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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 505 records · Page 28

Anodic Dissolution Rates Accelerate with Decreasing MoS 2 Nanoflake Thickness

Electrochemical gating of 2D transition metal dichalcogenide (TMD) electrodes is an emerging frontier in the field of semiconductor electrochemistry. In this approach, an applied bias modifies the charge carrier concentration of the 2D TMD, causing band edge shifts and drastic changes in charge transfer rates. However, leveraging this effect for (photo)electrocatalysis is practically limited by the stability of the TMD material under gating conditions. Gerischer showed anodic dissolution of bulk TMD electrodes can occur in the dark and hypothesized that the reaction proceeds via an electron tunneling mechanism from surface states to the TMD conduction band [H. Gerischer, D. Ross, and M. Lubke, Z. Physickalische Chem., 139, 1 (1984)]. Here we investigate this possibility in single MoS 2 nanoflakes using in situ optical microscopy and explore whether Gerischer’s electron tunneling mechanism can explain anodic dissolution rates of thin 2D semiconductors. Here, spatially resolved measurements show anodic dissolution initiates at perimeter edge sites and accelerates exponentially with decreasing layer thickness, consistent with Gerischer’s tunneling mechanism. Interestingly, single layer MoS 2 is impervious to anodic dissolution at applied potentials >200 mV more positive than those required to drive dissolution in bulk and multilayer-thick nanoflakes.

2D semiconductor↗

Influence of Proton Activity Gaps between Electrodes on Open-Circuit Potential of H 2 /H 2 and H 2 /Air Cells

Polymer -electrolyte-fuel-cell open-circuit voltages (OCVs) are exactly defined by equation (1), where cathode and anode proton activities [(aH+)cathode and (aH+)anode, respectively] usually are identical, so the third term in the right-hand side of equation (2) is ignored. OCV=E0+RT/2F*ln(a1/2 O2*(a2 H+)cathode/aH2O)-RT/2F*ln((a2 H+)anode/aH2) (1) =E0+RT/2F*ln(a1/2 O2*aH2/aH2O)+RT/2F*ln((a2 H+)cathode/(a2 H+)anode) (2) Water vapor pressure is a colligative property that fundamentally correlates to electrolyte concentrations in aqueous solutions. Proton activity is a function of acid concentration, such as pH, when electrolytes are acids. In polymer-electrolyte membranes, water vapor pressure and acid concentration are understood as relative humidity (RH) and water uptake (λ), respectively, where λ represents number of water molecules per sulfonic acid molecule. Several investigations have reported the relationship between RH and λ, meaning that proton activities and associated water uptakes are intimately related to RH. In actual fuel cell operation, cathode RH is determined by ambient-atmosphere and/or humidifier RH(s), and anode RH depends on hydrogen-circulator RH. Therefore, RH is not always identical at both electrodes, and the difference between electrode RHs is considerable during dry operation of polymer electrolyte fuel cells. Therefore, the third term in the right-hand side of equation (2) may be significant for dry operation. We measured OCVs when hydrogen was supplied to both electrodes at 80°C. One electrode (A) was fixed at 30% RH, while RH at the other electrode (B) was varied (0, 5, 10, 20, and 30%). Measured OCVs varied from 0 to 75 mV. For fuel cell tests, electrode A was supplied with hydrogen at 30% RH; electrode B, oxygen at 0, 5, 10, 20, and 30% RH. OCVs deviated from that measured when RH at electrode B was 30%, increasing from 0 to 60 mV with decreasing RH at electrode B. Results are also shown in Figure 1. Proton activities of both electrodes were thermodynamically calculated. The Gibbs–Duhem relation was applied to obtain molar Gibbs free energies of water and sulfonic acid, and proton activity coefficient was calculated using the Gibbs free energy of sulfonic acid and the relationship between RH and λ1–4, assuming that protons and sulfonic anions show identical ionic-activity coefficients. OCVs were estimated using the third term in the right-hand side of equation (2). Results are shown in Figure 1. Fuel-cell current–voltage performance was poor when RHs at the anode and cathode were 30 and 20%, respectively. To determine kinetic current, we measured the oxygen-reduction reaction (ORR) using a rotating-disk electrode (RDE) in concentrated-acid aqueous solutions, which modeled catalyst-layer ionomers. Kinetic currents decreased with acid concentrations. References T. A. Zawodzinski, Jr., C. Derouin, S. Radzinski, R. J. Sherman, V. T. Smith, T. E. Springer and S. Gottesfeld , J. Electrochem. Soc., 140,1041 (1993) P. K. Das and A. Z. Weber, Proceedings of the ASME 2013 11th Fuel Cell Science, Engineering and Technology Conference, Fuel Cell 18010 (2013) V. A. Sethuraman, J. W. Weidner, A. T. Haug, S. Motupally,b and L. V. Protsailo, J. Electrochem. Soc., 155, B50 (2008) A. Kusoglu and A. Z. Weber, Chem. Rev., 117, 987 (2017) Figure 1

