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All sources NASA NTRS DOE OSTI

DOE OSTI2024

Electronic structure and optical properties of halide double perovskites from a Wannier-localized optimally-tuned screened range-separated hybrid functional

Halide double perovskites are a chemically diverse and growing class of compound semiconductors that are promising for optoelectronic applications. However, the prediction of their fundamental gaps and optical properties with density functional theory (DFT) and ab initio many-body perturbation theory has been a significant challenge. Recently, a nonempirical Wannier-localized optimally tuned screened range-separated hybrid (WOT-SRSH) functional has been shown to accurately produce the fundamental band gaps of a wide set of semiconductors and insulators, including lead halide perovskites. Here, in this study, we apply the WOT-SRSH functional to five halide double perovskites and compare the results with those obtained from other known functionals and previous GW calculations. We also use the approach as a starting point for GW calculations and we compute the band structures and optical absorption spectrum for Cs 2 AgBiBr 6 , using both time-dependent DFT and the GW-Bethe-Salpeter equation approach. We show that the WOT-SRSH functional leads to accurate fundamental and optical band gaps, as well as optical absorption spectra, consistent with spectroscopic measurements, thereby establishing WOT-SRSH as a viable method for the accurate prediction of optoelectronic properties of halide double perovskites.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A machine learning model for predicting the minimum miscibility pressure of CO 2 and crude oil system based on a support vector machine algorithm approach

CO 2 enhanced oil recovery (EOR) is a potential way for carbon capture, utilization and storage (CCUS). Though, the effect of CO 2 injection is greatly influenced by the reservoir conditions. Typically, Minimum miscible pressure (MMP) is selected as one of the key parameters for the screening and evaluation of prospective CO 2 flooding. Conventional slim tube test is both accurate and widely accepted but it is inefficient. Existing empirical formulas for MMPs are easy to be used but have been proved inaccurate and unreliable. Machine learning-based methods have great advantages in predicting MMP. However, only predication accuracy is discussed for most models without the screening of the main control factors and further validation of the model reliability. In this paper, a new prediction model based on support vector machine (SVM) was developed for pure/impure CO 2 and crude oil system. This study was based on 147 sets of MMP data from the literature with full information on reservoir temperature, oil composition and gas composition. The main control factors were screened by several statistical methods. Unlike the conventional prediction models that verified by only prediction accuracy, learning curve and single factor control variable analysis are further validated to obtain the optimum model.

02 PETROLEUM↗

NASA NTRS1989

Animation graphic interface for the space shuttle onboard computer

Graphics interfaces designed to operate on space qualified hardware challenge software designers to display complex information under processing power and physical size constraints. Under contract to Johnson Space Center, MICROEXPERT Systems is currently constructing an intelligent interface for the LASER DOCKING SENSOR (LDS) flight experiment. Part of this interface is a graphic animation display for Rendezvous and Proximity Operations. The displays have been designed in consultation with Shuttle astronauts. The displays show multiple views of a satellite relative to the shuttle, coupled with numeric attitude information. The graphics are generated using position data received by the Shuttle Payload and General Support Computer (PGSC) from the Laser Docking Sensor. Some of the design considerations include crew member preferences in graphic data representation, single versus multiple window displays, mission tailoring of graphic displays, realistic 3D images versus generic icon representations of real objects, the physical relationship of the observers to the graphic display, how numeric or textual information should interface with graphic data, in what frame of reference objects should be portrayed, recognizing conditions of display information-overload, and screen format and placement consistency.

Wike, Jeffrey↗

DOE OSTI2023

Computational Discovery of Active and Selective Metal‐Nitrogen‐Graphene Catalysts for Electrooxidation of Water to H 2 O 2

