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Results for “computational screening”

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 1,081 records · Page 60

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NASA NTRS1976

Design of air-gapped magnetic-core inductors for superimposed direct and alternating currents

Using data on standard magnetic-material properties and standard core sizes for air-gap-type cores, an algorithm designed for a computer solution is developed which optimally determines the air-gap length and locates the quiescent point on the normal magnetization curve so as to yield an inductor design with the minimum number of turns for a given ac voltage and frequency and with a given dc bias current superimposed in the same winding. Magnetic-material data used in the design are the normal magnetization curve and a family of incremental permeability curves. A second procedure, which requires a simpler set of calculations, starts from an assigned quiescent point on the normal magnetization curve and first screens candidate core sizes for suitability, then determines the required turns and air-gap length.

Ohri, A. K.↗

NASA NTRS1986

Nonlocal screening in metal surfaces

Due to the effect of the nonuniform environment on the static screening of the Coulomb potential, the local-density approximation for the particle-hole interaction is found to be inadequate to determine the surface energy of simple metals. Use of the same set of single-particle states, and thus the same one-body density and the same work function, has eliminated the single-electron states in favor of the structure of the short-ranged correlations as the basis of this effect. A posteriori simplifications of the Fermi hypernetted-chain theory may be found to allow the same calculational accuracy with simpler computational tools.

Krotscheck, E.↗

NASA NTRS1990

Infrared detector responsivity measured simultaneously at multiple frequencies

The responsivity (the ratio of the output electrical signal to the incident radiation power) of an IR detector is measured at several frequencies simultaneously. A computer-controlled variable frequency chopper is used. Chopper modulation of a blackbody is square-wave-like, hence measurements can be taken not only at the fundamental frequency but also at the harmonics. The technique gives excellent agreement with the classical technique of measuring the fundamental response alone at a set of modulation frequencies. With a small enough aperture and a high enough chopper speed, agreement can be within five percent out to 31 times the fundamental frequency. The technique allows the rapid and automated acquisition of the frequency response of IR detectors, which may then be screened for responsivity, noise, and noise equivalent power.

Brasunas, John C.↗

DOE OSTI2020

Power system model parameter conditioning tool

A power system model parameter conditioning tool including a server control processor in communication with phasor measurement unit monitored data records of multiple disturbance events, a model calibration unit providing event screening, power system model simulation, and simultaneous tuning of model parameters. The model calibration performing a simulation using default model parameters, the processor comparing the simulation results to the monitored data. If the prediction is within threshold, then terminating conditioning; else performing parameter identifiability analysis to determine differing effects of various model parameters on power system model accuracy, selecting a parameter set causing a degradation in power system model prediction, and updating the default model parameters corresponding to members of the parameter set with values selected to reduce the degradation. A method and a non-transitory computer readable medium are also disclosed.

Baone, Chaitanya Ashok↗

DOE OSTI2025

Deep Learning Approaches for Predicting the Surface Tension of Ionic Liquids

Ionic liquids (ILs) are a novel class of solvents that have attracted significant attention due to their unique and tunable properties. Among their physiochemical characteristics, surface tension plays a critical role in various industrial applications including electrolytes, heat transfer fluids, and separation processes. However, because of the exploratory nature of IL design and the vast combinatorial space of possible anion–cation pairs, the experimental determination of these properties is often impractical, being both time-consuming and costly. To overcome these challenges, computational approaches are increasingly employed to develop accurate predictive models that can accelerate IL discovery and design. In this study, we present two deep learning (DL) models for predicting the surface tension of ILs across a broad temperature range at a constant pressure. The models use simplified molecular input line entry system, SMILES, representations of ILs to extract molecular features as inputs. Both DL models demonstrate excellent agreement with experimental data, achieving an R 2 value of 0.990 and a root-mean-square error of 0.792 mN/m. In conclusion, these results offer valuable insights for the rapid screening and rational design of ILs with tailored surface tension values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Electrical conductivity of a warm neutron star crust in magnetic fields: Neutron-drip regime

We compute the anisotropic electrical conductivity tensor of the inner crust of a compact star at nonzero temperature by extending a previous work on the conductivity of the outer crust. The physical scenarios, where such crust is formed, involve protoneutron stars born in supernova explosions, binary neutron star mergers, and accreting neutron stars. The temperature-density range studied covers the transition from a semidegenerate to a highly degenerate electron gas and assumes that the nuclei form a liquid, i.e., the temperature is above the melting temperature of the lattice of nuclei. The electronic transition probabilities include (i) the screening of electron-ion interaction in the hard-thermal-loop approximation for the QED plasma, (ii) the correlations of the ionic component in a one-component plasma, and (iii) finite nuclear size effects. The conductivity tensor is obtained from the Boltzmann kinetic equation in relaxation time approximation accounting for the anisotropy introduced by a magnetic field. The sensitivity of the results towards the matter composition of the inner crust is explored by using several compositions of the inner crust, which were obtained using different nuclear interactions and methods of solving the many-body problem. The standard deviations of relaxation time and components of the conductivity tensor from the average are below ≤25% except close to crust-core transition, where nonspherical nuclear structures are expected. Finally, our results can be used in dissipative magnetohydrodynamics simulations of warm compact stars.

