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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Extraction of valuable chemicals from food waste via computational solvent screening and experiments

About 1.3 billion tons of global food production end up in landfills and composting, leading to significant anthropogenic greenhouse gas (GHG) emissions. Extracting antioxidant and antimicrobial chemicals (flavonoids, phenolic acids, etc.) from food waste is an economically lucrative valorization strategy but is hindered by efficient solvent selection. Here we perform in silico high throughput screening to identify high solubility solvents for key phenolics and reveal more than 100+ higher-performing solvents than the traditional ethanol and methanol. Solubilities of nine shortlisted solvents are measured and found in reasonable agreement with model predictions. Analysis of the Conductor like Screening Model for Real Solvents (COSMO-RS) σ-profiles and Hansen Solubility Parameters reveals that polarity and hydrogen bonding make dimethylformamide (DMF) an excellent single solvent. We showcase the replacement of high-solubility toxic solvents with green mixtures and demonstrate the approach to potato peel waste. As a result, our work provides a blueprint for solvent selection and generates new insights into extraction from food waste.

09 BIOMASS FUELS↗
DOE OSTI2017

A topological screening heuristic for low-energy, high-index surfaces

Robust ab initio investigations of nanoparticle surface properties require a method to identify candidate low-energy surface facets a priori . By assuming that low-energy surfaces are planes with high atomic density, we devise an efficient algorithm to screen for low-energy surface orientations, even if they have high ( hkl ) miller indices. We successfully predict the observed low-energy, high-index {$10\overline{12} $} and {$10\bar{1}4 $} surfaces of hematite α-Fe 2 O 3 , the {311} surfaces of cuprite Cu 2 O, and the {112} surfaces of anatase TiO 2 . We further tabulate candidate low-energy surface orientations for nine of the most common binary oxide structures. Screened surfaces are found to be generally applicable across isostructural compounds with varying chemistries, although relative surface energies between facets may vary based on the preferred coordination of the surface atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Longitudinal analysis of risk factors for dementia based on Mild Cognitive Impairment Screen results and questionnaire responses from healthy Japanese individuals registered in an online database

Abstract Introduction Despite an urgent need for developing remedial measures against dementia, no disease‐modifying drugs have been developed. Efficient protocols for participant recruitment need to be established for conducting clinical trials. To meet this need, a large‐scale online registry system, the Integrated Registry of Orange Plan (IROOP ® ), was created for healthy individuals. Although the risk factors for dementia have been discussed in our previous studies for a short interval of 6 months, some factors remain controversial. The present study aimed to explore factors affecting longitudinal changes in cognitive function for a longer interval of 18 months using the IROOP ® data. Methods This study assessed the longitudinal changes in the collated data for predicting the risk of dementia and included 473 individuals (175 men and 298 women; mean age 59.6 ± 10.1 years) registered in the IROOP ® between July 5, 2016 and January 15, 2018 who completed the initial questionnaire and brief assessment of cognitive function (Mild Cognitive Impairment Screen) at baseline and the regular questionnaire and the Mild Cognitive Impairment Screen at least once after baseline. Statistical analyses were performed using IBM SPSS, version 23.0, for Windows for demographic data and the MIXED procedure in SAS, version 9.4, for the linear mixed‐effect model. In each analysis, the statistical significance level was set at P < .05. Results Mood, sleep, quality of life, and medical histories including cognition were found to influence longitudinal changes in cognitive function. Discussion Given the multifactorial etiology of dementia, preventive measures targeting multiple domains are required for maintaining cognitive function, instead of focusing on one lifestyle factor.

Ogawa, Masayo↗
DOE OSTI2015

MicroRNA library screening identifies growth-suppressive microRNAs that regulate genes involved in cell cycle progression and apoptosis

