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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
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

UO 2 target preparation with spin coating assisted solution combustion synthesis

A simple and efficient target preparation method is developed combining spin coating and solution combustion synthesis. Multiple smooth and uniform UO 2 targets have been prepared using this method on a variety of backings (aluminium, carbon, silicon) used in nuclear physics experiments. The thicknesses of the targets can be precisely tuned by changing the number of coatings within the range of ~50-1000 µm/cm 2 . These targets are highly uniform (<5% deviation), robust, and remain strongly adherent to their backings even after being irradiated by high doses (10 17 ions/ cm 2 ) of 1.7 MeV Ar 2+ ions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2010

Amino Acids Profiles in Biological Media

An accurate analytical method was developed to determine amino acids in some biological specimens by GC/MS technique. Stable isotopes provide useful tools for a variety of studies, offering ideal internal standards in quantitative information. Isotopic dilution gas chromatography--mass spectrometry (ID-GC/MS) is the techniques used for quantitative analysis of compounds labeled with stable isotopes. A Trace DSQ Thermo Finnigan quadrupole mass spectrometer coupled with a Trace GC was used. Amino acids were separated on a Rtx-5 MS capillary column, 30 mx0.25 mm, 0.25 {mu}m film thickness, using a temperature program from 50 deg. C, 1 min, 6 deg. C/min at 100 deg. C, 4 deg. C/min at 200 deg. C, 20 deg. C/min at 300 deg. C, (3 min). The transfer line temperature was 250 deg. C, the injector temperature 200 deg. C and ion source temperature 250 deg. C; splitter: 10:1. Electron energy was 70 eV and emission current, 100 {mu}A. The amino acids were purified on a Dowex 50W-W8 exchange resin and were derivatized in a procedure following two steps to obtain trifluoroacetyl butyl esters. The identification of amino acids was obtained by using NIST library but also by using amino acid standards.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Indirect-to-direct band gap transition in relaxed and strained Ge{sub 1−x−y}Si{sub x}Sn{sub y} ternary alloys

Sn-containing group IV semiconductors create the possibility to independently control strain and band gap thus providing a wealth of opportunities to develop an entirely new class of low dimensional systems, heterostructures, and silicon-compatible electronic and optoelectronic devices. With this perspective, this work presents a detailed investigation of the band structure of strained and relaxed Ge{sub 1−x−y}Si{sub x}Sn{sub y} ternary alloys using a semi-empirical second nearest neighbors tight binding method. This method is based on an accurate evaluation of the deformation potential constants of Ge, Si, and α-Sn using a stochastic Monte-Carlo approach as well as a gradient based optimization method. Moreover, a new and efficient differential evolution approach is also developed to accurately reproduce the experimental effective masses and band gaps. Based on this, we elucidated the influence of lattice disorder, strain, and composition on Ge{sub 1−x−y}Si{sub x}Sn{sub y} band gap energy and directness. For 0 ≤ x ≤ 0.4 and 0 ≤ y ≤ 0.2, we found that tensile strain lowers the critical content of Sn needed to achieve a direct band gap semiconductor with the corresponding band gap energies below 0.76 eV. This upper limit decreases to 0.43 eV for direct gap, fully relaxed ternary alloys. The obtained transition to direct band gap is given by y > 0.605 × x + 0.077 and y > 1.364 × x + 0.107 for epitaxially strained and fully relaxed alloys, respectively. The effects of strain, at a fixed composition, on band gap directness were also investigated and discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Analysis of N-16 concentration in primary cooling system of AP1000 power reactor

Nitrogen-16 (N-16) is one of the radiation safety parameter on the primary reactor system. The activation product, N-16, is the predominant contributor to the activity in the reactor coolant system during reactor operation. N-16 is activation product derived from activation of O-16 with fast neutron based on {sup 16}O(n,p){sup 16}N reaction. Thus study is needed and it performs to determine N-16 concentration in reactor coolant (primary coolant) in supporting radiation safety. One of the way is using analytical methode based on activation and redecay princip to obtain N-16 concentration. The analysis was performed on the configuration basis and operational of Westinghouse AP1000 power reactor in several monitoring points at coolant reactor system. The results of the calculation of N-16 concentration at the core outlet, reactor vessel outlet, pressurizer line, inlet and outlet of steam generators, primary pumps, reactor vessels inlet and core inlet are: 281, 257, 255, 250, 145, 142, 129 and 112 µCi/gram respectively. The results of analysis compared with AP1000 design control document as standard values. The verification showed very high accuracy comparation between analytical results and standard values.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Investigation of electrochemical migration on Sn-0.7Cu-0.3Ag-0.03P-0.005Ni solder alloy in HNO{sub 3} solution

