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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Fermi Level Engineering of Passivation and Electron Transport Materials for p-Type CuBi 2 O 4 Employing a High-Throughput Methodology

Metal oxide semiconductors are promising for solar photochemistry if the issues of excessive charge carrier recombination and material degradation can be resolved, which are both influenced by surface quality and interface chemistry. Coating the semiconductor with an overlayer to passivate surface states is a common remedial strategy but is less desirable than application of a functional coating that can improve carrier extraction and reduce recombination while mitigating corrosion. Here, a data-driven materials science approach utilizing high-throughput methodologies, including inkjet printing and scanning droplet electrochemical cell measurements, is used to create and evaluate multi-element coating libraries to discover new classes of candidate passivation and electron-selective contact materials for p-type CuBi 2 O 4 . The optimized overlayer (Cu 1.5 TiO z ) improves the onset potential by 110 mV, the photocurrent by 2.8×, and the absorbed photon-to-current efficiency by 15.5% compared to non-coated photoelectrodes. It is shown that these enhancements are related to reduced surface recombination through passivation of surface defect states as well as improved carrier extraction efficiency through Fermi level engineering. This work presents a generalizable, high-throughput method to design and optimize passivation materials for a variety of semiconductors, providing a powerful platform for development of high-performance photoelectrodes for incorporation into solar-fuel generation systems.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Application of Novel Adsorbent Prepared by Mucor hiemalis Biomass Impregnated with Calcium Alginate for Removal of Sr{sup 2+} from Aqueous Solutions

In this research, a novel biosorbent was prepared by Mucor hiemalis biomass combined with calcium alginate (Mucor hiemalis/Alg-Ca). The dead biomass was entrapped into alginate gel by curing method in the presence of Ca{sup 2+} ions. The synthesized biosorbent characterized by XRD, EDAX, BET, FTIR, and SEM techniques was used for removal of Sr{sup 2+} from aquatic streams under various experimental conditions and the optimized adsorption capacity of 140 mg g{sup −1} was obtained. The selectivity of the adsorbent towards Sr{sup 2+} studied in the presence of Na{sup +}, Cs{sup +}, Ca{sup 2+} and Mg{sup 2+} was reasonably high. The adsorption process was kinetically fast and the equilibrium was established within 60 min, and followed the pseudo-second order kinetics model. The equilibrium data was well described by Langmuir isotherm model. The thermodynamics parameters (∆G°, ∆H° and ∆S°) of the process were determined. Positive ∆H° and negative ∆G° were indicative of the endothermic and spontaneous nature of the adsorption process. Graphical Abstract: .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Cost impact of hexose-to-pentose sugar ratios for biomanufacturing

Central to the long-term vision for biomanufacturing is the ability to deconstruct plant cell walls to sugars that microbes can convert to products. Aside from glucose, the most abundant sugar in biomass is xylose, a pentose sugar. Industrially relevant microbes have been engineered to co-ferment xylose and glucose. Most nth plant technoeconomic analyses (TEAs) assume similar consumption rates and product yields for both sugars, but in reality, xylose is consumed more slowly. Feedstocks can be selected, or engineered, to alter the glucan-to-xylan ratio (GXR) but no TEAs have quantified the impact of this strategy systematically. This study explores the cost impacts of varying the glucan-to-xylan ratio (GXR) from 1.9 to 6.7 for co-fermenting glucose and xylose to ethanol and bisabolene. The minimum selling prices (MSPs) for both products decrease as the GXR increases, with the largest reductions at shorter residence times. For instance, with an increase in GXR from 1.9 to 6.7, ethanol’s MSP drops by 16 %, 5 %, and 3 % at 24, 72, and 144 h, respectively, while bisabolene’s MSP declines by 23 %, 20 %, and 15 % at 24, 72, and 120 h. Particularly for early-stage commercialization, the results suggest that altering or selecting for feedstocks with higher GXR can minimize capital costs by reducing optimal residence times. Capital-constrained biorefineries operating with shorter residence times can justify paying up to 1.5X to 2X the price for feedstocks with a higher GXR, based on the expected improvements in their product yield and overall process economics.

