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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Edge-Confined Excitons in Monolayer Black Phosphorus

Quantum confinement of two-dimensional excitons in van der Waals materials via electrostatic trapping, lithographic patterning, Moiré potentials, and chemical implantation has enabled significant advances in tailoring light emission from nanostructures. While such approaches rely on complex preparation of materials, natural edges are a ubiquitous feature in layered materials and provide a different approach for investigating quantum-confined excitons. Here, we observe that certain edge sites of monolayer black phosphorus (BP) strongly localize the intrinsic quasi-one-dimensional excitons, yielding sharp spectral lines in photoluminescence, with nearly an order of magnitude line width reduction. Through structural characterization of BP edges using transmission electron microscopy and first-principles GW plus Bethe–Salpeter equation (GW-BSE) calculations of exemplary BP nanoribbons, we find that certain atomic reconstructions can strongly quantum-confine excitons resulting in distinct emission features, mediated by local strain and screening. Here we observe linearly polarized luminescence emission from edge reconstructions that preserve the mirror symmetry of the parent BP lattice, in agreement with calculations. Furthermore, we demonstrate efficient electrical switching of localized edge excitonic luminescence, whose sites act as excitonic transistors for emission. Localized emission from BP edges motivates exploration of nanoribbons and quantum dots as hosts for tunable narrowband light generation, with future potential to create atomic-like structures for quantum information processing applications as well as exploration of exotic phases that may reside in atomic edge structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Multiple monoenergetic gamma radiography (MMGR) with a compact superconducting cyclotron

Smuggling of special nuclear materials and nuclear devices through borders and ports of entry constitutes a major risk to global security. Technologies are needed to reliably screen the flow of commerce for the presence of high-Z materials such as uranium and plutonium. Here, we present an experimental proof-of-concept of a technique that uses inelastic (p,p') nuclear reactions to generate monoenergetic photons, which provide means to measure the areal density and the effective-Z (Z eff ) of an object with an accuracy surpassing that achieved by current methods. We use an ION-12 SC superconducting 12 MeV proton cyclotron to produce 4.4, 6.1, 6.9, and 7.1 MeV photons from a variety of nuclear reactions. Using these photons in a transmission mode, we show that we are able to accurately reconstruct the areal densities and Zeff of a test object. This methodology could enable mobile applications to screen commercial cargoes with high material specificity, providing a means of distinguishing common cargo materials from high-Z materials that include uranium and plutonium.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Capacitive response of biological membranes

We present a minimal model to analyze the capacitive response of a biological membrane subjected to a step voltage via blocking electrodes. Through a perturbative analysis of the underlying electrolyte transport equations, we show that the leading-order relaxation of the transmembrane potential is governed by a capacitive timescale, τ_{C}=λ_{D}L/D(2+Γδ^{M}/L/4+Γδ^{M}/λ_{D}), where λ_{D} is the Debye screening length, L is the electrolyte width, Γ is the ratio of the permittivity of the electrolyte to the membrane, δ^{M} is the membrane thickness, and D is the ionic diffusivity. This timescale is considerably shorter than the traditional RC timescale λ_{D}L/D for a bare electrolyte due to the membrane's low permittivity and finite thickness. Beyond the linear regime, however, salt diffusion in the bulk electrolyte drives a secondary, nonlinear relaxation process of the transmembrane potential over a longer timescale τ_{L}=L^{2}/4π^{2}D. A simple equivalent-circuit model accurately captures the linear behavior, and the perturbation expansion remains applicable across the entire range of observed physiological transmembrane potentials. Together, these findings underscore the importance of the faster capacitive timescale and nonlinear effects on the bulk diffusion timescale in determining transmembrane potential dynamics for a range of biological systems.

Farhadi, Jafar↗
DOE OSTI2020

ARDD 2020: from aging mechanisms to interventions

Aging is emerging as a druggable target with growing interest from academia, industry and investors. New technologies such as artificial intelligence and advanced screening techniques, as well as a strong influence from the industry sector may lead to novel discoveries to treat age-related diseases. The present review summarizes presentations from the 7 th Annual Aging Research and Drug Discovery (ARDD) meeting, held online on the 1 st to 4 th of September 2020. The meeting covered topics related to new methodologies to study aging, knowledge about basic mechanisms of longevity, latest interventional strategies to target the aging process as well as discussions about the impact of aging research on society and economy. More than 2000 participants and 65 speakers joined the meeting and we already look forward to an even larger meeting next year. Please mark your calendars for the 8 th ARDD meeting that is scheduled for the 31 st of August to 3 rd of September, 2021, at Columbia University, USA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Microwave-Assisted Preparation of Luminescent Inorganic Materials: A Fast Route to Light Conversion and Storage Phosphors

