of metal oxide transport layer–based PV devices under the indoor lighting effect for the first time, which then necessitates the interface passivation/engineering for their reliant performance. This is not a stringent criterion under 1 sun illumination. By systematically investigating the charge carrier dynamics and sequence of measurements from dark, light–soaked, interlayer–passivated device, the bulk and interface defects are decoupled and reveal the gradual defect passivation from shallow to deep level traps. Thus, the present study puts forward a useful design strategy to overcome the deleterious effect of metal oxide HELs and employ them in halide perovskite indoor PVs.

14 SOLAR ENERGY↗
DOE OSTI2025

Revealing the Crystallization Pathways of Mixed‐Halide Low‐Dimensional Perovskites: A First Step Toward Solar Cell Applications

Ruddlesden–Popper perovskites (RPPs) are promising materials for optoelectronic devices. While iodide‐based RPPs are well‐studied, the crystallization of mixed‐halide RPPs remains less explored. Understanding the factors affecting their formation and crystallization are vital for optimizing morphology, phase purity, and orientation, which directly impact device performance. Here, we investigate the crystallization and properties of mixed‐halide RPPs (PEA) 2 FA n−1 Pb n (Br 1/3 I 2/3 ) 3n + 1 (PEA = C 6 H 5 (CH 2 ) 2 NH 3 + and FA = CH(NH 2 ) 2 + ) (n = 1, 5, 10) using DMSO ((CH 3 ) 2 SO) or NMP (OC 4 H 6 NCH 3 ) as cosolvents and MACl (MA = CH 3 NH 3 + ) as an additive. For the first time, the presence of planar defects in RPPs is directly observed by in situ grazing‐incidence wide‐angle X‐ray scattering (GIWAXS) and confirmed through the simulation of the patterns that matched the experimental. GIWAXS data also reveals that DMSO promotes higher crystallinity and vertical orientation, while MACl enhances crystal quality but increases halide segregation, shown here by nano X‐ray fluorescence (nano‐XRF) experiments. For low‐n RPPs, orientation is crucial for solar cell efficiency, but its impact decreases with increasing n. Our findings provide insights into optimizing mixed‐halide RPPs, guiding strategies to improve crystallization, phase control, and orientation for better performance not only in solar cells but also in other potential optoelectronic devices.

Guaita, Maria G D↗
DOE OSTI2023

Isospin-breaking corrections to light-meson leptonic decays from lattice simulations at physical quark masses

The decreasing uncertainties in theoretical predictions and experimental measurements of several hadronic observables related to weak processes, which in many cases are now smaller than O(1%), require theoretical calculations to include subleading corrections that were neglected so far. Precise determinations of leptonic and semi-leptonic decay rates, including QED and strong isospin-breaking effects, can play a central role in solving the current tensions in the first-row unitarity of the CKM matrix. In this work we present the first RBC/UKQCD lattice calculation of the isospin-breaking corrections to the ratio of leptonic decay rates of kaons and pions into muons and neutrinos. The calculation is performed at fixed lattice spacing (a –1 ≃ 1.730 GeV) on a 48 3 × 96 volume with N f = 2 + 1 dynamical quarks close to the physical point and domain wall fermions in the Möbius formulation are employed. Long-distance QED interactions are included according to the QED L prescription and the crucial role of finite-volume electromagnetic corrections in the determination of leptonic decay rates, which produce a large systematic uncertainty, is extensively discussed. Finally, we study the different sources of uncertainty on |V us |/|V ud | and observe that, if finite-volume systematics can be reduced, the error from isospin-breaking corrections is potentially sub-dominant in the final precision of the ratio of the CKM matrix elements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Hadronic mono- W ' probes of dark matter at colliders

Particle collisions at the energy frontier can probe the nature of invisible dark matter via production in association with recoiling visible objects. We propose a new potential production mode, in which dark matter is produced by the decay of a heavy dark Higgs boson radiated from a heavy W' boson. In such a model, motivated by left-right symmetric theories, dark matter would not be pair produced in association with other recoiling objects due to its lack of direct coupling to quarks or gluons. We study the hadronic decay mode via W' → tb and estimate the LHC exclusion sensitivity at 95% confidence level to be 10 2 - 10 5 fb for W' boson masses between 250 and 1750 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Combination of the W boson polarization measurements in top quark decays using ATLAS and CMS data at $\sqrt{s} =$ 8 TeV