Delayed xylose utilization↗
DOE OSTI2024

Glass Design Using Machine Learning Property Models with Prediction Uncertainties: Nuclear Waste Glass Formulation

The United States Department of Energy is responsible for managing the legacy nuclear waste stored in underground tanks at the Hanford Site. The waste will be separately vitrified as low-activity waste and high-level waste fractions. Waste glass formulation algorithms have been traditionally developed using partial quadratic mixture property-composition models. Recently, machine learning (ML) techniques have been used to predict glass properties and discover new glass materials for nuclear waste vitrification, and these advancements can be utilized to improve waste glass composition design. In this proof-of-principle study, ML algorithms such as Gaussian process regression (GPR) were used to interpolate glass properties (e.g., viscosity, electrical conductivity, chemical durability). After selecting appropriate sets of GPR hyper-parameters for each property, an optimization program was developed to formulate glass compositions to maximize waste loading while simultaneously satisfying property within constraints. The results of the ML-based waste loadings and glass compositions were compared to those obtained using the traditional methods. Comparing to the previous glass design framework, the ML-based optimization methods offer improved glass designs and a streamlined approach to generation of optimally designed data and near real-time updates.

glass formulation, machine learning, constraints, ↗
DOE OSTI2016

Design and Synthesis of a Pan-Janus Kinase Inhibitor Clinical Candidate (PF-06263276) Suitable for Inhaled and Topical Delivery for the Treatment of Inflammatory Diseases of the Lungs and Skin

By use of a structure-based computational method for identification of structurally novel Janus kinase (JAK) inhibitors predicted to bind beyond the ATP binding site, a potent series of indazoles was identified as selective pan-JAK inhibitors with a type 1.5 binding mode. Furthermore, optimization of the series for potency and increased duration of action commensurate with inhaled or topical delivery resulted in potent pan-JAK inhibitor 2 (PF-06263276), which was advanced into clinical studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

High-Affinity Peptidomimetic Inhibitors of the DCN1-UBC12 Protein–Protein Interaction

Cullin-RING ligases (CRLs) regulate the turnover of approximately 20% of the proteins in mammalian cells and are emerging therapeutic targets in human diseases. The activation of CRLs requires the neddylation of their cullin subunit, which is controlled by an activation complex consisting of Cullin-RBX1-UBC12-NEDD8-DCN1. In this paper, we describe the design, synthesis, and evaluation of peptidomimetics targeting the DCN1-UBC12 protein–protein interaction. Starting from a 12-residue UBC12 peptide, we have successfully obtained a series of peptidomimetic compounds that bind to DCN1 protein with KD values of <10 nM. Determination of a cocrystal structure of a potent peptidomimetic inhibitor complexed with DCN1 provides the structural basis for their high-affinity interaction. Cellular investigation of one potent DCN1 inhibitor, compound 36 (DI-404), reveals that it effectively and selectively inhibits the neddylation of cullin 3 over other cullin members. Further optimization of DI-404 may yield a new class of therapeutics for the treatment of human diseases in which cullin 3 CRL plays a key role.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Isolated single atom cobalt in Bi 3 O 4 Br atomic layers to trigger efficient CO 2 photoreduction

The design of efficient and stable photocatalysts for robust CO 2 reduction without sacrifice reagent or extra photosensitizer is still challenging. Herein, a single-atom catalyst of isolated single atom cobalt incorporated into Bi 3 O 4 Br atomic layers is successfully prepared. The cobalt single atoms in the Bi 3 O 4 Br favors the charge transition, carrier separation, CO 2 adsorption and activation. It can lower the CO 2 activation energy barrier through stabilizing the COOH* intermediates and tune the rate-limiting step from the formation of adsorbed intermediate COOH* to be CO* desorption. Taking advantage of cobalt single atoms and two-dimensional ultrathin Bi 3 O 4 Br atomic layers, the optimized catalyst can perform light-driven CO 2 reduction with a selective CO formation rate of 107.1 µmol g –1 h –1 , roughly 4 and 32 times higher than that of atomic layer Bi 3 O 4 Br and bulk Bi 3 O 4 Br, respectively.

