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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Engineering Auger recombination in colloidal quantum dots via dielectric screening

Auger recombination is the main non-radiative decay pathway for multi-carrier states of colloidal quantum dots, which affects performance of most of their optical and optoelectronic applications. Outstanding single-exciton properties of CdSe/CdS core/shell quantum dots enable us to simultaneously study the two basic types of Auger recombination channels-negative trion and positive trion channels. Though Auger rates of positive trion are regarded to be much faster than that of negative trion for II-VI quantum dots in literature, our experiments find the two rates can be inverted for certain core/shell geometries. This is confirmed by theoretical calculations as a result of geometry-dependent dielectric screening. By varying the core/shell geometry, both types of Auger rates can be independently tuned for ~1 order of magnitude. Experimental and theoretical findings shed new light on designing quantum dots with necessary Auger recombination characteristics for high-power light-emitting-diodes, lasers, single-molecular tracking, super-resolution microscope, and advanced quantum light sources.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dielectric screening in perovskite photovoltaics

Abstract The performance of perovskite photovoltaics is fundamentally impeded by the presence of undesirable defects that contribute to non-radiative losses within the devices. Although mitigating these losses has been extensively reported by numerous passivation strategies, a detailed understanding of loss origins within the devices remains elusive. Here, we demonstrate that the defect capturing probability estimated by the capture cross-section is decreased by varying the dielectric response, producing the dielectric screening effect in the perovskite. The resulting perovskites also show reduced surface recombination and a weaker electron-phonon coupling. All of these boost the power conversion efficiency to 22.3% for an inverted perovskite photovoltaic device with a high open-circuit voltage of 1.25 V and a low voltage deficit of 0.37 V (a bandgap ~1.62 eV). Our results provide not only an in-depth understanding of the carrier capture processes in perovskites, but also a promising pathway for realizing highly efficient devices via dielectric regulation.

14 SOLAR ENERGY↗
DOE OSTI2024

Natural diversity screening, assay development, and characterization of nylon-6 enzymatic depolymerization

Successes in biocatalytic polyester recycling have raised the possibility of deconstructing alternative polymers enzymatically, with polyamide (PA) being a logical target due to the array of amide-cleaving enzymes present in nature. Here, we screen 40 potential natural and engineered nylon-hydrolyzing enzymes (nylonases), using mass spectrometry to quantify eight compounds resulting from enzymatic nylon-6 (PA6) hydrolysis. Comparative time-course reactions incubated at 40-70 °C showcase enzyme-dependent variations in product distributions and extent of PA6 film depolymerization, with significant nylon deconstruction activity appearing rare. The most active nylonase, a NylC K variant we rationally thermostabilized (an N-terminal nucleophile (Ntn) hydrolase, NylC K -TS, T m = 87.4 °C, 16.4 °C higher than the wild-type), hydrolyzes 0.67 wt% of a PA6 film. Reactions fail to restart after fresh enzyme addition, indicating that substrate-based limitations, such as restricted enzyme access to hydrolysable bonds, prohibit more extensive deconstruction. Overall, this study expands our understanding of nylonase activity distribution, indicates that Ntn hydrolases may have the greatest potential for further development, and identifies key targets for progressing PA6 enzymatic depolymerization, including improving enzyme activity, product selectivity, and enhancing polymer accessibility.

09 BIOMASS FUELS↗
DOE OSTI2023

High-throughput screening of hypothetical metal-organic frameworks for thermal conductivity

Thermal energy management in metal-organic frameworks (MOFs) is an important, yet often neglected, challenge for many adsorption-based applications such as gas storage and separations. Despite its importance, there is insufficient understanding of the structure-property relationships governing thermal transport in MOFs. To provide a data-driven perspective into these relationships, here we perform large-scale computational screening of thermal conductivity k in MOFs, leveraging classical molecular dynamics simulations and 10,194 hypothetical MOFs created using the ToBaCCo 3.0 code. We found that high thermal conductivity in MOFs is favored by high densities (> 1.0 g cm -3 ), small pores (< 10 Å), and four-connected metal nodes. We also found that 36 MOFs exhibit ultra-low thermal conductivity (< 0.02 W m -1 K -1 ), which is primarily due to having extremely large pores (~65 Å). Furthermore, we discovered six hypothetical MOFs with very high thermal conductivity (>10 Wm -1 K -1 ), the structures of which we describe in additional detail.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High-throughput screening of 2D materials identifies p-type monolayer WS2 as potential ultra-high mobility semiconductor