Current issue in lead-free solder in term of its reliability is still under investigation. This high impact research attempts to investigate the electrochemical migration (ECM) on Sn-0.7Cu-0.3Ag-0.03P-0.005Ni solder alloy by Water Drop Test (WDT) in different concentration of HNO{sub 3} solution. The concentration of HNO{sub 3} solution used in this research was 0.05, 0.10, 0.50 and 1M. Optical Microscope (OM), Field Emission Scanning Electron Microscope (FESEM) and Energy Dispersive X-Ray Analysis (EDX) were carried out in order to analysis the ECM behavior based on the growth of dendrite formation after WDT. In general, the results demonstrated that dendrite growth is faster in higher concentration compared with low concentration of HNO{sub 3}. The concentration of HNO{sub 3} solution used has a strong correlation with Mean-Time-To-Failure (MTTF). As the concentration of HNO{sub 3} increases, the MTTF value decreases. Based on the MTTF results the solder alloy in 1M HNO{sub 3} solution is most susceptible to ECM. SnO{sub 2} forms as a corrosion by-product in the samples proved by EDX analysis. The solder alloy poses a high reliability risk in microelectronic devices during operation in 1M HNO{sub 3} solution.

36 MATERIALS SCIENCE↗
DOE OSTI2015

The effect of acid hydrolysis pretreatment on crystallinity and solubility of kenaf cellulose membrane

Cellulose was extracted from kenaf core pulp (KCP) by series of bleaching steps in the sequence (DEED) where D and E are referred as acid and alkali treatment. The bleached kenaf pulp (BKCP) is then pretreated with acid hydrolysis at room temperature for 1 and 3 h respectively. The pretreated cellulose is dissolved in lithium hydroxide/urea (LiOH/urea) and cellulose solution produced was immersed in distilled water bath. BKCP without treatment was also conducted for comparison purpose. The effects of acid hydrolysis pretreatment on solubility and crystallinity are investigated. Higher solubility of cellulose solution is achieved for treated samples. Cellulose II formation and crystallinity index of the cellulose membrane were determined by X-ray diffraction (XRD)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Neutron absorption of Al-Si-Mg-B{sub 4}C composite

Al-Si-Mg-B{sub 4}C composites containing 2-8 wt% of B{sub 4}C were prepared by stir casting technique. Homogenization treatment was carried out at temperatures of 540°C for 4 houra and followed by ageing at 180°C for 2 houra. Microstructure and phase identification were studied by scanning electron microscopy (SEM) and X-ray diffraction (XRD) respectively. Neutron absorption study was investigated using neutron source Am/Be{sup 241}. The result indicated that higher B{sub 4}C content improved the neutron absorption property. Meanwhile homogeneity of the composite was increased by ageing processes. This composite is potential to be used as neutron shielding material especially for nuclear reactor application.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Effective conversion of biomass tar into fuel gases in a microwave reactor

This work deals with conversion of naphthalene (C{sub 10}H{sub 8}) as a biomass tar model compound by means of thermal and catalytic treatments. A modified microwave oven with a maximum output power of 700 W was used as the experimental reactor. Experiments were performed in a wide temperature range of 450-1200°C at a predetermined residence time of 0.24-0.5 s. Dolomite and Y-zeolite were applied to convert naphthalene catalytically into useful gases. Experimental results on naphthalene conversion showed that conversion efficiency and yield of gases increased significantly with the increase of temperature. More than 90% naphthalene conversion efficiency was achieved by thermal treatment at 1200°C and 0.5 s. Nevertheless, this treatment was unfavorable for fuel gases production. The main product of this treatment was soot. Catalytic treatment provided different results with that of thermal treatment in which fuel gases formation was found to be the important product of naphthalene conversion. At a high temperature of 900°C, dolomite had better conversion activity where almost 40 wt.% of naphthalene could be converted into hydrogen, methane and other hydrocarbon gases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Nonlinear time-series analysis of current signal in cathodic contact glow discharge electrolysis

In the standard two-electrode configuration employed in electrolytic process, when the control dc voltage is brought to a critical value, the system undergoes a transition from conventional electrolysis to contact glow discharge electrolysis (CGDE), which has also been referred to as liquid-submerged micro-plasma, glow discharge plasma electrolysis, electrode effect, electrolytic plasma, etc. The light-emitting process is associated with the development of an irregular and erratic current time-series which has been arbitrarily labelled as “random,” and thus dissuaded further research in this direction. Here, we examine the current time-series signals measured in cathodic CGDE configuration in a concentrated KOH solution at different dc bias voltages greater than the critical voltage. We show that the signals are, in fact, not random according to the NIST SP. 800-22 test suite definition. We also demonstrate that post-processing low-pass filtered sequences requires less time than the native as-measured sequences, suggesting a superposition of low frequency chaotic fluctuations and high frequency behaviors (which may be produced by more than one possible source of entropy). Using an array of nonlinear time-series analyses for dynamical systems, i.e., the computation of largest Lyapunov exponents and correlation dimensions, and re-construction of phase portraits, we found that low-pass filtered datasets undergo a transition from quasi-periodic to chaotic to quasi-hyper-chaotic behavior, and back again to chaos when the voltage controlling-parameter is increased. The high frequency part of the signals is discussed in terms of highly nonlinear turbulent motion developed around the working electrode.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Managing hysteresis of Gd 5 Si 2 Ge 2 by magnetic field cycling

