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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A scalable variational inequality approach for flow through porous media models with pressure-dependent viscosity

Mathematical models for flow through porous media typically enjoy the so-called maximum principles, which place bounds on the pressure field. It is highly desirable to preserve these bounds on the pressure field in predictive numerical simulations, that is, one needs to satisfy discrete maximum principles (DMP). Unfortunately, many of the existing formulations for flow through porous media models do not satisfy DMP. This paper presents a robust, scalable numerical formulation based on variational inequalities (VI), to model non-linear flows through heterogeneous, anisotropic porous media without violating DMP. VI is an optimization technique that places bounds on the numerical solutions of partial differential equations. To crystallize the ideas, a modification to Darcy equations by taking into account pressure-dependent viscosity will be discretized using the lowest-order Raviart–Thomas (RT0) and Variational Multi-scale (VMS) finite element formulations. It will be shown that these formulations violate DMP, and, in fact, these violations increase with an increase in anisotropy. It will be shown that the proposed VI-based formulation provides a viable route to enforce DMP. Moreover, it will be shown that the proposed formulation is scalable, and can work with any numerical discretization and weak form. Aseriesof numerical benchmark problems are solved to demonstrate the effects of heterogeneity, anisotropy and non-linearity on DMP violations under the two chosen formulations (RT0 and VMS), and that of non-linearity on solver convergence for the proposed VI-based formulation. Parallel scalability on modern computational platforms will be illustrated through strong-scaling studies, which will prove the efficiency of the proposed formulation in a parallel setting. Algorithmic scalability as the problem size is scaled up will be demonstrated through novel static-scaling studies. The performed static-scaling studies can serve as a guide for users to be able to select an appropriate discretization for a given problem size.

42 ENGINEERING↗
DOE OSTI2021

Static and dynamic magnetic properties of honeycomb lattice antiferromagnets Na 2 M 2 TeO 6 , M = Co and Ni

The magnetic structures and spin dynamics of Na 2 CO 2 TeO 6 and Na 2 Ni 2 TeO 6 are investigated by means of elastic and inelastic neutron scattering measurements and the results are discussed in the context of a generalized Kitaev-Heisenberg model on a honeycomb lattice with strong spin-orbit coupling. The large number of parameters involved in the Hamiltonian model is evaluated by using an iterative optimization algorithm capable of extracting model solutions and simultaneously estimating their uncertainty. The analyses indicate that both Co 2+ (d 7 ) and Ni 2+ (d 8 ) antiferromagnets realize bond-dependent anisotropic nearest-neighbor interactions and support the theoretical predictions for the realization of Kitaev physics in 3 d electron systems with effective spins S = 1/2 and 1. By studying the Na-doped system Na 2.4 Ni 2 TeO 6 , we show that the control of Na content can provide an effective route for fine-tuning the magnetic lattice dimensionality, as well as to controlling the bond-dependent anisotropic interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Effect of polymer structure and material properties on mechanochemical reaction environments for polymer recycling

Plastic waste accumulation necessitates innovative recycling approaches to achieve sustainability goals. Mechanochemical depolymerization offers a solvent-free, energy-efficient route to convert polymers into valuable monomers. In addition to their chemical properties, the way that polymers absorb kinetic energy is a key parameter of any mechanochemical process. This perspective explores the principles underpinning mechanochemical recycling, emphasizing how deformation and localized transient heating mediate energy transfer between impacts and localized excitations. Key factors such as polymer crystallinity, molecular weight, viscoelasticity, and thermal effects are analyzed to elucidate their role in energy transfer mechanisms during ball milling. This work establishes a foundational framework for the design and optimization of mechanochemical recycling by connecting polymer response to mechanical energy with the intention to improve depolymerization efficiency. Future research opportunities are outlined to advance the integration of polymer science and mechanochemistry for scalable, sustainable plastic upcycling.

ball mill↗
DOE OSTI2026

Scalable, low-cost ink-based processing of high-performance silver selenide thermoelectrics

