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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Functional plasticity of HCO 3 – uptake and CO 2 fixation in Cupriavidus necator H16

Despite its prominence, the ability to engineer Cupriavidus necator H16 for inorganic carbon uptake and fixation is underexplored. We tested the roles of endogenous and heterologous genes on C. necator inorganic carbon metabolism. Deletion of β-carbonic anhydrase can had the most deleterious effect on C. necator autotrophic growth. Replacement of this native uptake system with several classes of dissolved inorganic carbon (DIC) transporters from Cyanobacteria and chemolithoautotrophic bacteria recovered autotrophic growth and supported higher cell densities compared to wild-type (WT) C. necator in batch culture. Strains expressing Halothiobacillus neopolitanus DAB2 (hnDAB2) and diverse rubisco homologs grew in CO 2 similarly to the wild-type strain. Our experiments suggest that the primary role of carbonic anhydrase during autotrophic growth is to support anaplerotic metabolism, and an array of DIC transporters can complement this function. This work demonstrates flexibility in HCO 3 - uptake and CO 2 fixation in C. necator, providing new pathways for CO 2 -based biomanufacturing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Using electron channeling contrast imaging to inform and improve the growth of high-efficiency GaAs solar cells on nanopatterned GaAs substrates

Patterned substrates provide opportunities for reducing the cost of high-efficiency III-V devices by incorporating mechanically weak layers beneficial for substrate reuse (e.g. by spalling). In this work, the functionality of electron channeling contrast imaging (ECCI) as a tool to efficiently understand and mitigate defect formation is exemplified by developing a process in which high-quality III-V material can be grown on nanopatterned GaAs substrates. Reactive ion etching used in the patterning process was found to damage the GaAs substrate surface, leading to the formation of stacking faults in the epitaxial material as observed by ECCI. Etching the patterned substrates in a 1 NH4OH: 1 H2O2: 50 DI H2O solution for 10 s prior to growth removed the substrate surface damage and stacking faults were no longer present. Growth of solar cell device structures initially produced samples with many macroscale flaws creating shunts in the devices, which complicated the assessment of material quality by device measurements. However, ECCI revealed that the epitaxial material surrounding macroscale flaws was free from any crystallographic defects such as stacking faults and threading dislocations. With this knowledge, we focused on refining the patterning process to eliminate the macroscale flaws. Solar cells were then grown on the improved nanopatterned substrates and exhibited device structures with defect densities less than 5 x 105 cm -2 and average conversion efficiency of 24.8%, nearly identical to devices grown on unpatterned epi-ready substrates (25.0%).

14 SOLAR ENERGY↗
DOE OSTI2025

Time-interval distributions in a digital gamma multi-channel analyzer at extreme input rates

Here, this study explores the relationship between experimentally observed inter-event time-interval distributions (TIDs) and measured dead times for pulses generated by a HPGe gamma detector and processed by a digital spectrometer. The system utilizes a fast and slow channel, pile-up rejector, trapezoid filtering, and flash analog-to-digital converter. The experimentally derived TIDs were compared with theory for validation. The results demonstrate that the theoretical model reliably describes measured TIDs up to 40% dead time. However, significant distortion effects become increasingly pronounced at higher input rates. It appears that the deviation between the measured and calculated time-interval distributions take the shape of higher-order convolutions of the TID, which represent the time difference between counts for more than two successive events. In this work, theoretical functions for the TID are expanded to reproduce measurements up to 90%. This refinement in the interpretation and treatment of the measured TIDs provides improved accuracy and precision in the prediction of the true event rate and measured dead time in the counter. Even though it reflects occasional count loss that is specific to the set-up, it is expected that a similar adjustment may be applicable to other detection systems as well.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Standardized nomenclature for photovoltaic connectors

Photovoltaic (PV) systems rely on discrete connectors for the efficient and safe flow of power from module to module and from strings to combiner boxes and inverters. Despite their functional importance, no common nomenclature for PV connectors currently exists, resulting in confusion and miscommunication. Misunderstood terms like "MC4 compatible", "cross-mating", "intermating", "female", and "male" can lead to installation and maintenance errors and compromise system reliability. We believe a standardized terminology will reduce confusion, help support installation best practices, aid in maintenance and repair, inform next-generation designs, and provide a technical basis for improved codes and standards. To that end, we are proposing a standardized glossary for 4 mm PV connectors (the most common type of connector used in PV applications) based on, and validated by, a Sandia National Laboratories' investigation that included the following sources: 1) a comprehensive review of official documents from 20 connector manufacturers, including schematics, datasheets, installation manuals, and catalogs, as well as relevant patents; 2) two rounds of surveys distributed to stakeholders, including connector manufacturers, engineers, asset owners, test labs, and researchers; and 3) visual examination of 25 different models of 4 mm single-pole DC PV connectors to document variations in design and functionality. This work provides a foundation for establishing a clear and consistent terminology for PV connectors that will in turn enable progress toward greater reliability and collaboration across the industry.