Yoshida, Toshihiko↗

pnnl/HCDfCBD

Harmonizing Complex Datasets for Chem-Bio Defense

Claborne, Daniel [Pacific Northwest National Labor↗

“Godzilla,” the Extreme African Dust Event of June 2020: Origins, Transport, and Impact on Air Quality in the Greater Caribbean Basin

In June 2020, the tropical Atlantic and the Caribbean Basin were affected by a series of African dust outbreaks unprecedented in size and intensity. These events, informally named “Godzilla,” coincided with CALIMA, a large field campaign, offering a rare opportunity to assess the impact of African dust on air quality in the Greater Caribbean Basin. Network measurements of respirable particles (i.e., PM 10 and PM 2.5 ) showed that dust significantly degraded regional air quality and increased the risk to public health in the Caribbean, the southern United States, northern South America, and Central America. CALIMA examined the meteorological context of Godzilla dust events over North Africa and how these conditions might relate to the greatly increased dust emissions and enhanced transport to the Americas. Godzilla was linked to strong pressure anomalies over West Africa, resulting in a large-scale geostrophic wind anomaly at 700 hPa over North Africa. We used surface-based and columnar measurements to test the performance of two frequently used aerosol forecast models: the NASA Goddard Earth Observing System (GEOS) and Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) models. The models showed some skills but differed substantially between their forecasts, suggesting large uncertainties in these forecasts that are critical for issuing early warnings of health-threatening dust events. Our results demonstrate the value of an integrated approach in characterizing the spatial and temporal variability of African dust transport and assessing its impact on regional air quality. Future studies are needed to improve models and to track the long-term changes in dust transport from Africa under a changing climate.

Aerosols/particulates↗

Urbanization-induced land and aerosol impacts on storm propagation and hail characteristics

Changes in land surface and aerosol characteristics from urbanization can affect dynamic and microphysical properties of severe storms, thus affecting hazardous weather events resulting from such storms such as hail and tornado. We examine the joint and individual effects of urban land and anthropogenic aerosols of Kansas City on a severe convective storm observed during the 2015 Plains Elevated Convection At Night (PECAN) field campaign, focusing on storm evolution, convective intensity, and hail characteristics. The simulations are carried out at the cloud-resolving scale (1 km) using a version of WRF-Chem in which the spectral-bin microphysics (SBM) is coupled with the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC). It is found that the urban land effect of Kansas City initiated a much stronger convective cell and the storm got further intensified when interacting with stronger turbulence induced by the urban land. The urban land effect also changed the storm path by diverting the storm toward the city mainly resulting from enhanced urban land-induced convergence in the urban area and around the urban-rural boundaries. The joint effect of urban land and anthropogenic aerosols enhances occurrences of both severe hail and significant severe hail by ~ 20% by enhancing hail formation and growth from riming. Overall the urban land effect on convective intensity and hail is relatively larger than the anthropogenic aerosol effect, but the joint effect is much notable than either of the individual effects, emphasizing the importance to consider both effects in evaluating urbanization effects.