The growing global energy demand and its accelerating contribution to climate change emphasize the urgent need for sustainable energy conversion/harvesting technologies. Thermoelectric (TE) devices offer a compelling route to directly convert waste heat into electricity and enable solid-state cooling without moving parts or harmful refrigerants. Achieving their full potential requires not only higher TE performance (zT) but also scalable, low-cost manufacturing processes. Here, we introduce a transformative ink-based processing approach for scalable manufacturing of high-performance silver selenide-based TE materials and devices. Using a simple, high-throughput ink-mixing and blade coating strategy, our Ag 2 Se-based materials under the optimized composition and processing conditions yield an ultrahigh room-temperature power factor of 2.8 mW m −1 K −2 , over 100% higher than baseline samples and a reproducible figure of merit zT of 1 at room temperature. A thermoelectric generator (TEG) achieves a very competitive power density of 112 mW cm −2 at a 90 °C temperature difference between the hot and cold sides of the device, which is among the highest reported for silver selenide-based TE devices to date. This facile, scalable ink-based processing establishes a practical pathway toward industrial-scale manufacturing and widespread adoption of thermoelectric devices, advancing sustainable energy technologies.

Bappy, Md. Omarsany [University of Notre Dame, IN ↗
DOE OSTI2017

Pyrite Iron Sulfide Solar Cells Made from Solution Final Technical Report

This document summarizes research done under the SunShot Next Generation PV II project entitled, “Pyrite Iron Sulfide Solar Cells Made from Solution,” award number DE-EE0005324, at the University of California, Irvine, from 9/1/11 thru 11/30/16. The project goal was to develop iron pyrite (cubic FeS 2 ) as an absorber layer for solution-processible p-n heterojunction solar cells with a pathway to >20% power conversion efficiency. Project milestones centered around seven main Tasks: (1) make device-quality pyrite thin-films from solar ink; (2) develop an ohmic bottom contact with suitable low resistivity; (3) produce a p-n heterojunction with VOC > 400 mV; (4) make a solar cell with >5% power conversion efficiency; (5) use alloying to increase the pyrite band gap to ~1.2-1.4 eV; (6) produce a p-n heterojunction with VOC > 500 mV; and finally (7) make a solar cell with >10% power conversion efficiency. In response to project findings, the Tasks were amended midway through the project to focus particular effort on passivating the surface of pyrite in order to eliminate excessively-strong surface band bending believed to be responsible for the low VOC of pyrite diodes. Major project achievements include: (1) development and detailed characterization of several new solution syntheses of high-quality thin-film pyrite, including two “molecular ink” routes; (2) demonstration of Mo/MoS 2 bilayers as good ohmic bottom contacts to pyrite films; (3) fabrication of pyrite diodes with a glass/Mo/MoS 2 /pyrite/ZnS/ZnO/AZO layer sequence that show VOC values >400 mV and as high as 610 mV at ~1 sun illumination, although these high VOC values ultimately proved irreproducible; (4) established that ZnS is a promising n-type junction partner for pyrite; (5) used density functional theory to show that the band gap of pyrite can be increased from ~1.0 to a more optimal 1.2-1.3 eV by alloying with oxygen; (6) through extensive measurements of ultrahigh-purity pyrite single crystals, proved the existence of a conductive, hole-rich inversion layer at the surface of n-type pyrite crystals and established that the inversion layer is the likely reason for pyrite’s low VOC; (7) developed several surface passivation treatments to reduce the surface hole density, but not enough to expect a significant increase in VOC; (8) by controlling the single crystal growth conditions, reduced the concentration of near-surface deep donors by a factor of ~1000, which should be sufficient to avoid thermionic field emission (i.e., tunneling) across the pyrite surface and thereby increase pyrite VOC. Recent project results will be described in forthcoming peer-reviewed publications.

14 SOLAR ENERGY↗
DOE OSTI2019

String Method for Protein–Protein Binding Free-Energy Calculations

A powerful computational strategy to determine the equilibrium association constant of two macromolecules with explicit-solvent molecular dynamics (MD) simulations is the "geometric route", which considers the reversible physical separation of the bound complex in solution. Nonetheless, multiple challenges remain to render this type of methodology reliable and computationally efficient in practice. In particular, in one, formulation of the geometric route relies on the potential of mean force (PMF) for physically separating the two binding partners restrained along a straight axis, which must be selected prior to the calculation. However, practical applications indicate that the calculation of the separation PMF along the predefined rectilinear pathway may be suboptimal and slowly convergent. Recognizing that a rectilinear straight separation pathway is generally not representative of how the protein complex physically separates in solution, we put forth a novel theoretical framework for binding free-energy calculations, leaning on the optimal curvilinear minimum free-energy path (MFEP) determined from the string method. The proposed formalism is validated by comparing the results obtained using both rectilinear and curvilinear pathways for a prototypical host-guest complex formed by cucurbit[7]uril (CB[7]) binding benzene, and for the barnase-barstar protein complex. On the basis of multi-microsecond MD calculations, we find that the calculations following the traditional rectilinear pathway and the string-based curvilinear pathway agree quantitatively, but convergence is faster with the latter.