14 SOLAR ENERGY↗
DOE OSTI2020

Graphite Lithiation under Fast Charging Conditions: Atomistic Modeling Insights

The charging of lithium ion batteries in a fast and safe manner is critical for promoting the mass adoption of electric vehicles. Li intercalation in graphite electrodes is known to be one of the bottlenecks during the fast charging process. The mechanism of Li diffusion in highly polarized graphite anode at high current rates remains, however, not well understood. In this work, Density Functional Theory (DFT) calculations are used to gain insights into the Li diffusion process in graphite when it is far from equilibrium under fast charging conditions. The effect of uncompensated charges on Li mobility is determined in the highly polarized regions of the anode close to the interfaces. The extra charge was found to increase the interlayer spacing in the diffusion layer and adjacent channels, increasing the diffusivity and promoting the formation of Li clusters. A concerted diffusion mechanism at the edge of high-concentration Li domains is proposed to enhance the diffusion of Li.

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

Latent Representation Learning for Structural Characterization of Catalysts

Supervised machine learning-enabled mapping of the X-ray absorption near edge structure (XANES) spectra to local structural descriptors offers new methods for understanding the structure and function of working nanocatalysts. We briefly summarize a status of XANES analysis approaches by supervised machine learning methods. We present an example of an autoencoder-based, unsupervised machine learning approach for latent representation learning of XANES spectra. This new approach produces a lower-dimensional latent representation, which retains a spectrum–structure relationship that can be eventually mapped to physicochemical properties. Furthermore, the latent space of the autoencoder also provides a pathway to interpret the information content “hidden” in the X-ray absorption coefficient. Our approach (that we named latent space analysis of spectra, or LSAS) is demonstrated for the supported Pd nanoparticle catalyst studied during the formation of Pd hydride. By employing the low-dimensional representation of Pd K-edge XANES, the LSAS method was able to isolate the key factors responsible for the observed spectral changes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Powerful Organic Molecular Oxidants and Reductants Enable Ambipolar Injection in a Large-Gap Organic Homojunction Diode

Doping has proven to be a critical tool for enhancing the performance of organic semiconductors in devices like organic light-emitting diodes. However, the challenge in working with high-ionization-energy (IE) organic semiconductors is to find p-dopants with correspondingly high electron affinity (EA) that will improve the conductivity and charge carrier transport in a film. Here, we use an oxidant that has been recently recognized to be a very strong p-type dopant, hexacyano-1,2,3-trimethylene-cyclopropane (CN6-CP). The EA of CN6-CP has been previously estimated via cyclic voltammetry to be 5.87 eV, almost 300 meV higher than other known high-EA organic molecular oxidants. We measure the frontier orbitals of CN6-CP using ultraviolet and inverse photoemission spectroscopy techniques and confirm a high EA value of 5.88 eV in the condensed phase. The introduction of CN6-CP in a film of large-band-gap, large-IE phenyldi(pyren-1-yl)phosphine oxide (POPy 2 ) leads to a significant shift of the Fermi level toward the highest occupied molecular orbital and a 2 orders of magnitude increase in conductivity. Using CN6-CP and n-dopant (pentamethylcyclopentadienyl)(1,3,5-trimethylbenzene)ruthenium (RuCp*Mes)2, we fabricate a POPy 2 -based rectifying p–i–n homojunction diode with a 2.9 V built-in potential. Blue light emission is achieved under forward bias. Furthermore, this effect demonstrates the dopant-enabled hole injection from the CN6-CP-doped layer and electron injection from the (RuCp*Mes) 2 -doped layer in the diode.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Boosting Thermoelectric Performance in Nanocrystalline Ternary Skutterudite Thin Films through Metallic CoTe 2 Integration