A direct electrosynthesis of H 2 O 2 from either O 2 or H 2 O is an attractive strategy to replace the energy-intensive industrial anthraquinone process. Two-electron water oxidation reaction (2e-WOR) offers several advantages over the oxygen reduction reaction such as better mass transfer due to the absence of gas-phase reactants. However, 2e-WOR is a more challenging and less studied process with only a handful of metal oxides exhibiting reasonable activity/selectivity properties. Herein, we employ density-functional-theory calculations to screen a variety of metal-nitrogen-graphene structures for 2e-WOR. As a consequence of scaling between the adsorption energies of reaction intermediates, we determine a linear relation between selectivities for the first and second reaction steps of 2e-WOR, viz. that if selectivity toward adsorbed OH is improved, then selectivity toward H 2 O 2 at the subsequent step is decreased. We also find that selectivity and activity are linearly scaled in such a way that a higher activity (i.e., a lower overpotential) leads to a lower selectivity for the H 2 O 2 formation step. Based on the obtained results several chemistries, e.g., containing NiN x -C moieties, are predicted to rival the best-performing metal oxides such as ZnO and CaSnO 3 in terms of combination of their activity/selectivity characteristics for 2e-WOR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Developing a complete AI-accelerated workflow for superconductor discovery

The quest to identify new superconducting materials with enhanced properties is hindered by the prohibitive cost of computing electron-phonon spectral functions, severely limiting the materials space that can be explored. Here, we introduce a Bootstrapped Ensemble of Equivariant Graph Neural Networks (BEE-NET), a machine-learning model trained to predict the Eliashberg spectral function and superconducting critical temperature with a mean-absolute-error of 0.87 K relative to DFT-based Allen-Dynes calculations. Intriguingly, BEE-NET achieves a true-negative-rate of 99.4%, enabling highly efficient screening for the rare property of superconductivity. Integrated into a multi-stage, AI-accelerated discovery pipeline that incorporates elemental-substitution strategies and machine-learned interatomic potentials, our workflow reduced over 1.3 million candidate structures to 741 dynamically and thermodynamically stable compounds with DFT-confirmed T c > 5 K. We report the successful synthesis and experimental confirmation of superconductivity in two of these previously unreported compounds. This study establishes a data-driven framework that integrates machine learning, quantum calculations, and experiments to systematically accelerate superconductor discovery.

Gibson, Jason B. [Quantum Formatics, Cambridge, MA↗

DOE OSTI2023

First-Principles Understanding of Optical Excitations within Low-Dimensional Materials

The objective of this project is to utilize first-principles computational approaches to understand optical excitations within two-dimensional monolayers and heterostructures, with the ultimate goal of designing new materials by modifying the chemical and physical structure on the nanoscale. In 2D heterostructures, the nature and movement of the exciton is determined to a large extent by the electron-electron and electron-phonon strengths within individual monolayers, as well as the coupling between layers, all of which in turn depend on chemistry, solid-state screening properties, and quantum confinement. Controlling the nature and migration properties of excitons requires an understanding of the complex relationship between electrons, phonons, defects, disorder, and dynamics. The aim of this project is to determine, by analysis of highly accurate density functional theory (DFT) and many-body perturbation theory (MBPT) calculations, how these complexities can be decomposed into simple, tunable parameters. The specific goals of this project are to 1) understand electron conductivity, absorption and transparency of monolayer semiconductors and metals; 2) develop a theory of excitons near defects in low dimensions; and 3) understand the influence of inter-layer interactions in heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Challenges and Solutions for Leave-One-Out Biosensor Design in the Context of a Rugged Fitness Landscape

The leave-one-out (LOO) green fluorescent protein (GFP) approach to biosensor design combines computational protein design with split protein reconstitution. LOO-GFPs reversibly fold and gain fluorescence upon encountering the target peptide, which can be redefined by computational design of the LOO site. Such an approach can be used to create reusable biosensors for the early detection of emerging biological threats. Enlightening biophysical inferences for nine LOO-GFP biosensor libraries are presented, with target sequences from dengue, influenza, or HIV, replacing beta strands 7, 8, or 11. An initially low hit rate was traced to components of the energy function, manifesting in the over-rewarding of over-tight side chain packing. Also, screening by colony picking required a low library complexity, but designing a biosensor against a peptide of at least 12 residues requires a high-complexity library. This double-bind was solved using a “piecemeal” iterative design strategy. Also, designed LOO-GFPs fluoresced in the unbound state due to unwanted dimerization, but this was solved by fusing a fully functional prototype LOO-GFP to a fiber-forming protein, Drosophila ultrabithorax, creating a biosensor fiber. One influenza hemagglutinin biosensor is characterized here in detail, showing a shifted excitation/emission spectrum, a micromolar affinity for the target peptide, and an unexpected photo-switching ability.