The combination of measurements of the W boson polarization in top quark decays performed by the ATLAS and CMS collaborations is presented. The measurements are based on proton-proton collision data produced at the LHC at a centre-of-mass energy of 8 TeV, and corresponding to an integrated luminosity of about 20 fb$^{−1}$ for each experiment. The measurements used events containing one lepton and having different jet multiplicities in the final state. The results are quoted as fractions of W bosons with longitudinal (F$_{0}$), left-handed (F$_{L}$), or right-handed (F$_{R}$) polarizations. The resulting combined measurements of the polarization fractions are F$_{0}$ = 0.693 ± 0.014 and F$_{L}$ = 0.315 ± 0.011. The fraction F$_{R}$ is calculated from the unitarity constraint to be F$_{R}$ = −0.008 ± 0.007. These results are in agreement with the standard model predictions at next-to-next-to-leading order in perturbative quantum chromodynamics and represent an improvement in precision of 25 (29)% for F$_{0}$ (F$_{L}$) with respect to the most precise single measurement. A limit on anomalous right-handed vector (V$_{R}$), and left- and right-handed tensor (g$_{L}$, g$_{R}$) tWb couplings is set while fixing all others to their standard model values. The allowed regions are [−0.11, 0.16] for V$_{R}$, [−0.08, 0.05] for g$_{L}$, and [−0.04, 0.02] for g$_{R}$, at 95% confidence level. Limits on the corresponding Wilson coefficients are also derived.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Modelling and computational improvements to the simulation of single vector-boson plus jet processes for the ATLAS experiment

This paper presents updated Monte Carlo configurations used to model the production of single electroweak vector bosons (W, Z/γ$^{∗}$) in association with jets in proton-proton collisions for the ATLAS experiment at the Large Hadron Collider. Improvements pertaining to the electroweak input scheme, parton-shower splitting kernels and scale-setting scheme are shown for multi-jet merged configurations accurate to next-to-leading order in the strong and electroweak couplings. The computational resources required for these set-ups are assessed, and approximations are introduced resulting in a factor three reduction of the per-event CPU time without affecting the physics modelling performance. Continuous statistical enhancement techniques are introduced by ATLAS in order to populate low cross-section regions of phase space and are shown to match or exceed the generated effective luminosity. This, together with the lower per-event CPU time, results in a 50% reduction in the required computing resources compared to a legacy set-up previously used by the ATLAS collaboration. The set-ups described in this paper will be used for future ATLAS analyses and lay the foundation for the next generation of Monte Carlo predictions for single vector-boson plus jets production.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Distinctive signals of frustrated dark matter

We study a renormalizable model of Dirac fermion dark matter (DM) that communicates with the Standard Model (SM) through a pair of mediators — one scalar, one fermion — in the representation (6, 1, $\frac{4}{3}$) of the SM gauge group SU(3) c x SU(2) L x U(1) Y . While such assignments preclude direct coupling of the dark matter to the Standard Model at tree level, we examine the many effective operators generated at one-loop order when the mediators are heavy, and find that they are often phenomenologically relevant. We reinterpret dijet and pair-produced resonance and jets + E$^{miss}_{T}$ searches at the Large Hadron Collider (LHC) in order to constrain the mediator sector, and we examine an array of DM constraints ranging from the observed relic density Ω χ h$^{2}_{Planck}$ to indirect and direct searches for dark matter. Tree-level annihilation, available for DM masses starting at the TeV scale, is required in order to produce Ω χ h$^{2}_{Planck}$ through freeze-out, but loops — led by the dimension-five DM magnetic dipole moment — are nonetheless able to produce signals large enough to be constrained, particularly by the XENON1T experiment. In some benchmarks, we find a fair amount of parameter space left open by experiment and compatible with freeze-out. In other scenarios, however, the open space is quite small, suggesting a need for further model-building and/or non-standard cosmologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Resurrecting low-mass axion dark matter via a dynamical QCD scale

In the framework where the strong coupling is dynamical, the QCD sector may confine at a much higher temperature than it would in the Standard Model, and the temperature-dependent mass of the QCD axion evolves in a non-trivial way. We find that, depending on the evolution of Λ QCD , the axion field may undergo multiple distinct phases of damping and oscillation leading generically to a suppression of its relic abundance. Such a suppression could therefore open up a wide range of parameter space, resurrecting in particular axion dark-matter models with a large Peccei-Quinn scale f a $\gg$ 10 12 GeV, i.e., with a lighter mass than the standard QCD axion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

3D Time-Lapse Electrical Resistivity Imaging of Rock Damage Patterns and Gas Flow Paths Resulting from Two Underground Chemical Explosions