Metal–semiconductor nanocomposites have emerged as a viable strategy for concurrently tailoring both thermal and electronic transport properties of established thermoelectric materials, ultimately achieving synergistic performance. In this investigation, a series of nanocomposite thin films were synthesized, embedding metallic cobalt telluride (CoTe 2 ) nanophase within the nanocrystalline ternary skutterudite (Co(Ge 1.22 Sb 0.22 )Te 1.58 or CGST) matrix. Our approach harnessed composition fluctuation-induced phase separation and in situ growth during thermal annealing to seamlessly integrate the metallic phase. The distinctive band structures of both materials have developed an ohmic-type contact characteristic at the interface, which raised carrier density considerably yet negligibly affected the mobility counterpart, leading to a substantial improvement in electrical conductivity. The intricate balance in transport properties is further influenced by the metallic CoTe 2 phase’s role in diminishing lattice thermal conductivity. The presence of the metallic phase instigates enhanced phonon scattering at the interface boundaries. Consequently, a 2-fold enhancement in the thermoelectric figure of merit (zT ~ 1.30) is attained with CGST-7 wt. % CoTe 2 nanocomposite film at 655 K compared to that of pristine CGST.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Spatially Resolved Potential and Li-Ion Distributions Reveal Performance-Limiting Regions in Solid-State Batteries

The performance of solid-state electrochemical systems is intimately tied to the potential and lithium distributions across electrolyte–electrode junctions that give rise to interface impedance. Here, we combine two operando methods, Kelvin probe force microscopy (KPFM) and neutron depth profiling (NDP), to identify the rate-limiting interface in operating Si-LiPON-LiCoO 2 solid-state batteries by mapping the contact potential difference (CPD) and the corresponding Li distributions. The contributions from ions, electrons, and interfaces are deconvolved by correlating the CPD profiles with Li-concentration profiles and by comparisons with first-principles-informed modeling. Furthermore, we find that the largest potential drop and variation in the Li concentration occur at the anode–electrolyte interface, with a smaller drop at the cathode–electrolyte interface and a shallow gradient within the bulk electrolyte. Correlating these results with electrochemical impedance spectroscopy following battery cycling at low and high rates confirms a long-standing conjecture linking large potential drops with a rate-limiting interfacial process.

25 ENERGY STORAGE↗
DOE OSTI2020

Strain-engineered high-responsivity MoTe 2 photodetector for silicon photonic integrated circuits

In integrated photonics, specific wavelengths are preferred such as 1550 nm due to low-loss transmission and the availability of optical gain in this spectral region. For chip-based photodetectors, layered two-dimensional (2D) materials bear scientific and technologically relevant properties such as electrostatic tunability and strong light-matter interactions. However, no efficient photodetector in the telecommunication C-band has been realized with 2D transition metal dichalcogenide materials due to their large optical bandgap. Furthermore, we demonstrate a MoTe 2 -based photodetector featuring strong photoresponse (responsivity = 0.5 A/W -1 ) operating at 1550 nm in silicon photonics enabled by strain engineering the 2D material. Non-planarized waveguide structures show a locally-induced bandgap change of 0.2 eV inside MoTe 2 , resulting in large photo-response, in an otherwise photo-inactive medium when unstrained. Unlike Graphene-based photodetectors relying on a gapless band structure, this photodetector shows a ~100X improved dark current, enabling an efficient noise equivalent power of 90 pW/Hz -0.5 . Such strain-engineered integrated photodetector provides new opportunities for integrated optoelectronic systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Insights into lithium ion deposition on lithium metal surfaces

Lithium metal is among the most promising anodes for the next generation of batteries due to its high theoretical energy density and high capacity. Challenges such as extreme reactivity and lithium dendrite formation have kept lithium metal anodes away from practical applications. However, the underlying mechanisms of Li ion deposition from the electrolyte solution onto the anode surface are still poorly understood due to their inherent complexity. In this work, density functional theory calculations and thermodynamic integration via constrained molecular dynamics simulations are conducted to study the electron and ion transfer between lithium metal slab and the electrolyte in absence of an external field. Here, we explore the effect of the solvent chemistry and structure, distance of the solvated complex from the surface, anion–cation separation, and concentration of Li-salts on the deposition of lithium ions from the electrolyte phase onto the surface. Ethylene carbonate (EC), 1,2-dimethoxyethane (DME), 1,3-dioxolane (DOL), and mixtures of them are used as solvents. These species compete with the salt anion and the Li cation for electron transfer from the surface. It is found that the structure and properties of the solvation shell around the lithium cation has a great influence on the ability of the cation to diffuse as well as on its surrounding electron environment. DME molecules allow easier motion of the lithium ion compared with EC and DOL molecules. The slow growth approach allows the study of energy barriers for the ion diffusion and desolvation during the deposition pathway. This method helps elucidating the underlying mechanisms on lithium-ion deposition and provides a better understanding of the early stages of Li nucleation.