Chemistry↗

NASA NTRS1990

Parallel line analysis: multifunctional software for the biomedical sciences

An easy to use, interactive FORTRAN program for analyzing the results of parallel line assays is described. The program is menu driven and consists of five major components: data entry, data editing, manual analysis, manual plotting, and automatic analysis and plotting. Data can be entered from the terminal or from previously created data files. The data editing portion of the program is used to inspect and modify data and to statistically identify outliers. The manual analysis component is used to test the assumptions necessary for parallel line assays using analysis of covariance techniques and to determine potency ratios with confidence limits. The manual plotting component provides a graphic display of the data on the terminal screen or on a standard line printer. The automatic portion runs through multiple analyses without operator input. Data may be saved in a special file to expedite input at a future time.

NASA Discipline Cell Biology↗

NASA NTRS1979

Aerospace Ground Equipment for model 4080 sequence programmer. A standard computer terminal is adapted to provide convenient operator to device interface

The Aerospace Ground Equipment (AGE) provides an interface between a human operator and a complete spaceborne sequence timing device with a memory storage program. The AGE provides a means for composing, editing, syntax checking, and storing timing device programs. The AGE is implemented with a standard Hewlett-Packard 2649A terminal system and a minimum of special hardware. The terminal's dual tape interface is used to store timing device programs and to read in special AGE operating system software. To compose a new program for the timing device the keyboard is used to fill in a form displayed on the screen.

Nissley, L. E.↗

DOE OSTI2024

Rapid Design of Cost-Effective Refractory High Entropy Alloys Strengthened by Precipitation

Funded by the ARPA-E ULTIMATE program, this project aims to develop cost-effective refractory high entropy alloys (RHEAs) for gas turbine blades applications at 1300 degree Celsius and above. The alloy design focuses on carbides precipitation strengthening in a strong and ductile solid solution BCC matrix. The goal is to achieve balanced mechanical properties including room temperature ductility & fracture toughness and high temperature strength and creep resistance, while maintaining comparable oxidation resistance and densities to Ni-base superalloys. To accelerate alloy design, multiscale modeling including CALPHAD and first-principles density functional theory (DFT) calculations and machine learning are performed. Specifically, high throughput phase diagram calculations and screening are carried out using CALPHAD; DFT calculations are performed to predict intrinsic ductility, grain boundary strengthening potential, coefficient of thermal expansion (CTE) and temperature-dependent elastic constants. Temperature dependent yield stress, creep strain and CTE are also predicted using machine learning. Down-selected alloys are synthesized in small buttons of about 250g using arc melting for rapid evaluation on microstructure and mechanical properties before employing plasma arc melting and additive manufacturing for producing large ingots. Preliminary computational and experimental results of this project will be presented and future direction in RHEA development will be discussed.

high temperature materials↗

NASA NTRS1988

Real-time optical image processing techniques

Nonlinear real-time optical processing on spatial pulse frequency modulation has been pursued through the analysis, design, and fabrication of pulse frequency modulated halftone screens and the modification of micro-channel spatial light modulators (MSLMs). Micro-channel spatial light modulators are modified via the Fabry-Perot method to achieve the high gamma operation required for non-linear operation. Real-time nonlinear processing was performed using the halftone screen and MSLM. The experiments showed the effectiveness of the thresholding and also showed the needs of higher SBP for image processing. The Hughes LCLV has been characterized and found to yield high gamma (about 1.7) when operated in low frequency and low bias mode. Cascading of two LCLVs should also provide enough gamma for nonlinear processing. In this case, the SBP of the LCLV is sufficient but the uniformity of the LCLV needs improvement. These include image correlation, computer generation of holograms, pseudo-color image encoding for image enhancement, and associative-retrieval in neural processing. The discovery of the only known optical method for dynamic range compression of an input image in real-time by using GaAs photorefractive crystals is reported. Finally, a new architecture for non-linear multiple sensory, neural processing has been suggested.