Luminescent inorganic materials are used in several technological applications such as light-emitting displays, white LEDs for illumination, bioimaging, and photodynamic therapy. Usually, inorganic phosphors (e.g., complex oxides, silicates) need high temperatures and, in some cases, specific atmospheres to be formed or to obtain a homogeneous composition. Low ionic diffusion and high melting points of the precursors lead to long processing times in these solid-state syntheses with a cost in energy consumption when conventional heating methods are applied. Microwave-assisted synthesis relies on selective, volumetric heating attributed to the electromagnetic radiation interaction with the matter. The microwave heating allows for rapid heating rates and small temperature gradients yielding homogeneous, well-formed materials swiftly. Luminescent inorganic materials can benefit significantly from the microwave-assisted synthesis for high homogeneity, diverse morphology, and rapid screening of different compositions. The rapid screening allows for fast material investigation, whereas the benefits of enhanced homogeneity include improvement in the optical properties such as quantum yields and storage capacity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

High-Throughput Analysis of Materials for Chemical Looping Processes

Chemical looping is a promising approach for improving the energy efficiency of many industrial chemical processes. However, a major limitation of modern chemical looping technologies is the lack of suitable active materials to mediate the involved subreactions. Identification of suitable materials has been historically limited by the scarcity of high-temperature (>600 °C) thermochemical data to evaluate candidate materials. An accuratethermodynamic approach is demonstrated here to rapidly identify active materials which is applicable to a wide variety of chemical looping chemistries. Application of this analysis to chemical looping combustion correctly classifies 17/17 experimentally studied redox materials by their viability and identifies over 1300 promising yet previously unstudied active materials. This approach is further demonstrated by analyzing redox pairs for mediating a novel chemical looping process for producing pure SO2 from raw sulfur and air which could provide a more efficient and lower emission route to sulfuric acid. 12 promising redox materials for this process are identified, two of which are supported by previous experimental studies of their individual oxidation and reduction reactions. This approach provides the necessary foundation for connecting process design with high-throughput material discovery to accelerate the innovation and development of a wide range of chemical looping technologies.

chemical looping↗
DOE OSTI2023

Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions

Abstract Reliably identifying synthesizable inorganic crystalline materials is an unsolved challenge required for realizing autonomous materials discovery. In this work, we develop a deep learning synthesizability model ( SynthNN ) that leverages the entire space of synthesized inorganic chemical compositions. By reformulating material discovery as a synthesizability classification task, SynthNN identifies synthesizable materials with 7× higher precision than with DFT-calculated formation energies. In a head-to-head material discovery comparison against 20 expert material scientists, SynthNN outperforms all experts, achieves 1.5× higher precision and completes the task five orders of magnitude faster than the best human expert. Remarkably, without any prior chemical knowledge, our experiments indicate that SynthNN learns the chemical principles of charge-balancing, chemical family relationships and ionicity, and utilizes these principles to generate synthesizability predictions. The development of SynthNN will allow for synthesizability constraints to be seamlessly integrated into computational material screening workflows to increase their reliability for identifying synthetically accessible materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders

We report the design/discovery of new materials is highly nontrivial owing to the near-infinite possibilities of material candidates and multiple required property/performance objectives. Thus, machine learning tools are now commonly employed to virtually screen material candidates with desired properties by learning a theoretical mapping from material-to-property space, referred to as the forward problem. However, this approach is inefficient and severely constrained by the candidates that the human imagination can conceive. Thus, in this work on polymers, we tackle the materials discovery challenge by solving the inverse problem: directly generating candidates that satisfy desired property/performance objectives. We utilize syntax-directed variational autoencoders (VAE) in tandem with Gaussian process regression (GPR) models to discover polymers expected to be robust under three extreme conditions: (1) high temperatures, (2) high electric field, and (3) high temperature and high electric field, useful for critical structural, electrical, and energy storage applications. This approach to learn from and augment) human ingenuity is general and can be extended to discover polymers with other targeted properties and performance measures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Scalable, two–stage, autoinduction of recombinant protein expression in E. coli utilizing phosphate depletion