Physics↗

DOE OSTI2024

Solid-State Mixed-Potential Electrochemical Sensors for Natural Gas Leak Detection and Quality Control (Final Technical Report)

Mitigation of methane emissions are a critical factor to limiting the impact of the natural gas industry on global climate change. Throughout the period of 2020-2024, the University of New Mexico and its commercialization partner and subcontractor, SensorComm Technologies, Inc. (SCT), have worked together to develop a low-cost Artificial Intelligence (AI)-driven Internet of Things (IoT)-based multi-gas sensor platform for methane emissions detection. In the final year of the project, we extended this work to include hydrogen detection in support of a transition to a hydrogen economy where hydrogen could be transported through existing natural gas infrastructure. Mixed potential electrochemical sensors were first prototyped by ceramic additive manufacturing and then transitioned to conventional ceramic manufacturing tape casting and screen-printing technologies in preparation for mass production. Demonstrated limits of detection of 5 ppm of methane in natural gas and 1 ppm of hydrogen were measured. These limits of detection are among the lowest of solid-state electrochemical sensors that have been reported in the literature or available in the industry. Machine learning algorithms were developed to identify natural gas mixtures with > 98% accuracy level and quantify methane concentrations at 97% accuracy. The presence of hydrogen could also be identified, and its concentration quantified at these accuracy levels. These algorithms were optimized for running on portable computing hardware which enabled > 1 Hz processing rates. A portable packaged IoT system was integrated with the electrochemical sensor in collaboration with SCT. The package consists of readout electronics with < 1 mV resolution, sensor temperature control, and data transmission over cellular wireless and/or Wi-Fi networks. Field testing was performed in two rounds at Colorado State University’s Methane Emissions Technology Evaluation Center (CSU METEC). The first round of testing demonstrated successful measurements of methane from an underground natural gas leak of 20 standard liters per minute (SLPM), which agreed with previously published literature using more sophisticated and expensive analytical equipment. The second round of testing showed that an above ground leak of 2 SLPM of hydrogen could be detected at 32 ft. This project has resulted in six published peer reviewed journal articles, over ten presentations at professional conferences, and one full patent application filed in 2023. Future work on this project includes increased sensitivity, higher production yields, and applications in the hydrogen safety and flare emissions monitoring spaces.

03 NATURAL GAS↗

DOE OSTI2024

In Silico Screening of CO 2 –Dipeptide Interactions for Bioinspired Carbon Capture

Carbon capture, sequestration and utilization offers a viable solution for reducing the total amount of atmospheric CO 2 concentrations. On an industrial scale, amine-based solvents are extensively employed for CO 2 capture through chemisorption. Nevertheless, this method is marked by the high cost associated with solvent regeneration, high vapor pressure, and the corrosive and toxic attributes of by-products, such as nitrosamines. An alternative approach is the biomimicry of sustainable materials that have strong affinity and selectivity for CO 2 . Bioinspired approaches, such as those based on naturally occurring amino acids, have been proposed for direct air capture methodologies. In this study, we present a database consisting of 960 dipeptide molecular structures, composed of the 20 naturally occurring amino acids. Furthermore, those structures were analyzed with a novel computational workflow presented in this work that considers certain interaction sites that determine CO 2 affinity. Density functional theory (DFT) and symmetry-adapted perturbation theory (SAPT) computations were performed for the calculation of CO 2 interaction energies, which allowed to limit our search space to 400 unique dipeptide structures. Using this computational workflow, we provide statistical insights into dipeptides and their affinity for CO 2 binding, as well as design principles that can further enhance CO 2 capture through cooperative binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Fragme∩t: An Open‐Source Framework for Multiscale Quantum Chemistry Based on Fragmentation