Micro(mi)RNAs play important and varied roles in tumorigenesis; however, the full repertoire of miRNAs that affect cancer cell growth is not known. In this study, an miRNA library was screened to identify those that affect the growth of A549 tumor cells. Among 300 miRNAs, miR-28-5p, -323-5p, -510-5p, -552-3p, and -608 were the most effective in inhibiting cell growth. More specifically, overexpressing miR-28-5p, -323-5p, and -510-5p induced G1 arrest, as determined by flow cytometry, whereas that of miR-608 induced cell death in a caspase-dependent manner. Moreover, several genes involved in apoptosis and cell cycle progression were downregulated upon overexpression of each of the five miRNAs, with the functional targets of miR-552-3p and miR-608 confirmed by microarray, quantitative real-time PCR, and luciferase reporter assay. In miR-608-transfected cells, B cell lymphoma 2-like 1 (BCL2L1), D-type cyclin 1 (CCND1), CCND3, cytochrome b5 reductase 3 (CYB5R3), phosphoinositide 3-kinase regulatory subunit 2 (PIK3R2), specificity protein 1 (SP1), and phosphorylated Akt were all downregulated, while Bcl-2-interacting killer (BIK) was upregulated. Moreover, miR-608 was determined to have a suppressive function on tumor growth in an NCI-H460 xenograft model. These findings provide insights into the roles of five miRNAs in growth inhibition and their potential function as cancer therapeutics. - Highlights: • MicroRNAs (miRNAs) affecting cancer cell growth were identified through a screen. • Five miRNAs that inhibit cell proliferation and survival were identified. • MiRNAs modulate various target genes to inhibit cancer cell growth. • These five miRNAs can potentially serve as new agents for cancer treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Large scale nanoparticle screening for small molecule analysis in laser desorption ionization mass spectrometry

Nanoparticles (NPs) have been suggested as efficient matrixes for small molecule profiling and imaging by laser-desorption ionization mass spectrometry (LDI-MS), but so far there has been no systematic study comparing different NPs in the analysis of various classes of small molecules. Here, we present a large scale screening of 13 NPs for the analysis of two dozen small metabolite molecules. Many NPs showed much higher LDI efficiency than organic matrixes in positive mode and some NPs showed comparable efficiencies for selected analytes in negative mode. Our results suggest that a thermally driven desorption process is a key factor for metal oxide NPs, but chemical interactions are also very important, especially for other NPs. Furthermore, the screening results provide a useful guideline for the selection of NPs in the LDI-MS analysis of small molecules.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Functionalized Polymer Thin Films for Plutonium Capture and Isotopic Screening from Aqueous Sources

The rapid screening of plutonium from aqueous sources remains a critical challenge for nuclear nonproliferation efforts. The determination of trace-level Pu isotopes in water requires offsite sample preparation and analysis; therefore, new methods that combine plutonium purification, concentration, and isotopic screening in a fieldable detection system will provide an invaluable tool for nuclear safeguards. This contribution describes the development and characterization of thin polymer-ligand films for the isolation and concentration of waterborne Pu for direct spectroscopic analyses. Submicron thin films were prepared through spin coating onto Si wafers and consisted of combinations of polystyrene (PS) with dibenzoylmethane, thenoyltrifluoroacetone, and di(2-ethylhexyl)phosphoric acid (HDEHP). Pu uptake studies from solutions at pH from 2.3 to 6.3 indicated that only films containing HDEHP exhibited significant recovery of Pu. High alpha spectroscopy peak energy resolutions were achieved for PS-HDEHP films over a range of film thicknesses from 30 to 250 nm. Furthermore, a separate study was performed to evaluate uptake from a primarily Pu(V) solution where it was observed that doubling the HDEHP loading in the film increased uptake of Pu by an order of magnitude. X-ray photoelectron spectroscopy (XPS) analysis revealed that HDEHP was highly concentrated within the first few nanometers of the film at the higher loading. XPS analysis also revealed that, in the presence of water, HDEHP was stripped from the surface layer of the film at circumneutral pH. While significant losses of ligand were seen in all samples, higher loadings of HDEHP resulted in measurable amounts of ligand retained after a 12-h soak in water. Findings of this study are being used to guide the development of thin-film composite membrane-based detection methods for the rapid, fieldable analysis of Pu in water.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A Simple Computational Proxy for Screening Magnetocaloric Compounds