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

Coordination environment tuning of nickel sites by oxyanions to optimize methanol electro-oxidation activity

To achieve zero-carbon economy, advanced anode catalysts are desirable for hydrogen production and biomass upgrading powered by renewable energy. Ni-based non-precious electrocatalysts are considered as potential candidates because of intrinsic redox attributes, but in-depth understanding and rational design of Ni site coordination still remain challenging. Here, we perform anodic electrochemical oxidation of Ni-metalloids (NiP x , NiS x , and NiSe x ) to in-situ construct different oxyanion-coordinated amorphous nickel oxyhydroxides (NiOOH-TO x ), among which NiOOH-PO x shows optimal local coordination environment and boosts electrocatalytic activity of Ni sites towards selective oxidation of methanol to formate. Experiments and theoretical results demonstrate that NiOOH-PO x possesses improved adsorption of OH* and methanol, and favors the formation of CH 3 O* intermediates. The coordinated phosphate oxyanions effectively tailor the d band center of Ni sites and increases Ni-O covalency, promoting the catalytic activity. This study provides additional insights into modulation of active-center coordination environment via oxyanions for organic molecules transformation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Integrating novel stellarator single-stage optimization algorithms to design the Columbia stellarator experiment

Abstract The Columbia Stellarator eXperiment (CSX), currently being designed at Columbia University, aims to test theoretical predictions related to QA plasma behavior, and to pioneer the construction of an optimized stellarator using three-dimensional, non-insulated high-temperature superconducting (NI-HTS) coils. The magnetic configuration is generated by a combination of two circular planar poloidal field (PF) coils and two 3D-shaped interlinked (IL) coils, with the possibility to add windowpane coils to enhance shaping and experimental flexibility. The PF coils and vacuum vessel are repurposed from the former Columbia Non-Neutral Torus experiment, while the IL coils will be custom-wound in-house using NI-HTS tapes. To obtain a plasma shape that meets the physics objectives with a limited number of coils, novel single-stage optimization techniques are employed, optimizing both the plasma and coils concurrently, in particular targeting a tight aspect ratio QA plasma and minimized strain on the HTS tape. Despite the increased complexity due to the expanded degrees of freedom, these methods successfully identify optimized plasma geometries that can be realized by coils meeting engineering specifications. This paper discusses the derivation of the constraints and objectives specific to CSX, and describe how two recently developed single-stage optimization methodologies are applied to the design of CSX. A set of selected configurations for CSX is then described in detail.

Baillod, A. (ORCID:0000000303529180)↗
DOE OSTI2020

Supernova host galaxies in the dark energy survey: I. Deep coadds, photometry, and stellar masses

ABSTRACT The 5-yr Dark Energy Survey Supernova Programme (DES-SN) is one of the largest and deepest transient surveys to date in terms of volume and number of supernovae. Identifying and characterizing the host galaxies of transients plays a key role in their classification, the study of their formation mechanisms, and the cosmological analyses. To derive accurate host galaxy properties, we create depth-optimized coadds using single-epoch DES-SN images that are selected based on sky and atmospheric conditions. For each of the five DES-SN seasons, a separate coadd is made from the other four seasons such that each SN has a corresponding deep coadd with no contaminating SN emission. The coadds reach limiting magnitudes of order ∼27 in g band, and have a much smaller magnitude uncertainty than the previous DES-SN host templates, particularly for faint objects. We present the resulting multiband photometry of host galaxies for samples of spectroscopically confirmed type Ia (SNe Ia), core-collapse (CCSNe), and superluminous (SLSNe) as well as rapidly evolving transients (RETs) discovered by DES-SN. We derive host galaxy stellar masses and probabilistically compare stellar-mass distributions to samples from other surveys. We find that the DES spectroscopically confirmed sample of SNe Ia selects preferentially fewer high-mass hosts at high-redshift compared to other surveys, while at low redshift the distributions are consistent. DES CCSNe and SLSNe hosts are similar to other samples, while RET hosts are unlike the hosts of any other transients, although these differences have not been disentangled from selection effects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Review of Particle Physics