Fragment-based quantum chemistry offers a means to circumvent the nonlinear computational scaling of conventional electronic structure calculations, by partitioning a large calculation into smaller subsystems then considering the many-body interactions between them. Variants of this approach have been used to parameterize classical force fields and machine learning potentials, applications that benefit from interoperability between quantum chemistry codes. However, there is a dearth of software that provides interoperability yet is purpose-built to handle the combinatorial complexity of fragment-based calculations. To fill this void we introduce “Fragme∩t”, an open-source software application that provides a tool for community validation of fragment-based methods, a platform for developing new approximations, and a framework for analyzing many-body interactions. Fragme∩t includes algorithms for automatic fragment generation and structure modification, and for distance- and energy-based screening of the requisite subsystems. Checkpointing, database management, and parallelization are handled internally and results are archived in a portable database. Interfaces to various quantum chemistry engines are easy to write and exist already for Q-Chem, PySCF, xTB, Orca, CP2K, MRCC, Psi4, NWChem, GAMESS, and MOPAC. Applications reported here demonstrate parallel efficiencies around 96% on more than 1000 processors but also showcase that the code can handle large-scale protein fragmentation using only workstation hardware, all with a codebase that is designed to be usable by non-experts. Fragme∩t conforms to modern software engineering best practices and is built upon well established technologies including Python, SQLite, and Ray. The source code is available under the Apache 2.0 license.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Designing transparent conductors using forbidden optical transitions

Many semiconductors present weak or forbidden transitions at their fundamental band gaps, inducing a widened region of transparency. This occurs in high-performing n-type transparent conductors (TCs) such as Sn-doped In 2 O 3 (ITO); however, thus far, the presence of forbidden transitions has been neglected in the search for new p-type TCs. To address this, we first compute high-throughput absorption spectra across ~18, 000 semiconductors, showing that over half exhibit forbidden or weak optical transitions at their band edges. Next, we demonstrate that compounds with highly localized band-edge states are more likely to present forbidden transitions. Lastly, we search this set for p-type and n-type TCs with forbidden transitions and, by performing defect calculations, propose unexplored TC candidates such as ambipolar BeSiP 2 , p-type wurtzite BAs, and n-type Ba 2 InGaO 5 , among others. In conclusion, we share our dataset and recommend that future screenings for optical properties consider the impact of forbidden transitions.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Bioaccumulation Factor for Radium in Rio Grande Biota

The Los Alamos National Laboratory (LANL or Laboratory) Environmental Protection and Compliance Division’s Environmental Stewardship Group (EPC-ES) performs the radiological analysis portion of biota dose assessments using the computer program RESRAD-Biota (DOE 2004, DOE 2020). RESRAD-Biota uses a default bioaccumulation factor, B iv , for radium in aquatic animals. This bioaccumulation factor, also listed in Department of Energy (DOE) Standard, DOE-STD-1153-2019, is the ratio of a radionuclide concentration in fresh weight biota to the environment in which it resides, which for aquatic animals is water. DOE-STD-1153-2019 offers conservative values for these ratios that are specific to the radiological contaminant, the biota, and the environment. The B iv in RESRAD-Biota can be used for general screening (Level 1 screening). If the factor proves to be too conservative, then a site-specific B iv may be used. The biota dose assessment of fish from the northern New Mexico region of the Rio Grande fail the general screen, which indicates that further analysis is necessary. Level 2 analysis is site-specific but still has conservative limitations. Level 3 analysis is a more realistic and representative, sitespecific analysis. The purpose of this paper is to use data specific to the Rio Grande to calculate a new aquatic animal radium B iv . This B iv can then be used for Level 3 analysis of aquatic animals specifically in the northern New Mexico region of the Rio Grande. The calculated radium B iv is a useful value for performing detailed, accurate biota dose assessments and calculating dose to fish using RESRAD-Biota when only sediment data are available.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1983

A survey of inlet/engine distortion compatibility

The history of distortion analysis is traced back to its origin in parallel compressor theory which was initially proposed in the late fifties. The development of this theory is reviewed up to its inclusion in the complex computer codes of today. It is found to be a very useful tool to guide development but not quantitative enough to predict compatibility. Dynamic or instantaneous distortion methodology is also reviewed from its origins in the sixties, to its current application in the eighties. Many of the requirements for interpreting instantaneous distortion are considered and illustrated. Statistical methods for predicting the peak distortion are described, and their limitations and advantages discussed. Finally, some Reynolds number and scaling considerations for inlet testing are considered. It is concluded that the deterministic instantaneous distortion methodology combined with distortion testing of engines with screens will remain the primary method of predicting compatibility for the near future. However, parallel compressor analysis and statistical peak distortion prediction will be important tools employed during the development of inlet/engine compatibility.