Abstract 2D semiconductors offer a promising pathway to replace silicon in next-generation electronics. Among their many advantages, 2D materials possess atomically-sharp surfaces and enable scaling the channel thickness down to the monolayer limit. However, these materials exhibit comparatively lower charge carrier mobility and higher contact resistance than 3D semiconductors, making it challenging to realize high-performance devices at scale. In this work, we search for high-mobility 2D materials by combining a high-throughput screening strategy with state-of-the-art calculations based on the ab initio Boltzmann transport equation. Our analysis singles out a known transition metal dichalcogenide, monolayer WS 2 , as the most promising 2D semiconductor, with the potential to reach ultra-high room-temperature hole mobilities in excess of 1300 cm 2 /Vs should Ohmic contacts and low defect densities be achieved. Our work also highlights the importance of performing full-blown ab initio transport calculations to achieve predictive accuracy, including spin–orbital couplings, quasiparticle corrections, dipole and quadrupole long-range electron–phonon interactions, as well as scattering by point defects and extended defects.

Chemistry↗
DOE OSTI2026

Data mining and computational screening of Rashba-Dresselhaus splitting and optoelectronic properties in two-dimensional perovskite materials

Recent developments highlighting the promise of two-dimensional perovskites have vastly increased the compositional search space in the perovskite family. This presents a great opportunity for the realization of highly performant devices and practical challenges associated with the identification of candidate materials. High-fidelity computational screening offers great value in this regard. In this study, we carry out a multiscale computational workflow, generating a dataset of two-dimensional perovskites in the Dion-Jacobson and Ruddlesden-Popper phases. Our dataset comprises ten B-site cations, four halogens, and over 20 organic cations across over 2000 materials. We compute electronic properties, thermoelectric performance, and numerous geometric characteristics. Furthermore, we introduce a framework for the high-throughput computation of Rashba-Dresselhaus splitting. Finally, we use this dataset to train machine learning models for the accurate prediction of band gaps, candidate Rashba-Dresselhaus materials, and partial charges. The work presented herein can aid future investigations of two-dimensional perovskites with targeted applications in mind.

14 SOLAR ENERGY↗
DOE OSTI2017

High-Performance Screen-Printed Thermoelectric Films on Fabrics

Printing techniques could offer a scalable approach to fabricate thermoelectric (TE) devices on flexible substrates for power generation used in wearable devices and personalized thermo-regulation. However, typical printing processes need a large concentration of binder additives, which often render a detrimental effect on electrical transport of the printed TE layers. Here, we report scalable screenprinting of TE layers on flexible fiber glass fabrics, by rationally optimizing the printing inks consisting of TE particles (p-type Bi 0.5 Sb 1.5 Te 3 or n-type Bi 2 Te 2.7 Se 0.3 ), binders, and organic solvents. We identified a suitable binder additive, methyl cellulose, which offers suitable viscosity for printability at a very small concentration (0.45–0.60 wt.%), thus minimizing its negative impact on electrical transport. Following printing, the binders were subsequently burnt off via sintering and hot pressing. We found that the nanoscale defects left behind after the binder burnt off became effective phonon scattering centers, leading to low lattice thermal conductivity in the printed n-type material. With the high electrical conductivity and low thermal conductivity, the screen-printed TE layers showed high room-temperature ZT values of 0.65 and 0.81 for p-type and n-type, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Validating deep learning inference during chest X-ray classification for COVID-19 screening

Abstract The new coronavirus unleashed a worldwide pandemic in early 2020, and a fatality rate several times that of the flu. As the number of infections soared, and capabilities for testing lagged behind, chest X-ray (CXR) imaging became more relevant in the early diagnosis and treatment planning for patients with suspected or confirmed COVID-19 infection. In a few weeks, proposed new methods for lung screening using deep learning rapidly appeared, while quality assurance discussions lagged behind. This paper proposes a set of protocols to validate deep learning algorithms, including our ROI Hide-and-Seek protocol, which emphasizes or hides key regions of interest from CXR data. Our protocol allows assessing the classification performance for anomaly detection and its correlation to radiological signatures, an important issue overlooked in several deep learning approaches proposed so far. By running a set of systematic tests over CXR representations using public image datasets, we demonstrate the weaknesses of current techniques and offer perspectives on the advantages and limitations of automated radiography analysis when using heterogeneous data sources.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Using machine learning with optical profilometry for GaN wafer screening

Abstract To improve the manufacturing process of GaN wafers, inexpensive wafer screening techniques are required to both provide feedback to the manufacturing process and prevent fabrication on low quality or defective wafers, thus reducing costs resulting from wasted processing effort. Many of the wafer scale characterization techniques—including optical profilometry—produce difficult to interpret results, while models using classical programming techniques require laborious translation of the human-generated data interpretation methodology. Alternatively, machine learning techniques are effective at producing such models if sufficient data is available. For this research project, we fabricated over 6000 vertical PiN GaN diodes across 10 wafers. Using low resolution wafer scale optical profilometry data taken before fabrication, we successfully trained four different machine learning models. All models predict device pass and fail with 70–75% accuracy, and the wafer yield can be predicted within 15% error on the majority of wafers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Direct genome-scale screening of Gluconobacter oxydans B58 for rare earth element bioleaching