The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 3,324 new measurements from 878 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on High Energy Soft QCD and Diffraction and one on the Determination of CKM Angles from B Hadrons. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 98 review articles. Volume 2 consists of the Particle Listings and contains also 22 reviews that address specific aspects of the data presented in the Listings. The complete Review (both volumes) is published online on the website of the Particle Data Group (pdg.lbl.gov) and in a journal. Volume 1 is available in print as the PDG Book. A Pariicle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print and as a web version optimized for use on phones as well as an Android app.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Chemically Synthesized Gold and Silver Particles Absorbing in the Near-IR Spectral Range

We propose methods for creating spherical gold particles of submicron size and silver rod-like particles with transverse dimensions of ~10 nm and an aspect ratio of 1: 10. Factors determining the frequency of plasmon resonances are considered, reagents are selected, and their ratios for obtaining prolate silver particles are determined. An optimal concentration of the surfactant is determined for creating most elongated silver particles. A shift of the plasmon absorption toward the near-IR range of the spectrum is obtained.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Synchronous and Concurrent Multidomain Computing Method for Cloud Computing Platforms

We present a numerical method for synchronous and concurrent solution of transient elastodynamics problem where the computational domain is divided into subdomains that may reside on separate computational platforms. Here, this work employs the variational multiscale discontinuous Galerkin (VMDG) method to develop interdomain transmission conditions for transient problems. The fine-scale modeling concept leads to variationally consistent coupling terms at the common interfaces. The method admits a large class of time discretization schemes, and decoupling of the solution for each subdomain is achieved by selecting any explicit algorithm. Numerical tests with a manufactured solution problem show optimal convergence rates. The energy history in a free vibration problem is in agreement with that of the solution from a monolithic computational domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Accurate, Fast and Scalable Kernel Ridge Regression on Parallel and Distributed Systems

Kernel Ridge Regression (KRR) is a fundamental method in machine learning. Given an n-by-d data matrix as input, a traditional implementation requires Θ(n2) memory to form an n-by-n kernel matrix and Θ(n3) flops to compute the final model. These time and storage costs prohibit KRR from scaling up to large datasets. For example, even on a relatively small dataset (a 520k-by-90 input requiring 357 MB), KRR requires 2 TB memory just to store the kernel matrix. Additionally, the reason is that n usually is much larger than d for real-world applications. On the other hand, weak scaling becomes a problem: if we keep d and n/p fixed as p grows (p is # machines), the memory needed grows as Θ(p) per processor and the flops as Θ(p2) per processor. In the perfect weak scaling situation, both the memory needed and the flops grow as Θ(1) per processor (i.e. memory and flops are constant). The traditional Distributed KRR implementation (DKRR) only achieved 0.32% weak scaling efficiency from 96 to 1536 processors. In this work, we propose two new methods to address these problems: the Balanced KRR (BKRR) and K-means KRR (KKRR). These methods consider alternative ways to partition the input dataset into p different parts, generating p different models, and then selecting the best model among them. Compared to a conventional implementation, KKRR2 (optimized version of KKRR) improves the weak scaling efficiency from 0.32% to 38% and achieves a 591x speedup for getting the same accuracy by using the same data and the same hardware (1536 processors). BKRR2 (optimized version of BKRR) achieves a higher accuracy than the current fastest method using less training time for a variety of datasets. For the applications requiring only approximate solutions, BKRR2 improves the weak scaling efficiency to 92% and achieves 3505x speedup (theoretical speedup: 4096x).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Electrochemistry of the Arrow Poison, Tubocurarine, Using Boron Doped Diamond Electrode: Experimental and Theoretical Approaches