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

Comparing Top-Down Proteoform Identification: Deconvolution, PrSM Overlap, and PTM Detection

Generating top-down tandem mass spectra (MS/MS) for complex mixtures of proteoforms has become possible through improvements in fractionation, on-line separation, dissociation, and mass analysis. The algorithms to match tandem mass spectra to sequences have undergone a parallel evolution, with both spectral alignment and peak matching being paired with diverse methods for scoring proteoform-spectral matches (PrSMs). This study assesses state-of-the-art algorithms for top-down identification through three distinct challenges. The first is identifying a large yield of PrSMs while controlling false discovery rate (FDR) in identifying thousands of proteoforms from complex cell lysates via four software workflows: ProSight Proteome Discoverer, TopPIC, Informed Proteomics, and pTop. The second is the deconvolution of data from both Thermo Orbitrap-class and Bruker maXis Q-TOF instruments to produce consistent precursor charge and mass determinations while generating fragment mass lists to optimize identification. The third attempts to detect diverse post-translational modifications (PTMs) in proteoforms from cow milk and human ovarian tissue. The data demonstrate that existing software suites produce admirable sensitivity, in some cases identifying a third of collected tandem mass spectra with FDR controlled below 2%; the overlap in these PrSMs, however, illustrates real value in searching data with multiple search engines. Differences among identification workflows seem to result from each search algorithm incorporating its own deconvolution algorithm. By transmitting deconvolution data from multiple deconvolution routes (Thermo Xtract, Bruker Auto MSn, Mascot Distiller, TopFD, and FLASHDeconv) to the downstream TopPIC search algorithm, we were able to detect common causes of deconvolution disagreement. The detection of PTMs was very inconsistent among search algorithms, with some workflows suggesting as little as 1% of PrSMs from cow’s milk were singly-phosphorylated while other workflows found that 18% of PrSMs were singly-phosphorylated. Taken together, these results make a strong argument for top-down researchers to adopt a standard practice of analyzing each MS/MS experiment with at least two different search engines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Flexible silicon photonic architecture for accelerating distributed deep learning

The increasing size and complexity of deep learning (DL) models have led to the wide adoption of distributed training methods in datacenters (DCs) and high-performance computing (HPC) systems. However, communication among distributed computing units (CUs) has emerged as a major bottleneck in the training process. In this study, we propose Flex-SiPAC, a flexible silicon photonic accelerated compute cluster designed to accelerate multi-tenant distributed DL training workloads. Flex-SiPAC takes a co-design approach that combines a silicon photonic hardware platform with a tailored collective algorithm, optimized to leverage the unique physical properties of the architecture. The hardware platform integrates a novel wavelength-reconfigurable transceiver design and a micro-resonator-based wavelength-reconfigurable switch, enabling the system to achieve flexible bandwidth steering in the wavelength domain. The collective algorithm is designed to support reconfigurable topologies, enabling efficient all-reduce communications that are commonly used in DL training. The feasibility of the Flex-SiPAC architecture is demonstrated through two testbed experiments. First, an optical testbed experiment demonstrates the flexible routing of wavelengths by shuffling an array of input wavelengths using a custom-designed spatial-wavelength selective switch. Second, a four-GPU testbed running two DL workloads shows a 23% improvement in job completion time compared to a similarly sized leaf-spine topology. We further evaluate Flex-SiPAC using large-scale simulations, which show that Flex-SiPAC is able to reduce the communication time by 26% to 29% compared to state-of-the-art compute clusters under representative collective operations.