Abstract Rock damage from underground nuclear explosions (UNEs) has a strong influence on sub-surface gas movement and on seismic waveform characteristics, both of which are used to detect UNEs. Although advanced numerical simulation capabilities exist to predict rock damage patterns and corresponding detection signals, those predictions are dependent on (generally) unknown properties of the host rock. For example, the effects of in-situ mechanical heterogeneities on the explosively generated damage/fractures that provide gas flow pathways to the surface are not well understood, due largely to the difficulty in accessing and characterizing the near-source region. In this paper we demonstrate the emerging use of electrical resistivity tomography (ERT) for imaging rock damage and gas flow patterns resulting from two relatively small-scale underground chemical explosions. Pre-explosion ERT and crosshole seismic imaging revealed a natural fracture zone within the test bed. Post-explosion imaging revealed that the damage zone was non-symmetric and was focused primarily within the pre-existing fracture zone, located 10 m above the first explosion and 5 m above the second explosion. Time-lapse ERT imaging of heated air injected into the detonation borehole revealed the primary gas flow paths to be within the upper margin of the same primary damage zone. These results point to the utility of ERT imaging for understanding rock damage and gas flow patterns under experimental conditions, and to the importance of understanding the effects of geologic heterogeneity on UNE detection signals, particularly gas surface breakthrough times.

58 GEOSCIENCES↗
DOE OSTI2022

aphBO-2GP-3B: a budgeted asynchronous parallel multi-acquisition functions for constrained Bayesian optimization on high-performing computing architecture

High-fidelity complex engineering simulations are often predictive, but also computationally expensive and often require substantial computational efforts. The mitigation of computational burden is usually enabled through parallelism in high-performance cluster (HPC) architecture. Optimization problems associated with these applications is a challenging problem due to the high computational cost of the high-fidelity simulations. In this paper, an asynchronous parallel constrained Bayesian optimization method is proposed to efficiently solve the computationally expensive simulation-based optimization problems on the HPC platform, with a budgeted computational resource, where the maximum number of simulations is a constant. The advantage of this method are three-fold. Firstly, the efficiency of the Bayesian optimization is improved, where multiple input locations are evaluated parallel in an asynchronous manner to accelerate the optimization convergence with respect to physical runtime. This efficiency feature is further improved so that when each of the inputs is finished, another input is queried without waiting for the whole batch to complete. Second, the proposed method can handle both known and unknown constraints. Third, the proposed method samples several acquisition functions based on their rewards using a modified GP-Hedge scheme. The proposed framework is termed aphBO-2GP-3B, which means asynchronous parallel hedge Bayesian optimization with two Gaussian processes and three batches. The numerical performance of the proposed framework aphBO-2GP-3B is comprehensively benchmarked using 16 numerical examples, compared against other 6 parallel Bayesian optimization variants and 1 parallel Monte Carlo as a baseline, and demonstrated using two real-world high-fidelity expensive industrial applications. The first engineering application is based on finite element analysis (FEA) and the second one is based on computational fluid dynamics (CFD) simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Peatland Microbial Community Composition Is Driven by a Natural Climate Gradient

Peatlands are important players in climate change–biosphere feedbacks via long-term net carbon (C) accumulation in soil organic matter and as potential net C sources including the potent greenhouse gas methane (CH 4 ). Interactions of climate, site-hydrology, plant community, and groundwater chemical factors influence peatland development and functioning, including C dioxide (CO 2 ) and CH 4 fluxes, but the role of microbial community composition is not well understood. To assess microbial functional and taxonomic dissimilarities, we used high throughput sequencing of the small subunit ribosomal DNA (SSU rDNA) to determine bacterial and archaeal community composition in soils from twenty North American peatlands. Targeted DNA metabarcoding showed that although Proteobacteria, Acidobacteria, and Actinobacteria were the dominant phyla on average, intermediate and rich fens hosted greater diversity and taxonomic richness, as well as an array of candidate phyla when compared with acidic and nutrient-poor poor fens and bogs. Moreover, pH was revealed to be the strongest predictor of microbial community structure across sites. Predictive metagenome content (PICRUSt) showed increases in specific genes, such as purine/pyrimidine and amino-acid metabolism in mid-latitude peatlands from 38 to 45° N, suggesting a shift toward utilization of microbial biomass over utilization of initial plant biomass in these microbial communities. Overall, there appears to be noticeable differences in community structure between peatland classes, as well as differences in microbial metabolic activity between latitudes. Finally, these findings are in line with a predicted increase in the decomposition and accelerated C turnover, and suggest that peatlands north of 37° latitude may be particularly vulnerable to climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The Ontology of Biological Attributes (OBA)—computational traits for the life sciences

Abstract Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

59 BASIC BIOLOGICAL SCIENCES↗