Alternating cycles of isothermal magnetization and adiabatic demagnetization applied to a magnetocaloric material can drive refrigeration in very much the same manner as cycles of gas compression and expansion. The material property of interest in finding candidate magnetocaloric materials is ΔS M , their gravimetric entropy change upon application of a magnetic field under isothermal conditions. There is, however, no general method for screening materials for such an entropy change without actually performing the relevant, time- and effort-intensive magnetic measurements. Here we propose a simple computational proxy based on performing nonmagnetic and magnetic density functional theory calculations on magnetic materials. This proxy, which we term the magnetic deformation Σ M , is a measure of how much the unit cell deforms comparing with the relaxed structures with and without the inclusion of spin polarization. Σ M appears to correlate very well with experimentally measured magnetic entropy change values. Here, the proxy has been tested against 33 ferromagnetic materials with known ΔS M , including nine materials newly measured for this study. It has then been used to screen 134 ferromagnetic materials for which the magnetic entropy has not yet been reported, identifying 30 compounds as being promising for further study. As a demonstration of the effectiveness of our approach, we have prepared one of these compounds and measured its isothermal entropy change. MnCoP, with a T C of 575 K, shows a maximal ΔS M of –6.0 J kg –1 K –1 for an H = 5 T applied field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Searching for “Defect-Tolerant” Photovoltaic Materials: Combined Theoretical and Experimental Screening

Recently, we and others have proposed screening criteria for 'defect-tolerant' photovoltaic (PV) absorbers, identifying several classes of semiconducting compounds with electronic structures similar to those of hybrid lead-halide perovskites. In this work, we reflect on the accuracy and prospects of these new design criteria through a combined experimental and theoretical approach. We construct a model to extract photoluminescence lifetimes of six of these candidate PV absorbers, including four (InI, SbSI, SbSeI, and BiOI) for which time-resolved photoluminescence has not been previously reported. The lifetimes of all six candidate materials exceed 1 ns, a threshold for promising early stage PV device performance. However, there are variations between these materials, and none achieve lifetimes as high as those of the hybrid lead-halide perovskites, suggesting that the heuristics for defect-tolerant semiconductors are incomplete. Here, we explore this through first-principles point defect calculations and Shockley-Read-Hall recombination models to describe the variation between the measured materials. In light of these insights, we discuss the evolution of screening criteria for defect tolerance and high-performance PV materials.

14 SOLAR ENERGY↗
DOE OSTI2020

Suspect and Nontarget Screening for Contaminants of Emerging Concern in an Urban Estuary

This study used suspect and nontarget screening with high-resolution mass spectrometry to characterize the occurrence of contaminants of emerging concern (CECs) in the nearshore marine environment of Puget Sound (WA). In total, 87 non-polymeric CECs were identified; those confirmed with reference standards (45) included pharmaceuticals, herbicides, vehicle-related compounds, plasticizers, and flame retardants. Eight polyfluoroalkyl substances were detected; perfluorooctanesulfonic acid (PFOS) concentrations were as high as 72-140 ng/L at one location. Low levels of methamphetamine were detected in 41% of the samples. Transformation products of pesticides were tentatively identified, including two novel transformation products of tebuthiuron. While a hydrodynamic simulation, analytical results, and dilution calculations demonstrated the prevalence of wastewater effluent to nearshore marine environments, the identity and abundance of selected CECs revealed the additional contributions from stormwater and localized urban and industrial sources. For the confirmed CECs, risk quotients were calculated based on concentrations and predicted toxicities, and eight CECs had risk quotients >1. Dilution in the marine estuarine environment lowered the risks of most wastewater-derived CECs, but dilution alone is insufficient to mitigate risks of localized inputs. These findings highlighted the necessity of suspect and nontarget screening and revealed the importance of localized contamination sources in urban marine environments.

Tian, Zhenyu↗
DOE OSTI2023

Identifying High-Performance Metal–Organic Frameworks for Low-Temperature Oxygen Recovery from Helium by Computational Screening

Metal–organic frameworks (MOFs) are an important class of porous crystalline materials for applications ranging from gas adsorption and separation to catalysis. There are thousands of potential MOFs available for separation applications. Here, we developed a computational approach to screen MOFs for the separation of oxygen–helium mixtures at low temperatures (100–200 K), conditions that were motivated by issues associated with propulsion in space-based settings. We used detailed molecular simulations for a small number of MOFs to develop screening methods that were then used to estimate the optimum temperatures for separations using pressure swing adsorption for 2932 MOFs from the CoRE MOF database and the swing capacity and oxygen–helium selectivity at these temperatures. We used the stability of the best-performing structures in the presence of moisture as a means to provide a short list of high-performance materials. In addition to identifying specific materials for oxygen–helium separations, this approach could prove useful for selecting adsorbents for other gas separations.