Wu, Zhenguo (ORCID:0000000322847985)↗
DOE OSTI2016

Synthesis, microstructure and dielectric properties of zirconium doped barium titanate

We report on synthesis, microstructural and relaxor ferroelectric properties of Zirconium(Zr) doped Barium Titanate (BT) samples with general formula Ba(Ti{sub 1-x}Zr{sub x})O{sub 3} (x=0.20, 0.35). These lead-free ceramics were prepared by solid state reaction route. The phase transition behavior and temperature dependent dielectric properties and composition dependent ferroelectric properties were investigated. XRD analysis at room temperature confirms phase purity of the samples. SEM observations revealed retarded grain growth with increasing Zr mole fraction. Dielectric properties of BZT ceramics is influenced significantly by small addition of Zr mole fraction. With increasing Zr mole fraction, dielectric constant decreases while FWHM and frequency dispersion increases. Polarization vs electric field hysteresis measurements reveal ferroelectric relaxor phase at room temperature. The advantages of such substitution maneuvering towards optimizing ferroelectric properties of BaTiO{sub 3} are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Enhancing Electrocatalytic Water Splitting by Strain Engineering

Electrochemical water splitting driven by sustainable energy such as solar, wind, and tide is attracting ever-increasing attention for sustainable production of clean hydrogen fuel from water. Leveraging these advances requires efficient and earth-abundant electrocatalysts to accelerate the kinetically sluggish hydrogen and oxygen evolution reactions (HER and OER). A large number of advanced water-splitting electrocatalysts have been developed through recent understanding of the electrochemical nature and engineering approaches. Specifically, strain engineering offers a novel route to promote the electrocatalytic HER/OER performances for efficient water splitting. Herein, the recent theoretical and experimental progress on applying strain to enhance heterogeneous electrocatalysts for both HER and OER are reviewed and future opportunities are discussed. A brief introduction of the fundamentals of water-splitting reactions, and the rationalization for utilizing mechanical strain to tune an electrocatalyst is given, followed by a discussion of the recent advances on strain-promoted HER and OER, with special emphasis given to combined theoretical and experimental approaches for determining the optimal straining effect for water electrolysis, along with experimental approaches for creating and characterizing strain in nanocatalysts, particularly emerging 2D nanomaterials. Finally, a vision for a future sustainable hydrogen fuel community based on strain-promoted water electrolysis is proposed.

42 ENGINEERING↗
DOE OSTI2022

Bimetallic NiCo boride nanoparticles confined in a MXene network enable efficient ambient ammonia electrosynthesis

Ambient electrocatalytic nitrogen fixation is an emerging technology for green ammonia synthesis, but the absence of optimized, stable and performant catalysts can render its practical application challenging. Herein, bimetallic NiCo boride nanoparticles confined in MXene are shown to accomplish high-performance nitrogen reduction electrolysis. Taking advantage of the synergistic effect in specific compositions with unique electronic d and p orbits and typical architecture of rich nanosized particles embedded in the interconnected conductive network, the synthesized MXene@NiCoB composite demonstrates extensive improvements in nitrogen molecule chemisorption, active area exposure and charge transport. As a result, optimal NH 3 yield rate of 38.7 μg h -1 mgcat. -1 and Faradaic efficiency of 6.92% are acquired in 0.1 M Na 2 SO 4 electrolyte. Moreover, the great catalytic performance can be almost entirely maintained in the cases of repeatedly-cycled and long-term electrolysis. Theoretical investigations reveal that the nitrogen reduction reaction on MXene@NiCoB catalyst proceeds according to the distal pathway, with a distinctly-reduced energy barrier relative to the Co 2 B counterpart. In conclusion, this work may inspire a new route towards the rational catalyst design for the nitrogen reduction reaction.

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

Hierarchical Reinforcement Learning of a Short-Range Bond-Order Potential for Silica: Analytic Embedding of Coordination with Classical Efficiency

Reinforcement learning (RL) has recently emerged as a data-efficient strategy to parametrize short-range interatomic potentials. Building on our past RL optimization of pairwise silica models, we extend the framework to a bond-order (Tersoff-type) potential that provides an analytic embedding of local coordination through a three-body term. A hierarchical RL workflow combining continuous-action Monte Carlo Tree Search and property-based rewards efficiently explores the 26-dimensional parameter space, sequentially optimizing lattice parameters, densities, angles, and cohesive energies of 21 silica polymorphs. The resulting models, Q-Tersoff and ML-Tersoff, reproduce the energetic ordering of low-energy phases and capture the angular correlations and amorphous structure factors of silica with improved fidelity over pairwise force fields, while remaining orders of magnitude faster than high-dimensional machine-learned potentials. Both models underperform for elastic constants and high-energy frameworks, delineating the limits of the current analytic form. The approach establishes a general and interpretable route to angle-aware, short-range potentials that bridge physics-based and machine-learned descriptions of silicate materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Green Additive Limits Runaway Crystallinity in PM6:Y6 Organic Solar Cells but Causes Field-Independent Geminate Recombination