We report the scalable production of recombinant proteins in Escherichia coli, reliant on tightly controlled autoinduction, triggered by phosphate depletion in the stationary phase. The method, reliant on engineered strains and plasmids, enables improved protein expression across scales. Expression levels using this approach have reached as high as 55% of the total cellular protein. The initial use of the method in instrumented fed–batch fermentations enables cell densities of ~30 gCDW/L and protein titers up to 8.1 ± 0.7 g/L (~270 mg/gCDW). The process has also been adapted to an optimized autoinduction media, enabling routine batch production at culture volumes of 20 μl (384–well plates), 100 μl (96–well plates), 20 ml, and 100 ml. In batch cultures, cell densities routinely reach ~5–7 gCDW/L, offering protein titers above 2 g/L. Here, the methodology has been validated with a set of diverse heterologous proteins and is of general use for the facile optimization of routine protein expression from high throughput screens to fed–batch fermentation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Nonequilibrium Thermodynamics of Colloidal Gold Nanocrystals Monitored by Ultrafast Electron Diffraction and Optical Scattering Microscopy

Metal nanocrystals exhibit important optoelectronic and photocatalytic functionalities in response to light. These dynamic energy conversion processes have been commonly studied by transient optical probes to date, but an understanding of the atomistic response following photoexcitation has remained elusive. In this paper, we use femtosecond resolution electron diffraction to investigate transient lattice responses in optically excited colloidal gold nanocrystals, revealing the effects of nanocrystal size and surface ligands on the electron–phonon coupling and thermal relaxation dynamics. First, we uncover a strong size effect on the electron–phonon coupling, which arises from reduced dielectric screening at the nanocrystal surfaces and prevails independent of the optical excitation mechanism (i.e., inter- and intraband). Second, we find that surface ligands act as a tuning parameter for hot carrier cooling. Particularly, gold nanocrystals with thiol-based ligands show significantly slower carrier cooling as compared to amine-based ligands under intraband optical excitation due to electronic coupling at the nanocrystal/ligand interfaces. Finally, we spatiotemporally resolve thermal transport and heat dissipation in photoexcited nanocrystal films by combining electron diffraction with stroboscopic elastic scattering microscopy. Taken together, we resolve the distinct thermal relaxation time scales ranging from 1 ps to 100 ns associated with the multiple interfaces through which heat flows at the nanoscale. Our findings provide insights into optimization of gold nanocrystals and their thin films for photocatalysis and thermoelectric applications.

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

Inkless, dry printing nanographene via in-Situ Coordinated laser ablation and sintering processes

Printing carbon, such as graphene and other carbon structures, for flexible and printed electronics currently relies on either ink-based printing, laser-induced forward transfer (LIFT), or laser-induced graphitization (LIG) to convert carbon-rich precursor materials, such as polymers, to graphene-like carbon structures. Liquid inks contain toxic solvents, surfactants, and stabilizing additives that degrade electrical conductivity and require high-temperature post-processing. On the other hand, LIG is limited by the substrate. Here, this study introduces an additive manufacturing method for dry-printing carbon nanomaterials, ranging from amorphous carbon to crystalline graphene-like structures, on various substrates. The system utilizes laser ablation of a solid graphite target to create pure carbon nanoparticles in situ and on demand. An inert gas carries the nanoparticles onto the substrate, where they can be deposited either as amorphous structures or laser-sintered in real time to form various graphitic structures. The study of laser processing parameters, specifically fluence and pulse repetition frequency, revealed three unique regimes of nanostructure evolution that influence the morphological and electrical properties of these printed structures. Raman spectroscopy confirmed graphitization with a resistivity slightly higher than that of the bulk graphite target. The conductivity/resistivity could be tuned as a function of sintering laser power. Scanning transmission electron microscopy (STEM) revealed that turbostratic nanographene formed with an interlayer spacing of 0.40 nm. Despite ink-based printing methods, such as screen printing, inkjet printing (IJP), and aerosol jet printing (AJP), this eco-friendly and green manufacturing technique could eliminate toxic chemicals, reduce environmental impact, and enable single-step fabrication of carbon-based devices for applications in wearable sensors, energy storage, flexible electronics, and Internet of Things (IoT) devices.

Additive nanomanufacturing↗
DOE OSTI2023

Pretreatment of Algae for the Production of Fuels and Chemical Coproducts

Algal biomass is a promising resource for producing renewable fuels and chemicals, but despite decades of research, algal biorefining remains in a pre-commercial state. Recent economic analyses have indicated that high-value co-products are necessary to offset the cost of fuel production, implying the need for algae fractionation technology. One promising fractionation approach is Combined Algal Processing (CAP), which pretreats and extracts algal biomass to produce a fermentable aqueous hydrolysate, an organic lipid fraction, and a residual solids fraction. The CAP approach has historically employed a dilute acid pretreatment to lyse cells and solubilize algal carbohydrates for fermentation of the hydrolysate phase, but we recently identified alternative pretreatments with the potential to decrease costs and environmental impacts, including different implementations of dilute acid pretreatment, dilute alkali pretreatment, enzymatic pretreatment, and flash hydrolysis. We conducted a screening of six different pretreatment approaches across nine algae strains of varying composition, and measured pretreatment effectiveness as a combination of carbon and nitrogen solubilization, lipid extraction yield, and lipid speciation. In this screening, we found traditional dilute acid pretreatment to provide the most robust pretreatment performance, though other pretreatments were competitive, and some performed better for certain strains of algae. These results highlight the interplay between algae composition and pretreatment effectiveness.