Liu, Hua-Kuang↗

NASA NTRS1994

Simulation in a dynamic prototyping environment: Petri nets or rules?

An evaluation of a prototyped user interface is best supported by a simulation of the system. A simulation allows for dynamic evaluation of the interface rather than just a static evaluation of the screen's appearance. This allows potential users to evaluate both the look (in terms of the screen layout, color, objects, etc.) and feel (in terms of operations and actions which need to be performed) of a system's interface. Because of the need to provide dynamic evaluation of an interface, there must be support for producing active simulations. The high-fidelity training simulators are delivered too late to be effectively used in prototyping the displays. Therefore, it is important to build a low fidelity simulator, so that the iterative cycle of refining the human computer interface based upon a user's interactions can proceed early in software development.

Moore, Loretta A.↗

NASA NTRS1997

Immersive cyberspace system

An immersive cyberspace system is presented which provides visual, audible, and vibrational inputs to a subject remaining in neutral immersion, and also provides for subject control input. The immersive cyberspace system includes a relaxation chair and a neutral immersion display hood. The relaxation chair supports a subject positioned thereupon, and places the subject in position which merges a neutral body position, the position a body naturally assumes in zero gravity, with a savasana yoga position. The display hood, which covers the subject's head, is configured to produce light images and sounds. An image projection subsystem provides either external or internal image projection. The display hood includes a projection screen moveably attached to an opaque shroud. A motion base supports the relaxation chair and produces vibrational inputs over a range of about 0-30 Hz. The motion base also produces limited translation and rotational movements of the relaxation chair. These limited translational and rotational movements, when properly coordinated with visual stimuli, constitute motion cues which create sensations of pitch, yaw, and roll movements. Vibration transducers produce vibrational inputs from about 20 Hz to about 150 Hz. An external computer, coupled to various components of the immersive cyberspace system, executes a software program and creates the cyberspace environment. One or more neutral hand posture controllers may be coupled to the external computer system and used to control various aspects of the cyberspace environment, or to enter data during the cyberspace experience.

Park, Brian V.↗

DOE OSTI2020

Special Analyses for the Hanford Integrated Disposal Facility Performance Assessment - 20102

In 2014, the Department of Energy (DOE) Office of River Protection and its contractors began to develop a performance assessment for the near-surface disposal of low-level and mixed low-level waste at the Hanford Site's Integrated Disposal Facility (IDF). The IDF is a doubly-lined landfill that was constructed between 2004 and 2006 to be the disposal facility for the vitrified low-activity waste that will be produced at the Waste Treatment and Immobilization Plant (WTP). IDF is also expected to receive solid secondary waste produced at the WTP and other solid wastes from site activities. The IDF has been in a preoperational state awaiting authorization from DOE and a RCRA permit modification from the State of Washington Department of Ecology to receive waste. Both the Disposal Authorization Statement and permit modification require a performance assessment demonstrating that the system of engineered and natural features will limit releases of radionuclides and hazardous chemicals from the IDF and be protective of human health and the environment. The simulated duration is 10,000 years. Based on the analyses presented in the 2017 Integrated Disposal Facility Performance Assessment, DOE issued a conditional Operating Disposal Authorization Statement for the IDF in June 2018. The long-term performance of the IDF to be protective of human health and the environment was evaluated under the requirements of DOE Order 435.1, Radioactive Waste Management. Computer simulations were performed to evaluate whether or not the IDF would comply with DOE requirements. In the time that has passed since the performance assessment was approved by DOE, new information has been discovered that had not been considered in the performance assessment. Since this new information has not been evaluated, the potential impact of the changes have not been taken into consideration in DoE's disposal authorization. DOE and its contractors follow a change control process to screen and, when necessary, evaluate new information that could potentially impact the conclusions of the completed performance assessment. This paper will describe the change control process and provide two examples of evaluations performed following the change control process. The first example evaluates a new waste form for liquid secondary waste that was not evaluated in the performance assessment. In the performance assessment, liquid secondary waste was assumed to be solidified with grout. A new recommendation to dispose of the liquid secondary waste after drying it to a powder was evaluated. The second example evaluates inventory implications from changes to the flow sheet that estimates the feed composition to the low-activity waste vitrification facility. The changes result in higher strontium concentrations in the vitrified waste stream. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Computational Design of Metal-Exchanged MFI Zeolites for Coupling CO 2 –Ethylene to Form Acrylic Acid