Solvent additives are well-established for improving device performance of organic solar cells by enhancing nanodomain phase separation and crystallization. However, optimum additive concentrations are typically at trace amounts with slight fluctuations causing runaway crystallinity that short the device and limit scale-up potential. Furthermore, we show that a nonhalogenated solvent additive 1-phenylnaphthalene (PN) can be used to optimize high-performance PM6:Y6 devices, but without runaway crystallinity even at concentrations 10× above the optimum. Our holistic analysis of device losses shows that PN increases photoabsorption while decreasing bimolecular recombination. However, above the optimum, charge generation is reduced due to field-independent geminate recombination of charge transfer states that overcomes the other benefits. Rotated Y6 crystallite orientation is a likely culprit, where the device electric field is ineffective at separating the charges. Despite this, device performance remains higher than that of traditional additives, indicating a route to avoiding the high sensitivity of performance to processing conditions.

14 SOLAR ENERGY↗
DOE OSTI2013

In situ ethyl ester production from wet algal biomass under microwave-mediated supercritical ethanol conditions

An in situ transesterification approach was demonstrated for converting lipid-rich wet algae (Nannochloropsis salina) into fatty acid ethyl esters (FAEE) under microwave-mediated supercritical ethanol conditions, while preserving the nutrients and other valuable components in the algae. This single-step process can simultaneously and effectively extract the lipids from wet algae and transesterify them into crude biodiesel. Experimental runs were designed to optimize the process parameters and to evaluate their effects on algal biodiesel yield. The algal biomass characterization and algal biodiesel analysis were carried out by using various analytical instruments such as FTIR, SEM-EDS, TLC, GC-MS and transmission electron microscopy (TEM). The thermogravimetric analysis (TGA) under nitrogen and oxygen environments was also performed to examine the thermal and oxidative stability of ethyl esters produced from wet algae. This simple in situ transesterification process using a green solvent and catalyst-free approach can be a potentially efficient route for algal biodiesel production.

09 BIOMASS FUELS↗
DOE OSTI2019

Nitrogen-coordinated single iron atom catalysts derived from metal organic frameworks for oxygen reduction reaction

Iron and nitrogen co-doped carbon (Fe-N-C) catalysts hold great promise to replace platinum group metal used for the oxygen reduction reaction (ORR) in low-temperature fuel cells. However, general synthesis routes require tedious acid washing and extensive heat treatment, usually resulting in uncontrollable morphologies and undesirable compounds. In this work, a zeolitic imidazolate framework (ZIF-8) was employed as a self-template for one-pot synthesis of a Fe-N-C catalyst consisting of uniformly dispersed Fe single atoms. Atomically dispersed Fe atoms were well distributed along the edges of the porous carbon matrix. Each of the Fe atoms was coordinated with four N atoms in the plane and two O atoms in the axial direction. The optimized Fe-N-C catalyst showed excellent ORR activities with half-wave potentials of 0.81 and 0.90 V in acidic and alkaline solutions, respectively. The results may be important for the optimization of single-atom-based catalysts for various reactions.

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

Cell-Free-Based Thermophilic Biocatalyst for the Synthesis of Amino Acids from One-Carbon Feedstocks