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

Machine Learning-Driven Solvent Screening for Biobased 2,3-Butanediol Extraction

Biobased 2,3-butanediol (2,3-BDO) is a valuable biomass-derived chemical due to its versatility in being transformed into a wide variety of products. However, the separation and purification of 2,3-BDO from fermentation broth remain a significant challenge owing to its high boiling point and hydrophilic nature. Herein, we developed a machine learning (ML)-based screening workflow that uses molecular calculations as training data and requires only a small number of experimental measurements for validation to identify alternative solvent candidates for the liquid–liquid extraction (LLE) of 2,3-BDO from aqueous solution. In particular, 130 density functional theory (DFT) calculations with the implicit solvation method not only built a correlation between the computational partition coefficient and the experimental distribution coefficient of 2,3-BDO but also parameterized an Extra-Trees ML model to screen the distribution coefficient for a wider range of 6717 organic solvents. The experimental measurements of only 24 solvents were needed to validate the computational results. A list of 50 prioritized solvents was proposed for 2,3-BDO LLE, and seven additional experimental measurements were conducted to further verify our selected solvents. The impact of the extraction temperature and solvent-to-feed ratio was also investigated for selected solvents in experiments. Furthermore, this work suggested alternative solvents for 2,3-BDO LLE and proposed a versatile workflow that requires fewer experiments and can be applied to a broader range of LLE studies.

Extraction↗
DOE OSTI2024

High-Throughput Screening for Boride Superconductors

A high-throughput screening using density functional calculations is performed to search for stable boride superconductors from the existing materials database. The workflow employs the fast frozen-phonon method as the descriptor to evaluate the superconducting properties quickly. Twenty-three stable candidates were identified during the screening. The superconductivity was obtained earlier experimentally or computationally for almost all found binary compounds. Previous studies on ternary borides are very limited. Here our extensive search among ternary systems confirmed superconductivity in known systems and found several new compounds. Among these discovered superconducting ternary borides, TaMo 2 B 2 shows the highest superconducting temperature of ∼12 K. Most predicted compounds were synthesized previously; therefore, our predictions can be examined experimentally. Our work also demonstrates that the boride systems can have diverse structural motifs that lead to superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Creation of Polymer Datasets with Targeted Backbones for Screening of High-Performance Membranes for Gas Separation

A simple approach was developed to computationally construct a polymer dataset by combining simplified molecular-input line-entry system (SMILES) strings of a targeted polymer backbone and a variety of molecular fragments. This method was used to create 14 polymer datasets by combining seven polymer backbones and molecules from two large molecular datasets (MOSES and QM9). Polymer backbones that were studied include four polydimethylsiloxane (PDMS) based backbones, poly(ethylene oxide) (PEO), poly(allyl glycidyl ether) (PAGE), and polyphosphazene (PPZ). The generated polymer datasets can be used for various cheminformatics tasks, including high-throughput screening for gas permeability and selectivity. This study utilized machine learning (ML) models to screen the polymers for CO2/CH4 and CO2/N2 gas separation using membranes. Several polymers of interest were identified. Here the results highlight that employing an ML model fitted to polymer selectivities leads to higher accuracy in predicting polymer selectivity compared to using the ratio of predicted permeabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Nonempirical Range-Separated Hybrid Functional with Spatially Dependent Screened Exchange

Electronic structure calculations based on density functional theory (DFT) have successfully predicted numerous ground-state properties of a variety of molecules and materials. However, exchange and correlation functionals currently used in the literature, including semilocal and hybrid functionals, are often inaccurate to describe the electronic properties of heterogeneous solids, especially systems composed of building blocks with large dielectric mismatch. Here, in this study, we present a dielectric-dependent range-separated hybrid functional, screened-exchange range-separated hybrid (SE-RSH), for the investigation of heterogeneous materials. We define a spatially dependent fraction of exact exchange inspired by the static Coulomb-hole and screened-exchange (COHSEX) approximation used in many-body perturbation theory, and we show that the proposed functional accurately predicts the electronic structure of several nonmetallic interfaces, three- and two-dimensional, pristine, and defective solids and nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Energy-Screened Many-Body Expansion for Protein–Ligand Interactions: Examining Convergence for Metalloenzymes Through Seven–Body Interactions