The production of acrylic acid by coupling CO 2 and ethylene is highly desirable, as it uses a C 1 molecule to introduce the carboxylic group into a large commodity chemical, forming an unsaturated carboxylic acid. Molecular complexes have been used as catalysts in the literature for this reaction; however, these homogeneous studies were all limited by low activity and stability, and efficient heterogeneous catalysts remain to be explored. Here, we report density functional theory calculations, through which we investigated metal-exchanged MFI zeolites with metals from 3d, 4d, and 5d series for this reaction. Screening of reaction thermodynamics has shown that Sc, Y, Cr, Mo, W, Mn, Tc, and Re dispersed into MFI zeolites are potential catalysts. We further calculated the activation barriers for the β–H transfer, a key elementary step that normally determines the overall rates, and found the lowest barrier over Sc- and Y-MFI; such a feasible kinetics is attributed to the low electronegativity of Sc and Y that strongly affects the nature of the transition states and the charge redistribution during the β–H transfer. In conclusion, this work thus provides guidelines for designing a zeolite-based catalyst for this valuable reaction and identifies promising metal centers to be used.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

The REPACT Tool: User Manual [Slides]

Reuse of Existing Pipelines for Adapted Carbon Transport (REPACT) is an Excel-based screening tool. This tool enables the user to determine whether a pipeline originally deployed for natural gas transport, can be reused for CO 2 transport. The tool along with its associated users manual walk through an intended usage statement, setup instructions, a list of inputs and outputs in the tool, and frequently used protocols. Please note that this is a first-pass screening tool. The approach presented within this tool is valid for high-level evaluation only and should not be used to make engineering, financial, and/or regulatory decisions. Access the tool here: https://www.netl.doe.gov/energy-analysis/details?id=c699a604-ded1-45cd-b1c0-247b1405aeeb

03 NATURAL GAS↗

NASA NTRS2004

Article Screening System

During the last ten years patents directed to luggage scanning apparatus began to appear in the patent art. Absent from the variety of approaches in the art is stereoscopic imaging that entails exposing two or more images of the same object, each taken from a slightly different perspective. If the perspectives are too different, that is. if there is too much separation of the X-ray exposures, the image will look flat. Yet with a slight separation, a stereo separation, interference occurs. Herein a system is provided for the production of stereo pairs. One perspective, a left or a right perspective angle, is first established. Next, the other perspective angle is computed. Using these left and right perspectives the X-ray sources can then be spaced away from each other.

Kenneth R Fernandez↗

DOE OSTI2021

Computational Framework for Machine-Learning-Enabled 13 C Fluxomics

13 C metabolic flux analysis (MFA) has emerged as a powerful tool for synthetic biology. This optimization-based approach suffers long computation time and unstable solutions depending on the initial guess. Here, we develop a machine-learning-based framework for 13 C fluxomics. Specifically, training and test data sets are generated by metabolic network decomposition and flux sampling, in which flux ratios at metabolic nodes and simulated labeling patterns of metabolites are used as training targets and features, respectively. To improve prediction accuracy and simplify the model, automated processes are developed for flux ratio selection based on solvability and feature screening based on importance. We found that predictive performance can be significantly improved using both amino acids and central carbon metabolites in comparison with amino acids alone. Together with measured external fluxes, the predicted flux ratios determine the mass balance system, yielding global flux distributions. This approach is validated by flux estimation using both simulated and experimental data in comparison with canonical 13 C MFA. The approach represents a reliable fluxomics method readily applicable to high-throughput metabolic phenotyping, which highlights the advances of intelligent learning algorithms in synthetic biology, specifically in the Test and Learn stage of the Design-Build-Test-Learn cycle.

13C metabolic flux analysis↗