Bioproduction from one-carbon compounds, such as formate, is an attractive prospect due to reduced energy requirements and the possibility for using CO 2 as a sustainable feedstock. Formate-fixing pathways engineered using Escherichia coli lysate-based cell-free expression (CFE) biocatalysts have the potential to route 100% of feedstock carbon toward chemical synthesis but are undermined by siphoning of in-pathway metabolites and cofactors by the CFE background metabolism. To address this limitation, we engineer a CFE-based thermophilic multienzyme biocatalyst for the synthesis of serine and glycine from formate, bicarbonate, and ammonia. After expression of the thermophilic formate-to-serine pathway in a one-pot reaction, the mesophilic E. coli CFE background machinery is removed by simple heat denaturation, eliminating the siphoning of cofactors, inpathway metabolites, and products. After bioprocess optimization, including pathway gene expression duration and chemical synthesis temperature, we achieve near stoichiometric conversion of formate and bicarbonate to serine and glycine, reaching 97% of stoichiometric yield. The use of a moderately thermophilic biocatalyst allowed chemical synthesis to take place at mesophilic temperatures, enabling the balance of optimal enzyme activity with minimal metabolite/cofactor thermal degradation. In a fed-batch experiment, the biocatalyst shows sustained chemical synthesis rates for 8 h, paving the way toward a continuous bioprocess. Finally, a sensitivity analysis of cofactor usage revealed that the most expensive cofactors, THF and NADPH, can be reduced by 5-fold without significantly lowering product yields. To the best of our knowledge, this is the first instance of expressing a thermophilic pathway in an E. coli lysate-based CFE system to generate a thermophilic biocatalyst for use at mesophilic temperatures. The CFEbased thermophilic formate-to-serine biocatalyst triples the combined serine and glycine yield previously obtained by a CFE-based mesophilic formate-to-serine biocatalyst (30%), and quadruple the yield obtained by a purified enzyme system (22%). Ultimately, this work opens the door to using E. coli lysate-based CFE for thermophilic biocatalyst generation to achieve high chemical synthesis yields.

bacteria↗
DOE OSTI2019

Development of a Sustainable Green Chemistry Platform for Production of Acetone and Downstream Drop-in Fuel and Commodity Products Directly From Biomass Syngas Via a Novel Energy Conserving Route in Engineered Acetogenic Bacteria

LanzaTech and Oak Ridge National Laboratory have developed and scaled up a process for sustainable production of acetone and downstream drop-in fuel and commodity products directly from biomass syngas via a novel energy conserving route in engineered acetogenic bacteria. This process offers a safer and more environmentally-friendly production method for acetone production than the current phenol-dependent method, and the product has significantly lower GHG emissions. The developed process offers a cost competitive route to Acetone and enables biofuels at or below DOE’s $3 gge target. In addition, it also provides an attractive biological alternative to traditional sugar-based ABE fermentation, by enabling utilization of non-food biomass resources as fermentation feedstocks. Challenges overcome: • By-products formation: Byproduct 2,3-butandiol and 3-hydroxybutyrate reduce yield and stability. Addressed by elimination of both pathways in our chassis acetone production strain. • Cost competitiveness: Addressed by developing an integrated acetone strain and eliminating by-products to increase yield and stability. Optimized co-selectivity and coproductivity of acetone and ethanol instead of titer, based on technoeconomic analysis. • Limited enzyme variety: Addressed by genome mining of over 300 industrial strains in LanzaTech collection, identifying unique enzyme sequences, and refactoring these unique enzyme variants through LanzaTech’s engineering platform. Resulted in over 10x improvement in acetone production from gas. • Continuous process (stability): Identified bottleneck through detailed omics studies, addressed by integration of the acetone pathway on the chromosome. • Novel process to scale up: Addressed by demonstrating stable acetone production in a 80- L pilot reactor, with acetone productivity and selectivity comparable to those observed under the same conditions in 2-L reactors. We have demonstrated stable acetone production for over 7 days at commercial target rate and selectivity in 2-L reactors and have piloted the process.

09 BIOMASS FUELS↗
DOE OSTI2021

Optimization of Localized High Concentration Electrolytes (LHCE) for Li||LiCoO 2 and Si|| LiCoO 2 Batteries used in Consumer Electronics Applications (Final Report for I3T Project 75934)

This project will optimize localized high concentration electrolyte (LHCE) for Li/LCO and Si/LCO batteries for consumer electronics applications, including select the best solvent and diluent, optimize the ratios of the solvents and the salt concentration. Results will be demonstrated not only in both coin cells, but also in pouch cells, which is required for large-scale commercial applications. This work can provide better understanding that would also benefit other LMB projects, including Li/NMC and Li/S batteries for electric vehicle applications. In the history of rechargeable batteries, all batteries have been first used in small scale consumer electronics, then eventually penetrate to large scale applications such as electrical vehicle or grid. We believe this development route will also be true for LMBs. By developing the best electrolyte for Li/LCO and Si/LCO chemistry, we will not only get the early market entry in consumer electronics, but we can also accumulate experience on the practical application of LMBs which can be used to further develop other types of LMBs for EV and other large-scale applications pursued by DOE.

25 ENERGY STORAGE↗