In present work boron doped diamond (BDD) electrode was applied for studying electrochemical behavior, as well as for quantitative determination of natural alkaloid, tubocurarine (arrow poison/ TUB). Electrochemical behavior was investigated using several organic solvents and aqueous buffers, at different pHs, as supporting electrolytes. After selection of the most appropriate supporting electrolyte and investigation of its electrochemical behavior, analytical procedures for quantitative analysis of TUB were developed in an acetonitrile/methanol (80:20) mixture and in 1 mol L−1 nitric acid, which had linear quantification ranges from 4 × 10−6 to 1 × 10−4 mol L−1 (LOD = 3.07 × 10−6 mol L−1) and 4 × 10−6 to 9 × 10−5 mol L−1 (LOD = 2.45 × 10−6 mol L−1 and 5.28 × 10−7 mol L−1, depending on the selected peak), respectively. The oxidation mechanism of TUB was proposed from the theoretical aspect. Remarkable selectivity and good sensitivity were obtained after the TUB quantification method was optimized, allowing application of the developed method for TUB quantification in biological fluids, with excellent reproducibility, accuracy and precision.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Experimental study of airpath electrification in an opposed-piston two stroke (OP2S) engine architecture

The opposed-piston two stroke (OP2S) engine shows potential as an alternative engine architecture to the conventional four stroke engine due to its high-power density, thermal efficiency, and versatile airpath management system. Since the pistons of a two-stroke engine do not pump the air into and out of the cylinder like in a four-stroke engine, the selection of the air induction devices and airpath actuators becomes critical to optimize engine performance. Both the pumping losses and the in-cylinder combustion process can be affected by the scavenging process in a two-stroke engine. Therefore, this study compares two different airpath configurations for the same family of OP2S engines and investigates performance metrics like scavenging control, pumping work, net indicated and brake efficiencies, and engine-out emissions associated with each airpath. Data was collected on a 3.2 L, two-cylinder OP2S engine with an electrically assisted turbocharger (EAT) and a 4.9 L displacement, three-cylinder engine with a variable geometry turbocharger (VGT) and a supercharger. The experiments consisted of speed and load sweeps for both engines at the same operating conditions to compare scavenge control in both architectures. For the three-cylinder layout, the SE sweep range was much higher, and the intake pressure could be independently varied with air flowrate, thus providing more flexibility for scavenging control. The supercharger and the VGT usage was optimized based on its efficiency map and thus, this layout had lower pumping losses compared to the EAT. The two-cylinder engine had a higher overall SE as compared to the three-cylinder engine, but the intake pressure and air flowrate could not be decoupled, leading to over scavenging and increased short circuiting of fresh charge into the exhaust.

Bhatt, Ankur [Clemson University, Clemson, SC, USA↗
DOE OSTI2017

Isolating GaSb membranes grown metamorphically on GaAs substrates using highly selective substrate removal etch processes

The etch rates of NH 4 OH:H 2 O 2 and C 6 H 8 O 7 :H 2 O 2 for GaAs and GaSb have been investigated to develop a selective etch for GaAs substrates and to isolate GaSb epilayers grown on GaAs. The NH 4 OH:H 2 O 2 solution has a greater etch rate differential for the GaSb/GaAs material system than C 6 H 8 O 7 :H 2 O 2 solution. The selectivity of NH 4 OH:H 2 O 2 for GaAs/GaSb under optimized etch conditions has been observed to be as high as 11471 ± 1691 whereas that of C 6 H 8 O 7 :H 2 O 2 has been measured up to 143 ± 2. The etch contrast has been verified by isolating 2 μm thick GaSb epi-layers that were grown on GaAs substrates. GaSb membranes were tested and characterized with high-resolution X-Ray diffraction (HR-XRD) and atomic force microscopy (AFM).

36 MATERIALS SCIENCE↗
DOE OSTI2026

A reproducible study design for the MIMIC-IV in-hospital mortality task

Open, tabular electronic health record (EHR) datasets such as MIMIC-III and MIMIC-IV have become critical resources for developing machine learning (ML) models addressing clinical prediction tasks, including hospital readmission, length of stay, and in-hospital mortality (IHM). While MIMIC-III has benefited from well-established preprocessing pipelines and standardized feature sets, MIMIC-IV remains comparatively challenging to work with because there are no standardized benchmarks to support reproducibility and comparability across studies. To address this limitation, we present a rigorously curated MIMIC-IV custom feature set optimized for IHM prediction, constructed through a reproducible preprocessing pipeline and feature selection strategy.

97 MATHEMATICS AND COMPUTING↗