algae↗
DOE OSTI2023

eYGFPuv-Assisted Transgenic Selection in Populus deltoides WV94 and Multiplex Genome Editing in Protoplasts of P. trichocarpa × P. deltoides Clone ‘52-225’

Although CRISPR/Cas-based genome editing has been widely used for plant genetic engineering, its application in the genetic improvement of trees has been limited, partly because of challenges in Agrobacterium-mediated transformation. As an important model for poplar genomics and biotechnology research, eastern cottonwood (Populus deltoides) clone WV94 can be transformed by A. tumefaciens, but several challenges remain unresolved, including the relatively low transformation efficiency and the relatively high rate of false positives from antibiotic-based selection of transgenic events. Moreover, the efficacy of CRISPR-Cas system has not been explored in P. deltoides yet. Here, we first optimized the protocol for Agrobacterium-mediated stable transformation in P. deltoides WV94 and applied a UV-visible reporter called eYGFPuv in transformation. Our results showed that the transgenic events in the early stage of transformation could be easily recognized and counted in a non-invasive manner to narrow down the number of regenerated shoots for further molecular characterization (at the DNA or mRNA level) using PCR. We found that approximately 8.7% of explants regenerated transgenic shoots with green fluorescence within two months. Next, we examined the efficacy of multiplex CRISPR-based genome editing in the protoplasts derived from P. deltoides WV94 and hybrid poplar clone ‘52-225’ (P. trichocarpa × P. deltoides clone ‘52-225’). The two constructs expressing the Trex2-Cas9 system resulted in mutation efficiency ranging from 31% to 57% in hybrid poplar clone 52-225, but no editing events were observed in P. deltoides WV94 transient assay. The eYGFPuv-assisted plant transformation and genome editing approach demonstrated in this study has great potential for accelerating the genome editing-based breeding process in poplar and other non-model plants species and point to the need for additional CRISPR work in P. deltoides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

The accurate prediction of molecular properties is important for the rational design and the advancement of green chemistry and sustainable materials research. However, the predictive power of traditional computational chemistry methods is limited due to computational restrictions. Here, in this study, we examine an alternative approach to the accurate prediction of properties of organic compounds: natural language processing (NLP)-based molecular embedding. Using viscosity, partition coefficient (log P), and enthalpy of vaporization as test properties through a survey of comprehensive datasets comprising 5695 data points for viscosity, 25 870 data points for log P, and 2296 data points for enthalpy of vaporization. These are important properties for the design of greener, safer, and sustainable chemical processes. Models were trained using NLP methods such as Mol2vec and fine-tuned ChemBERTa, and results were compared with traditional input featurization techniques such as Morgan fingerprints and quantum chemistry derived sigma profiles and DFT features. Among the various machine learning models, Mol2vec demonstrated superior predictive capabilities, achieving the highest correlation coefficient (R 2 = 0.945) and lowest RMSE (0.106 mPa s) for viscosity, as well as high accuracy for log P and enthalpy of vaporization predictions. These findings establish the Mol2vec featurization technique, graph-convolutional neural networks (GCNN), and fine-tuned ChemBERTa model as powerful tools for predictive modeling of organic compounds properties, offering a significant improvement over previously used featurization techniques and opening up strategies for very-high-throughput computational screening. Finally, we integrated ML models with hybrid language-model-based generative adversarial networks (LM-GAN) to generate novel molecular sequences with desirable properties for different research applications. The ability to computationally design solvents with lower viscosity, lower log P, and lower enthalpy of vaporization offers a data-driven route to accelerating the discovery of sustainable alternatives to traditionally toxic solvents.