The influence of magnetic field cycling through the first-order magnetostructural transformation on the magnetic and magnetocaloric properties, as well as hysteresis of polycrystalline Gd 5 Si 2 Ge 2 , has been studied using magnetometry. Here, the cycling has a minimal effect on the magnetic field-induced entropy change and the phase transformation temperature of the material. On the other hand, magnetic hysteresis decreases by 30% after approximately ten cycles and remains low unless the sample is moved far into the paramagnetic regime. Factors playing a role in the history dependence of hysteresis have been discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Irradiation-induced reactions at the CeO 2 /SiO 2 /Si interface

The influence of high-energy (1.6 MeV) Ar 2+ irradiation on the interfacial interaction between cerium oxide thin films (~15 nm) with a SiO 2 /Si substrate is investigated using transmission electron microscopy, ultrahigh vacuum x-ray photoelectron spectroscopy (XPS), and a carbon monoxide (CO) oxidation catalytic reaction using ambient pressure XPS. The combination of these methods allows probing the dynamics of vacancy generation and its relation to chemical interactions at the CeO 2 /SiO 2 /Si interface. The results suggest that irradiation causes amorphization of some portion of CeO 2 at the CeO 2 /SiO 2 /Si interface and creates oxygen vacancies due to the formation of Ce 2 O 3 at room temperature. The subsequent ultra-high-vacuum annealing of irradiated films increases the concentration of Ce 2 O 3 with the simultaneous growth of the SiO 2 layer. Interactions with CO molecules result in an additional reduction of cerium and promote the transition of Ce 2 O 3 to a silicate compound. Furthermore, thermal annealing of thin films exposed to oxygen or carbon monoxide shows that the silicate phase is highly stabile even at 450 °C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Controlling magnetostructural transition and magnetocaloric effect in multi-component transition-metal-based materials

Proper coupling between structural and magnetic transitions is critical for the emergence and control of magnetocaloric effects in solids. We examine the influence of minor substitutional doping (replacing Mn by Cr and Al by Sn) and interstitial doping with B on the magnetic, structural, and magnetocaloric properties of recently discovered Mn 0.5 Fe 0.5 NiSi 0.94 Al 0.06 alloy exhibiting a giant magnetocaloric effect near room temperature. We demonstrate that magnetocaloric properties of the base compound can be controlled and, in some cases, improved by chemical substitutions. First-principles computations elucidate how small changes in the composition affect properties in this family of compounds and, thus, provide useful guidance for the selection of suitable doping elements for such materials. Here the magnetic-field-induced entropy change measured for Mn 0.5 Fe 0.5 NiSi 0.94 Al 0.06 B 0.005 is –22 J/kg K near room temperature for the applied magnetic field of 2 T, and it is among the highest known values for this class of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Active meta-learning for predicting and selecting perovskite crystallization experiments

Autonomous experimentation systems use algorithms and data from prior experiments to select and perform new experiments in order to meet a specified objective. In most experimental chemistry situations, there is a limited set of prior historical data available, and acquiring new data may be expensive and time consuming, which places constraints on machine learning methods. Active learning methods prioritize new experiment selection by using machine learning model uncertainty and predicted outcomes. Meta-learning methods attempt to construct models that can learn quickly with a limited set of data for a new task. Here in this paper, we applied the model-agnostic meta-learning (MAML) model and the Probabilistic LATent model for Incorporating Priors and Uncertainty in few-Shot learning (PLATIPUS) approach, which extends MAML to active learning, to the problem of halide perovskite growth by inverse temperature crystallization. Using a dataset of 1870 reactions conducted using 19 different organoammonium lead iodide systems, we determined the optimal strategies for incorporating historical data into active and meta-learning models to predict reaction compositions that result in crystals. We then evaluated the best three algorithms (PLATIPUS and active-learning k-nearest neighbor and decision tree algorithms) with four new chemical systems in experimental laboratory tests. With a fixed budget of 20 experiments, PLATIPUS makes superior predictions of reaction outcomes compared to other active-learning algorithms and a random baseline.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