25 ENERGY STORAGE↗
DOE OSTI2020

Strain-driven surface reconstruction and cation segregation in layered Li(Ni 1– x – y Mn x Co y )O 2 (NMC) cathode materials

The composition, structure and phase transformations occurring on cathode surfaces greatly affect the performance of Li-ion batteries. Li-Ion diffusion and surface–electrolyte interaction are two major phenomena that impact the capacity and cell impedance. The effects of surface reconstruction (SR) of cathode materials on the performance of Li-ion batteries are of current interest. However, the origin and evolution of the SR are still not well understood. In this work, density functional theory (DFT) calculations are used to investigate the processes taking place during surface segregation and reconstruction. Facet dependent segregation was found in Li(Ni 1– x – y Mn x Co y )O 2 (NMC) cathodes. Specifically, Co tends to segregate to the (104) surface of the primary particles within the transition metal layer, while Ni ions tend to segregate to the (012) surface in the Li layer, forming a SR. Experimental evidence shows the SR to be epitaxial with the bulk of the as-synthesized material, and the new SR phase is pinned to the NMC unit cell leading to a strained SR. Here, we demonstrate that strain can stabilize a spinel structure of the SR layers. Understanding the effects of surface strain opens a new avenue for the design of cathode materials with enhanced surface properties.

25 ENERGY STORAGE↗
DOE OSTI2021

Expanding the momentum field of view in angle-resolved photoemission systems with hemispherical analyzers

In photoelectron spectroscopy, the measured electron momentum range is intrinsically related to the excitation photon energy. Low photon energies <10 eV are commonly encountered in laser-based photoemission and lead to a momentum range that is smaller than the Brillouin zones of most materials. This can become a limiting factor when studying condensed matter with laser-based photoemission. An additional restriction is introduced by widely used hemispherical analyzers that record only electrons photoemitted in a solid angle set by the aperture size at the analyzer entrance. Here, we present an upgrade to increase the effective solid angle that is measured with a hemispherical analyzer. We achieve this by accelerating the photoelectrons toward the analyzer with an electric field that is generated by a bias voltage on the sample. Our experimental geometry is comparable to a parallel plate capacitor, and therefore, we approximate the electric field to be uniform along the photoelectron trajectory. With this assumption, we developed an analytic, parameter-free model that relates the measured angles to the electron momenta in the solid and verify its validity by comparing with experimental results on the charge density wave material TbTe3. By providing a larger field of view in momentum space, our approach using a bias potential considerably expands the flexibility of laser-based photoemission setups.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An optimally tuned range-separated hybrid starting point for ab initio GW plus Bethe–Salpeter equation calculations of molecules

The ab initio GW plus Bethe–Salpeter equation (GW-BSE, where G is the one particle Green's function and W is the screened Coulomb interaction) approach has emerged as a leading method for predicting excitations in both solids and molecules with a predictive power contingent upon several factors. Among these factors are the (1) generalized Kohn–Sham eigensystem used to construct the GW self-energy and to solve the BSE and (2) the efficacy and suitability of the Tamm–Dancoff approximation. Here, we present a detailed benchmark study of low-lying singlet excitations from a generalized Kohn–Sham (gKS) starting point based on an optimally tuned range-separated hybrid (OTRSH) functional. We show that the use of this gKS starting point with one-shot G0W0 and G0W0-BSE leads to the lowest mean absolute errors (MAEs) and mean signed errors (MSEs), with respect to high-accuracy reference values, demonstrated in the literature thus far for the ionization potentials of the GW100 benchmark set and for low-lying neutral excitations of Thiel’s set molecules in the gas phase, without the need for self-consistency. The MSEs and MAEs of one-shot G0W0-BSE@OTRSH excitation energies are comparable to or lower than those obtained with other functional starting points after self-consistency. Additionally, we compare these results with linear-response time-dependent density functional theory (TDDFT) calculations and find GW-BSE to be superior to TDDFT when calculations are based on the same exchange-correlation functional. This work demonstrates tuned range-separated hybrids used in combination with GW and GW-BSE can greatly suppress starting point dependence for molecules, leading to accuracy similar to that for higher-order wavefunction-based theories for molecules without the need for costlier iterations to self-consistency.