ChemBERTa↗
DOE OSTI2020

Discovery of single-atom alloy catalysts for CO 2 -to-methanol reaction by density functional theory calculations

The transformations of CO 2 molecules into valuable products are of increasing interest due to the negative impact of anthropogenic CO 2 emissions on global warming. The CO 2 -to-methanol hydrogenation is an economically profitable reaction of carbon fixation, but it still steps away from widespread industrialization because of the lack of efficient and selective catalysts. Recently, single-atom alloy (SAA) catalysts have been developed to work remarkably in CO 2 hydrogenation reactions. Doping isolated single atoms into metallic catalyst can dramatically alter the catalytic performance of the host. Here, we have performed a screening discovery on Ru and 6 RuX (X = Fe, Co, Ni, Cu, Ir and Pt) SAAs using density functional theory (DFT) computations. We considered 13 possible elementary reactions in 4 possible reaction pathways on Ru and all RuX surfaces. In the computed mechanisms, we found that the formation of *H 2 COOH and *HCOO intermediates plays a critical role in determining catalysts’ activities. Doping Co and Pt isolated single atoms into Ru surface can thermodynamically and kinetically facilitate these intermediates formation processes, eventually promoting the production of methanol. The combination of weak binding and enhanced charge redistribution on RuCo and RuPt surfaces give them improved catalytic activities over pure Ru. This work will ultimately facilitate the discovery and development of SAAs for CO 2 to methanol, serving as guidance to experiments and theoreticians alike.

25 ENERGY STORAGE↗
DOE OSTI2022

Investigating the possible existence of hyper-heavy nuclei in a neutron-star environment

The synthesis of hyper-heavy elements is investigated under conditions simulating neutron star environment. The constrained molecular dynamics approach is used to simulate low energy collisions of extremely n-rich nuclei. A new type of the fusion barrier due to a “neutron wind” is observed when the effect of neutron star environment (screening of Coulomb interaction) is introduced implicitly. When introducing also a background of surrounding nuclei, the nuclear fusion becomes possible down to temperatures of 10 8 K and synthesis of extremely heavy and n-rich nuclei appears feasible. A possible existence of hyper-heavy nuclei in a neutron star environment could provide a mechanism of extra coherent neutrino scattering or an additional mechanism, resulting in x-ray burst or a gravitational wave signal and, thus, becoming another crucial process adding new information to the suggested models on neutron star evolution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Blocking C-terminal processing of KRAS4b via a direct covalent attack on the CaaX-box cysteine

RAS is the most frequently mutated oncogene in cancer. RAS proteins show high sequence similarities in their G-domains but are significantly different in their C-terminal hypervariable regions (HVR). These regions interact with the cell membrane via lipid anchors that result from posttranslational modifications (PTM) of cysteine residues. KRAS4b is unique as it has only one cysteine that undergoes PTM, C185. Small molecule covalent modification of C185 would block any form of prenylation and subsequently inhibit attachment of KRAS4b to the cell membrane, blocking its biological activity. We translated this concept to the discovery and development of disulfide tethering screen hits into irreversible covalent modifiers of C185. These compounds inhibited proliferation of KRAS4b-driven mouse embryonic fibroblasts, but not cells driven by N-myristoylated KRAS4b that harbor a C185S mutation and are not dependent on C185 prenylation. Top–down proteomics was used to confirm target engagement in cells. These compounds bind in a pocket formed when the HVR folds back between helix 3 and 4 in the G-domain (HVR-α3-α4). This interaction can happen in the absence of small molecules as predicted by molecular dynamics simulations and is stabilized in the presence of C185 binders as confirmed by small-angle X-ray scattering and solution NMR. NOESY-HSQC, an NMR approach that measures internuclear distances of 6 Å or less, and structure analysis identified the critical residues and interactions that define the HVR-α3-α4 pocket. Further development of compounds that bind to this pocket could be the basis of a new approach to targeting KRAS cancers.

C185↗
DOE OSTI2026

Screen-Printed SHJ Solar Cells with Complex Silver Inks

Metallization using complex metal inks has gained significant research interest due to its cost-effectiveness and ability to achieve performance comparable to traditional nanoparticle pastes. This study introduces the use of complex silver (Ag) inks applied via industrial screen-printing for silicon heterojunction (SHJ) solar cell metallization. The printed Ag lines exhibit a contact resistivity on SHJ tin-doped indium oxide (ITO) surfaces as low as approximately 0.2-12 mO cm2. Photoluminescence imaging reveals minimal surface passivation degradation (iVoc < 3.5 mV), while scanning electron microscopy (SEM) shows a denser structure compared to Ag layer from nanoparticle pastes. The printed Ag grid features thin (approximately 1 micrometer), continuous fingers approximately 100-120 micrometer wide, significantly thinner than conventional approximately 20-30 micrometer fingers produced with nanoparticle-based pastes. Double printing achieves SHJ device efficiencies exceeding 20%, the highest reported for industrial solar cell precursors using this technology. These findings highlight the potential of complex Ag inks as a sustainable alternative to particle-based pastes, reducing Ag consumption and processing temperatures without compromising efficiency.

14 SOLAR ENERGY↗