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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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All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2025

An Innovative High Throughput Genome Releaser for Rapid and Efficient PCR Screening

High-throughput PCR screening is vital in synthetic biology and metabolic engineering as it allows researchers to rapidly analyze and detect numerous targeted genetic mutation in the genome. Current challenges for high-throughput PCR screening in synthetic biology include efficiently preparing genomic DNA, optimizing protocols for diverse sample types, managing contamination risks, and effectively analyzing the large volumes of data generated while ensuring consistent and accurate results. In this study, we present the development of a High Throughput Genome Releaser (HTGR), an innovative device addressing common challenges in screening PCR. This genome DNA releaser is designed based on a squash method for rapid, cost-effective, and efficient DNA release, optimized for subsequent PCR reactions. After experimenting with various synthetic materials, we selected a plastic that closely replicates the smooth surface and compression properties of microscope slides, ensuring reliable performance. We engineered a device featuring a 96-Well Plate and a shear applicator, operable both manually and automatically, and compatible with standard liquid-handling robot platform. This compatibility enhances ease of use in high-throughput PCR workflows. Additionally, we developed software to support its automatic functions. Our results demonstrated that the specially engineered 96-Well Plate and HTGR can effectively squash fungal spores , which release enough genome DNA for PCR screening. The genome releaser facilitates the preparation of PCR-amplifiable genomic DNA substrate from 96 samples within minutes, eliminates the need for extraction buffers, and is adaptable to a wide range of microorganisms and cells, which could significantly advance biomanufacturing processes.

Yuan, Guoliang [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2016

System and method for design and optimization of grid connected photovoltaic power plant with multiple photovoltaic module technologies

A system and method of using one or more DC-DC/DC-AC converters and/or alternative devices allows strings of multiple module technologies to coexist within the same PV power plant. A computing (optimization) framework estimates the percentage allocation of PV power plant capacity to selected PV module technologies. The framework and its supporting components considers irradiation, temperature, spectral profiles, cost and other practical constraints to achieve the lowest levelized cost of electricity, maximum output and minimum system cost. The system and method can function using any device enabling distributed maximum power point tracking at the module, string or combiner level.

14 SOLAR ENERGY↗
DOE OSTI2020

Stochastic Analysis for Long Term Capital Structures, Systems, and Components Refurbishment and Replacement

As commercial Nuclear Power Plants (NPPs) pursue extended plant operation in the form of Second License Renewal (SLR), opportunities exist for these plants to provide capital investments to ensure long-term safe and economic performance. At the current time, several utilities have announced an intention to pursue extended operation for one or more of their NPPs via SLR . The goal of this research is to develop a risk-informed approach to evaluate and prioritize plant capital investments made in preparation for, and during the period of, extended plant operations to support decisions for NPP operations. Since the capital investments are influenced by various factors, such as markets, safety and regulatory, the decision-making process of NPP operations should take into account relevant factors for balancing risks, costs and profits. The traditional method of capital budgeting is based on the priority list of candidate projects using economic measures such as benefit-investment ratio, net present value (NPV) and internal rate of return. In the literatures, the problem of capital budgeting or the variant can be represented by an appropriate knapsack problem. The knapsack approach to capital budgeting takes as input as investment, along with the cost and profit of each project. The objective of capital budgeting is to find the combination of the binary decisions for every investment such that the overall profit is as large as possible. The output is a collection of projects to be carried out, and we refer this selected collection of projects as a project portfolio. One limitation of traditional optimization models for capital budgeting is that they do not account for risk/uncertainty in profit and cost streams associated with individual projects, they do not account for risk in resource availability in future years [1,2,3]. Projects can incur cost over-runs, especially when projects are large, performed infrequently, and when there is risk regarding technical viability, external contractors, and/or suppliers of requisite parts and materials. Occasionally, projects are performed ahead of schedule and with cost savings. Planned budgets for capital improvements can be cut and key personnel may be lost. Or, there may be surprise windfalls in budgets for maintenance activities due to decreased costs for “unplanned” maintenance. In these cases, how should we resolve capital budgeting when we have risk forecasts for costs, profits and budgets? One approach we proposed in this summary is to re-solve the optimization models based on assumed statistical distributions of given parameters. If these distributions were not available, a two-stage stochastic optimization approach can be used to provide priority lists to decision-makers to support better risk-informed decisions [4, 5]. In this summary, we will only focus on the first approach.

42 ENGINEERING↗
DOE OSTI2022

Support Vector Machines for Classification of Direct Energy Deposition Standoff Distance for Improved Process Control

A critical factor in the implementation of direct energy deposition is the ability to maintain the standoff distance between the nozzle and the build surface, as this influences powder capture efficiency and overall part quality. Due to process-related variations, layer height may vary, causing unintended variation in standoff distance and poor build quality. While prior work has utilized contact probing to qualify standoff distance during processing, in situ methods for qualification of standoff distance are of major interest. The present work seeks to understand efficacy of image-based methods for classifying standoff distance variation in real-time using support vector machines (SVMs). It was hypothesized that the size of the melt pool and the amount of spatter will have significant correlations with deviations in the standoff distance; thus, SVMs were used on a dataset that is comprised of morphological features of melt pool size and image entropy. The SVM model was used to classify melt pool images into categories according to standoff distance variation from nominal. K-folds cross validation was used to find the optimal hyperparameters for the SVM model. To understand the impact of the selected features on the classification performance and inference speed, multiple models were trained with differing numbers of included features. Results for classification score, inference time, and image preprocessing/feature extraction from these data are reported. The present results show that the SVM model was able to predict the standoff distance classification with an accuracy of 97 percent and a speed of 0.122 s per image, making it a viable solution for real-time control of standoff distance.