Abstract The transition to a sustainable energy economy will require an enormous increase in the supply of rare earth elements (REEs). Bioleaching offers a promising alternative to conventional hydrometallurgical methods for REE extraction from low-grade ores. However, exploiting this potential remains challenging due to large gaps in our understanding of the genetics involved, and inadequate biological tools to address them. We generated a highly non-redundant whole-genome knockout collection for the bioleaching microbe Gluconobacter oxydans B58, reducing redundancy by 85% compared to the previous best collection. This new collection was directly screened for bioleaching neodymium from a synthetic monazite powder, identifying 89 genes important for bioleaching, 68 of which have not previously been associated with this mechanism. We conducted bench-scale experiments to validate the extraction efficiency of promising strains: 8 demonstrated significant increases in extraction by up to 111% (δ GO_1598 , disruption of the gene encoding the orotate phosphoribosyltransferase enzyme PyrE), and one strain significantly reduced it by 97% (δ GO_1096 , disruption of the gene encoding the GTP-binding protein TypA). Notable changes in pH were only observed for 3 strains, suggesting an important role for non-acid mechanisms in bioleaching. These findings provide valuable insights into further enhancing REE-bioleaching by G. oxydans through genetic engineering.

Marecos, Sabrina (ORCID:0000000158529933)↗
DOE OSTI2020

High-throughput screening for discovery of benchtop separations systems for selected rare earth elements

Abstract Rare earth (RE) elements (scandium, yttrium, and the lanthanides) are critical for their role in sustainable energy technologies. Problems with their supply chain have motivated research to improve separations methods to recycle these elements from end of life technology. Toward this goal, we report the synthesis and characterization of the ligand tris[(1-hydroxy-2-oxo-1,2-dihydropyridine-3-carboxamido)ethyl]amine, H 3 1·TFA (TFA = trifluoroacetic acid), and complexes 1·RE (RE = La, Nd, Dy). A high-throughput experimentation (HTE) screen was developed to quantitatively determine the precipitation of 1·RE as a function of pH as well as equivalents of H 3 1·TFA. This method rapidly determines optimal conditions for the separation of RE mixtures, while minimizing materials consumption. The HTE-predicted conditions are used to achieve the lab-scale separation of Nd/Dy ( SF Nd/Dy = 213 ± 34) and La/Nd ( SF La/Nd = 16.2 ± 0.2) mixtures in acidic aqueous media.

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

High-throughput screening of inorganic compounds for the discovery of novel dielectric and optical materials

Dielectrics are an important class of materials that are ubiquitous in modern electronic applications. Even though their properties are important for the performance of devices, the number of compounds with known dielectric constant is on the order of a few hundred. Here, we use Density Functional Perturbation Theory as a way to screen for the dielectric constant and refractive index of materials in a fast and computationally efficient way. Our results constitute the largest dielectric tensors database to date, containing 1,056 compounds. Details regarding the computational methodology and technical validation are presented along with the format of our publicly available data. In addition, we integrate our dataset with the Materials Project allowing users easy access to material properties. Finally, we explain how our dataset and calculation methodology can be used in the search for novel dielectric compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A chemical genetic screen uncovers a small molecule enhancer of the N-acylethanolamine degrading enzyme, fatty acid amide hydrolase, in Arabidopsis

N-Acylethanolamines (NAEs) are a group of fatty acid amides that play signaling roles in diverse physiological processes in eukaryotes. We used fatty acid amide hydrolase (FAAH) degrades NAE into ethanolamine and free fatty acid to terminate its signaling function. In animals, chemical inhibitors of FAAH for therapeutic treatment of pain and as tools to probe deeper into biochemical properties of FAAH. In a chemical genetic screen for small molecules that dampened the inhibitory effect of N-lauroylethanolamine (NAE 12:0) on Arabidopsis thaliana seedling growth, we identified 6-(2-methoxyphenyl)-1,3-dimethyl-5-phenyl-1H-pyrrolo[3,4-d]pyrimidine-2,4(3 H,6 H)-dione (or MDPD). MDPD alleviated the growth inhibitory effects of NAE 12:0, in part by enhancing the enzymatic activity of Arabidopsis FAAH (AtFAAH). In vitro, biochemical assays showed that MDPD enhanced the apparent Vmax of AtFAAH but did not alter the affinity of AtFAAH for its NAE substrates. Furthermore, structural analogs of MDPD did not affect AtFAAH activity or dampen the inhibitory effect of NAE 12:0 on seedling growth indicating that MDPD is a specific synthetic chemical activator of AtFAAH. Our study demonstrates the feasibility of using an unbiased chemical genetic approach to identify new pharmacological tools for manipulating FAAH- and NAE-mediated physiological processes in plants.