McKeon, Caroline A. (ORCID:0000000217373503)↗
DOE OSTI2021

Multimeric antibodies from antigen-specific human IgM+ memory B cells restrict Plasmodium parasites

Multimeric immunoglobulin-like molecules arose early in vertebrate evolution, yet the unique contributions of multimeric IgM antibodies to infection control are not well understood. This is partially due to the difficulty of distinguishing low-affinity IgM, secreted rapidly by plasmablasts, from high-affinity antibodies derived from later-arising memory cells. We developed a pipeline to express B cell receptors (BCRs) from Plasmodium falciparum–specific IgM+ and IgG+ human memory B cells (MBCs) as both IgM and IgG molecules. BCRs from both subsets were somatically hypermutated and exhibited comparable monomeric affinity. Crystallization of one IgM+ MBC-derived antibody complexed with antigen defined a linear epitope within a conserved Plasmodium protein. In its physiological multimeric state, this antibody displayed exponentially higher antigen binding than a clonally identical IgG monomer, and more effectively inhibited P. falciparum invasion. Forced multimerization of this IgG significantly improved both antigen binding and parasite restriction, underscoring how avidity can alter antibody function. This work demonstrates the potential of high-avidity IgM in both therapeutics and vaccines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Numerical calculation of the particle–fluid–particle stress in random arrays of fixed particles

Based on the nearest particle statistics [Zhang, J. Fluid Mech. 910, A16 (2021)], the phase interaction force in a multiphase flow is decomposed into a particle–mean-field force and the divergence of the particle–fluid–particle (PFP) stress. The PFP stress is proportional to the correlation product of the distance from a particle to its nearest neighbor and the force on the particle conditionally averaged on the nearest-neighbor location. In this work, a functional form of the stress is obtained corrected to the first order of the ratio between the interparticle distance and the macroscopic length scale of the flow. Particle-resolved numerical simulations are used to calculate the PFP stress in random arrays of fixed particles and to explore the physics represented by the stress. The numerical results show that the PFP stress is attractive along the direction of the flow and is repulsive in the directions perpendicular to the flow. In the flow regime simulated, this PFP stress can be considered as a macroscopic representation of the drafting–kissing–tumbling mechanism. Finally, the Reynolds stress for the fluid phase is also calculated and compared with the PFP stress.

42 ENGINEERING↗
DOE OSTI2021

Long-range hydrogen-binding effects of carbide interfaces in iron

A micromechanics model was developed to evaluate the elastic binding energy between carbide precipitates and hydrogen interstitials using Eshelby's equivalent inclusion method. In this work, density functional theory (DFT) simulations were performed to obtain the material-specific quantities, e.g., lattice constants and the elastic constants, for the continuum model. Using this model, we find that for coherent carbide precipitates, hydrogen atoms are more likely to bind on the broad surfaces of the disk-like precipitates, which is consistent with experimental observations. For semicoherent and incoherent precipitates, our model suggests that it is possible for semicoherent precipitates to have significant hydrogen binding capability while there is no hydrogen-binding capability of incoherent precipitates, which also agrees with experimental findings. In addition, several factors that influence the binding energies between hydrogen atoms and carbide precipitates were quantitatively analyzed, including the precipitate size, morphology, orientation, and interface. These collective results include both the position and the value of the strongest hydrogen-binding interaction for a wide range of carbide stoichiometries, which contributes to our understanding of hydrogen trapping in steel-based materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The Use of Machine Learning Models for Predicting the Dielectric Strength of Gases

Technological advancements in high voltage systems have pushed sulfur hexafluoride (SF6) to its operational limits. Furthermore, this gas has other drawbacks including a high liquefaction temperature and a high global warming potential. Therefore, there has been an urgent need to find alternative gases with high dielectric strength (DS). In this work, density functional theory (DFT) is used to calculate molecular descriptors that are fed into an artificial neural network (ANN) and a random forest (RF). These machine learning (ML) models are then used to predict the DS for hundreds of molecules. A finite element model (FEM) is also used to calculate the electric field profile of multiple simple electrode geometries as the applied voltage to the system is increased. Results indicate that the random forest model has better generalization to unseen data than the neural network. The highest DS value predicted by the RF was 2.16 relative to the experimental DS of SF6. The results also demonstrate how choosing a gas with a higher DS and a geometry with minimal edges and corners can significantly increase the operating voltage of an electrical system. Due to its superior generalization, the RF represents the most promising path toward an accurate DS predictor once sufficient experimental data are available.

Mileski, Matthew [AFIT]↗