Klesmith, Zoe↗
DOE OSTI2015

SU-E-T-213: Comparison of Treatment Efficiency of Gamma Knife SRS Plans for Brain Metastases with Different Planning Methods

Purpose: To improve Gamma Knife SRS treatment efficiency for brain metastases and compare the differences of treatment time and radiobiological effects between two different planning methods of automatic filling and manual placement of shots with inverse planning. Methods: T1-weighted MRI images with gadolinium contrast from five patients with a single brain metastatic-lesion were used in this retrospective study. Among them, two were from primary breast cancer, two from primary melanoma cancer and one from primary prostate cancer. For each patient, two plans were generated in Leksell GammaPlan10.1.1 for radiosurgical treatment with a Leksell GammaKnife Perfexion machine: one with automatic filling, automatic sector configuration and inverse optimization (Method1); and the other with manual placement of shots, manual setup of collimator sizes, manual setup of sector blocking and inverse optimization (Method2). Dosimetric quality of the plans was evaluated with parameters of Coverage, Selectivity, Gradient-Index and DVH. Beam-on Time, Number-of-Shots and Tumor Control Probability(TCP) were compared for the two plans while keeping their dosimetric quality very similar. Relative reduction of Beam-on Time and Number-of-Shots were calculated as the ratios among the two plans and used for quantitative analysis. Results: With very similar dosimetric and radiobiological plan quality, plans created with Method 2 had significantly reduced treatment time. Relative reduction of Beam-on Time ranged from 20% to 51 % (median:29%,p=0.001), and reduction of Number-of-Shots ranged from 5% to 67% (median:40%,p=0.0002), respectively. Time of plan creation for Method1 and Method2 was similar, approximately 20 minutes, excluding the time for tumor delineation. TCP calculated for the tumors from differential DVHs did not show significant difference between the two plans (p=0.35). Conclusion: The method of manual setup combined with inverse optimization in LGP for treatment of brain metastatic lesions with the Perfexion can achieve significantly higher time efficiency without degrading treatment quality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Atomic Layer Etching at the Tipping Point: An Overview

The ability to achieve near-atomic precision in etching different materials when transferring lithographically defined templates is a requirement of increasing importance for nanoscale structure fabrication in the semiconductor and related industries. The use of ultra-thin gate dielectrics, ultra thin channels, and sub-20 nm film thicknesses in field effect transistors and other devices requires near-atomic scale etching control and selectivity. There is an emerging consensus that as critical dimensions approach the sub-10 nm scale, the need for an etching method corresponding to Atomic Layer Deposition (ALD), i.e. Atomic Layer Etching (ALE), has become essential, and that the more than 30-year quest to complement/replace continuous directional plasma etching (PE) methods for critical applications by a sequence of individual, self-limited surface reaction steps has reached a crucial stage. A key advantage of this approach relative to continuous PE is that it enables optimization of the individual steps with regard to reactant adsorption, self-limited etching, selectivity relative to other materials, and damage of critical surface layers. In this overview we present basic approaches to ALE of materials, discuss similarities/crucial differences relative to thermal and plasma-enhanced ALD, and then review selected results on ALE of materials aimed at pattern transfer. Furthermore, the overview concludes with a discussion of opportunities and challenges ahead.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Microbial production of high octane and high sensitivity olefinic ester biofuels

Abstract Background Advanced spark ignition engines require high performance fuels with improved resistance to autoignition. Biologically derived olefinic alcohols have arisen as promising blendstock candidates due to favorable octane numbers and synergistic blending characteristics. However, production and downstream separation of these alcohols are limited by their intrinsic toxicity and high aqueous solubility, respectively. Bioproduction of carboxylate esters of alcohols can improve partitioning and reduce toxicity, but in practice has been limited to saturated esters with characteristically low octane sensitivity. If olefinic esters retain the synergistic blending characteristics of their alcohol counterparts, they could improve the bioblendstock combustion performance while also retaining the production advantages of the ester moiety. Results Optimization of Escherichia coli isoprenoid pathways has led to high titers of isoprenol and prenol, which are not only excellent standalone biofuel and blend candidates, but also novel targets for esterification. Here, a selection of olefinic esters enhanced blendstock performance according to their degree of unsaturation and branching. E. coli strains harboring optimized mevalonate pathways, thioester pathways, and heterologous alcohol acyltransferases (ATF1, ATF2, and SAAT) were engineered for the bioproduction of four novel olefinic esters. Although prenyl and isoprenyl lactate titers were limited to 1.48 ± 0.41 mg/L and 5.57 ± 1.36 mg/L, strains engineered for prenyl and isoprenyl acetate attained titers of 176.3 ± 16.0 mg/L and 3.08 ± 0.27 g/L, respectively. Furthermore, prenyl acetate (20% bRON = 125.8) and isoprenyl acetate (20% bRON = 108.4) exhibited blend properties comparable to ethanol and significantly better than any saturated ester. By further scaling cultures to a 2-L bioreactor under fed-batch conditions, 15.0 ± 0.9 g/L isoprenyl acetate was achieved on minimal medium. Metabolic engineering of acetate pathway flux further improved titer to attain an unprecedented 28.0 ± 1.0 g/L isoprenyl acetate, accounting for 75.7% theoretical yield from glucose. Conclusion Our study demonstrated novel bioproduction of four isoprenoid oxygenates for fuel blending. Our optimized E. coli production strain generated an unprecedented titer of isoprenyl acetate and when paired with its favorable blend properties, may enable rapid scale-up of olefinic alcohol esters for use as a fuel blend additive or as a precursor for longer-chain biofuels and biochemicals.

09 BIOMASS FUELS↗