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

Activity screening of environmental metagenomic libraries reveals novel carboxylesterase families

Metagenomics has made accessible an enormous reserve of global biochemical diversity. In order to tap into this vast resource of novel enzymes, we have screened over one million clones from metagenome DNA libraries derived from sixteen different environments for carboxylesterase activity and identified 714 positive hits. Here, we validated the esterase activity of 80 selected genes, which belong to 17 different protein families including unknown and cyclase-like proteins. Three metagenomic enzymes exhibited lipase activity, and seven proteins showed polyester depolymerization activity against polylactic acid and polycaprolactone. Detailed biochemical characterization of four new enzymes revealed their substrate preference, whereas their catalytic residues were identified using site-directed mutagenesis. The crystal structure of the metal-ion dependent esterase MGS0169 from the amidohydrolase superfamily revealed a novel active site with a bound unknown ligand. Thus, activity-centered metagenomics has revealed diverse enzymes and novel families of microbial carboxylesterases, whose activity could not have been predicted using bioinformatics tools.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Large scale computational screening and experimental discovery of novel materials for high temperature CO 2 capture

The implementation of large-scale carbon dioxide capture and storage (CCS) is dependent on finding materials that satisfy several different criteria, the most important being minimising the energy load imposed on the power plant to run the process. The most mature CCS technology, amine scrubbing, leads to a loss of 30% of the electrical work output of the power station without capture, which is far too high for widespread deployment. High-temperature CO 2 absorption looping has emerged as a technology that has the potential to deliver much lower energy penalties, but further work is needed to find and develop an optimal material. Here, we have developed a combined computational and experimental methodology to predict new materials that should have desirable properties for CCS looping, and then select promising candidates to experimentally validate these predictions. This work not only has discovered novel materials for use in high-temperature CCS looping, but analysis of the entirety of the screening enables greater insights into new design strategies for future development.

36 MATERIALS SCIENCE↗
DOE OSTI2018

C2 adsorption in zeolites: in silico screening and sensitivity to molecular models

Efficient separation of ethane and ethylene has been a long-standing challenge for the chemical industry. In this work, we use molecular modeling to identify zeolite and zeotype frameworks that have the potential to be the next-generation solution for the separation of these C2 compounds. Using two different united-atom versions of the transferable potentials for phase equilibria (TraPPE) force field, the zeolitic structures in the database of the International Zeolite Association are screened for the separation of ethane and ethylene. A detailed analysis, with regards to accessibility of favorable sites and sensitivity to molecular models (also considering the explicit-hydrogen TraPPE model for ethane), is carried out on the top-performing structures. This study provides insights on the performance and limitations of molecular models for predicting mixture adsorption in zeolites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

High throughput near infrared screening discovers DNA-templated silver clusters with peak fluorescence beyond 950 nm

In this study, we use high throughput near-infrared (NIR) screening technology to discover abundant new DNA-stabilized silver clusters, Ag N -DNA, that fluoresce in the NIR. These include the longest wavelength Ag N -DNA fluorophores identified to date, with peak emission beyond 950 nm that extends into the NIR II tissue transparency window, and the highest silver content.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Optimizing PtFe intermetallics for oxygen reduction reaction: from DFT screening to in situ XAFS characterization

Rational designing of catalysts to promote the sluggish kinetics of the cathode oxygen reduction reaction in proton exchange membrane fuel cells is still challenging, yet of crucial importance to its commercial application. Here, on the basis of theoretical DFT calculations which suggest that order structured fct-phased PtFe (O-PtFe) with an atomic Pt shell exhibits superior electrocatalytic performance towards the ORR, the desired structure was prepared by using a scalable impregnation–reduction method. The as-prepared O-PtFe delivered enhanced activity (0.68 A mg -1 Pt ) and stability (73% activity retention after 10 000 potential cycles) compared with the corresponding disordered PtFe alloy (D-PtFe) and Pt. To confirm the excellent durability, in situ X-ray absorption fine structure spectroscopy was conducted to probe the local and electronic structure changes of O-PtFe during 10 000 cycle accelerated durability testing. In conclusion, we hope that this facile synthesis method and the in situ XAFS experiment could be readily adapted to other catalyst systems, facilitating the screening of highly efficient ORR catalysts for fuel cell application.

36 MATERIALS SCIENCE↗