Bowditch, D. N.↗

NASA NTRS1983

A survey of inlet/engine distortion compatibility

Bowditch, D. N.↗

NASA NTRS1999

A new version of the RDP (Ribosomal Database Project)

The Ribosomal Database Project (RDP-II), previously described by Maidak et al. [ Nucleic Acids Res. (1997), 25, 109-111], is now hosted by the Center for Microbial Ecology at Michigan State University. RDP-II is a curated database that offers ribosomal RNA (rRNA) nucleotide sequence data in aligned and unaligned forms, analysis services, and associated computer programs. During the past two years, data alignments have been updated and now include >9700 small subunit rRNA sequences. The recent development of an ObjectStore database will provide more rapid updating of data, better data accuracy and increased user access. RDP-II includes phylogenetically ordered alignments of rRNA sequences, derived phylogenetic trees, rRNA secondary structure diagrams, and various software programs for handling, analyzing and displaying alignments and trees. The data are available via anonymous ftp (ftp.cme.msu. edu) and WWW (http://www.cme.msu.edu/RDP). The WWW server provides ribosomal probe checking, approximate phylogenetic placement of user-submitted sequences, screening for possible chimeric rRNA sequences, automated alignment, and a suggested placement of an unknown sequence on an existing phylogenetic tree. Additional utilities also exist at RDP-II, including distance matrix, T-RFLP, and a Java-based viewer of the phylogenetic trees that can be used to create subtrees.

Non-NASA Center↗

NASA NTRS2005

Tool for Ranking Research Options

Tool for Research Enhancement Decision Support (TREDS) is a computer program developed to assist managers in ranking options for research aboard the International Space Station (ISS). It could likely also be adapted to perform similar decision-support functions in industrial and academic settings. TREDS provides a ranking of the options, based on a quantifiable assessment of all the relevant programmatic decision factors of benefit, cost, and risk. The computation of the benefit for each option is based on a figure of merit (FOM) for ISS research capacity that incorporates both quantitative and qualitative inputs. Qualitative inputs are gathered and partly quantified by use of the time-tested analytical hierarchical process and used to set weighting factors in the FOM corresponding to priorities determined by the cognizant decision maker(s). Then by use of algorithms developed specifically for this application, TREDS adjusts the projected benefit for each option on the basis of levels of technical implementation, cost, and schedule risk. Based partly on Excel spreadsheets, TREDS provides screens for entering cost, benefit, and risk information. Drop-down boxes are provided for entry of qualitative information. TREDS produces graphical output in multiple formats that can be tailored by users.

Ortiz, James N.↗

DOE OSTI2022

A parametric approach to identify synergistic domains of process intensification for reactive separation

Process intensification aims to combine multiple tasks within multi-functional units to drastically improve economic, energy or sustainability metrics of a chemical process. Limited work exists to systematically identify the synergistic domains where intensification outperforms its nonintensified counterpart. In this work, we computationally derive the synergistic domains of a reactive separation system. Specifically, we first postulate general models for both intensified and nonintensified systems. We use these models to generate data to train a ReLU-type artifical neural network (ANN). Further, the trained ReLU-NN model is formulated as a multi-parametric mixed-integer linear program (mp-MILP), and the critical regions of this mp-MILP define the synergistic feasible domains of intensification. We have derived these synergistic domains of vapor–liquid equilibrium (VLE)-based reactive separation for several industrial applications. These synergistic domains enable quick screening of properties that favor intensification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Auger spectroscopy beyond the ultra-short core-hole relaxation time approximation

Abstract We present a time-dependent computational approach to study Auger electron spectroscopy (AES) beyond the ultra-short core-hole relaxation time approximation and, as a test case, we apply it to the paradigmatic example of a one-dimensional Mott insulator represented by a half-filled Hubbard chain. The Auger spectrum is usually calculated by assuming that, after the creation of a core-hole, the system thermalizes almost instantaneously. This leads to a relatively simple analytical expression that uses the ground-state with a core-hole as a reference state and ignores all the transient dynamics related to the screening of the core-hole. In this picture, the response of the system can be associated to the pair spectral function. On the other hand, in our numerical calculations, the core hole is created by a light pulse, allowing one to study the transient dynamics of the system in terms of the pulse duration and in the non-perturbative regime. Time-dependent density matrix renormalization group calculations reveal that the relaxation process involves the creation of a polarization cloud of doublon excitations that have an effect similar to photo-doping. As a consequence, there is a leak of spectral weight to higher energies into what otherwise would be the Mott gap. For longer pulses, these excited states, mostly comprised of doublons, can dominate the spectrum. By changing the duration of the light-pulse, the entire screening process can be resolved in time.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1979

Man-machine interfaces in LACIE/ERIPS

One of the most important aspects of the interactive portion of the LACIE/ERIPS software system is the way in which the analysis and decision-making capabilities of a human being are integrated with the speed and accuracy of a computer to produce a powerful analysis system. The three major man-machine interfaces in the system are (1) the use of menus for communications between the software and the interactive user; (2) the checkpoint/restart facility to recreate in one job the internal environment achieved in an earlier one; and (3) the error recovery capability which would normally cause job termination. This interactive system, which executes on an IBM 360/75 mainframe, was adapted for use in noninteractive (batch) mode. A case study is presented to show how the interfaces work in practice by defining some fields based on an image screen display, noting the field definitions, and obtaining a film product of the classification map.

Duprey, B. B.↗