Fragment-based quantum chemistry is a powerful strategy for calculating protein−ligand interaction energies using quantum chemistry methods. Rigorous convergence often requires hundreds of atoms in the protein binding-site model, especially if that model is constructed using distance-based criteria to select amino acid residues, while three- and four-body calculations exhibit instability related to combinatorial proliferation in the number of subsystem calculations. Here, we report an energy-based screening protocol for the many-body expansion applied to protein−ligand interactions, implemented in the open-source FRAGME∩T code. Using a combination of aggressive screening based on semiempirical quantum chemistry, with an improved graph-theoretical algorithm to eliminate unimportant subsystems, we are able to perform n-body calculations up to n = 7 using density functional theory in triple-ζ basis sets. Distance cutoffs further reduce the cost without compromising accuracy. Rapid and stable convergence of the many-body expansion is obtained by n = 4, for a pair of metalloenzymes in which a divalent ion coordinates directly to the ligand. As compared to previous results that relied solely on distance cutoffs, oscillations in the n-body corrections are reduced or eliminated, although residual errors remain in one case. This work demonstrates that benchmark-quality protein−ligand interaction energies can be systematically converged using a method with excellent parallel efficiency and scalability.

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

Screening Ionic Liquids Based on Ionic Volume and Electrostatic Potential Analyses

Ionic liquids are known to have tunable solvation properties, based on the pairing of different anions and cations, but the compositional landscape is vast and challenging to navigate efficiently. Some computational screening protocols are available, but they can be either time-consuming or difficult to implement. Herein, we perform a detailed investigation of the fundamental role of electrostatic interactions in these systems. We effectively develop a bridge between the previous volume-based approach (VBA) with a quantum structure–property relationship (QSPR) approach to create fast, simple screening guidelines. We propose a new parameter that is applicable to both monovalent and multivalent ions, the ionic polarity index (IPI), which is defined as the ratio of the average electrostatic surface potential ($\bar{V}$) of the ion to the net charge of the ion (q). The IPI correlation has been tested on a diverse dataset of 121 ions and reliable predictions can be obtained within a homologous series of ionic liquid compounds.

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

Scalable Screening of Soft Matter: A Case Study of Mixtures of Ionic Liquids and Organic Solvents

Room-temperature ionic liquids (RTILs) are a class of organic salts that are liquid at room temperature. Their physiochemical properties, including low vapor pressure and wide electrochemical stability window, have expedited their use as electrolytes in many electrochemical applications; yet, the slow transport properties of many RTILs have limited their utility in some applications. This issue is often mitigated by solvating ionic liquids in neutral organic solvents. To date, however, solvent interactions have only been explored for a small number of solvents, particularly acetonitrile and propylene carbonate, at only a few compositions. Here, we use molecular dynamics simulations in the context of a computational screening approach to study mixtures of ionic liquids in many different solvents at a range of concentrations. Building on prior work, we again find that ionic liquid diffusivity increases monotonically with greater solvent concentration. In contrast to prior work, we find that pure solvent diffusivity, not polarity, is the most influential solvent property on mixture behavior. We also explore the concentration dependence of ionic conductivity and find maxima at intermediate concentrations. Experimental conductivity measurements, inspired by the computational screening study, support this observation with qualitatively consistent results. These results can further guide the selection of solvents for electrochemical applications of RTILs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Computational Screening of Cationic Zeolites for n -Butane/Methane Separations Using Quantitatively Accurate First-Principles-Derived Force Fields

We developed force fields for linear alkanes in Na and Ca-exchanged zeolites based on periodic first-principles calculations with coupled cluster corrections. These force fields were validated by comparing the simulated adsorption properties with extensive experimental data. As an example of using these force fields, we screened silica and aluminosilicate zeolites for separation of n-butane/methane mixtures in several different separation processes. A key step in this screening was the use of an interpolation method to create accurate zeolite structures that take account of the lattice constant changes for different Si/Al ratios for a given zeolite topology. We focused on zeolite structures that have known synthesis routes, so the materials selected from our calculations can be tested experimentally. Several promising materials that show good separation performance were selected for more detailed simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