Lin, Yun↗

SARS-CoV2 Docking Dataset

Description: Small-molecule conformations and docking scores for 1.4 billion molecules docked against 6 protein targets from SARS-CoV2: MPro 5R84, MPro 6WQF, NSP15 6WLC, PLPro 7JIR, Spike 6M0J, and a hand-optimized model of the RNA-dependent RNA polymerase. Docking was carried out using the Autodock-GPU program performing 20 independent structure minimizations per dock - saving 3 results per molecule. Scores reported include the Autodock free energy estimate as well as RF3 and VS-DUD-E v2 machine-learned rescoring models. Protein structure files and maps in the format input to Autodock-GPU are included. Literature Ref: Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19, J. Chem. Inf. Model. 2020, 60(12): 5832–5852.

36 MATERIALS SCIENCE↗

MnRhBi3: A Cleavable Antiferromagnetic Metal

This dataset contains DFT input and output files supporting the theoretical modeling in the associated publication (Chem. Mater. 2024, 36, 11306-11316). The calculations characterize MnRhBi3, an orthorhombic (Cmmm) van der Waals-layered intermetallic compound that cleaves easily between neighboring Bi layers. The dataset is organized into three calculation types: (i) Bulk: Structural relaxations of the periodic MnRhBi3 crystal in antiferromagnetic (AFM) and ferromagnetic (FM) configurations, using the vdW-DF-optB86b functional. These provide the equilibrium lattice constants, magnetic energy differences (AFM is 0.5 meV/f.u. lower than FM), and magnetic moments (4.4 µB/Mn, 0.17 µB/Rh, 0.18 µB/Bi) reported in Table 1 of the main text. (ii) Slab: Same magnetic configurations computed with an 18 Ang vacuum layer introduced between Bi layers, used to calculate the cleavage energy Ec = 0.56 J/m2 (AFM) and 0.57 J/m2 (FM), establishing MnRhBi3 as a van der Waals-layered material comparable to graphite, MoS2, and CrI3. (iii) ELF: Single-point calculation on the relaxed bulk AFM geometry with LELF=.TRUE., producing the ELFCAR file used to generate electron localization function isosurfaces and contour maps (Fig. 2, main text) showing Bi lone pairs directed into the van der Waals gaps. All folders contain CONTCAR, INCAR, KPOINTS, OUTCAR, and POSCAR. The ELF/ folder additionally contains ELFCAR. Calculations were performed using VASP 6.3.2 with PBE + vdW-DF-optB86b, PAW potentials, and an energy cutoff of 800 eV.

36 MATERIALS SCIENCE↗

Dataset for Role of electron correlation on the adenine dimer interaction for non-equilibrium geometries: a benchmark Quantum Monte Carlo study

Datasets for the calculations reported in "Role of electron correlation on the adenine dimer interaction for non-equilibrium geometries: A benchmark Quantum Monte Carlo study" by L. Washburn, A. Sedova, P. R. C. Kent. J. Chem. Phys. (2026) 165 (5): 054118. https://doi.org/10.1063/5.0332651. Includes the molecular geometries, QMCPACK, PySCF, and ORCA inputs and outputs, analysis scripts and files needed to reproduce all the figures and tables.

59 BASIC BIOLOGICAL SCIENCES↗

Modelling the coupled mercury-halogen-ozone cycle in the central Arctic during spring

Near-surface mercury and ozone depletion events occur in the lowest part of the atmosphere during Arctic spring. Mercury depletion is the first step in a process that transforms long-lived elemental mercury to more reactive forms within the Arctic that are deposited to the cryosphere, ocean, and other surfaces, which can ultimately get integrated into the Arctic food web. Depletion of both mercury and ozone occur due to the presence of reactive halogen radicals that are released from snow, ice, and aerosols. In this work, we added a detailed description of the Arctic atmospheric mercury cycle to our recently published version of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem 4.3.3) that includes Arctic bromine and chlorine chemistry and activation/recycling on snow and aerosols. The major advantage of our modelling approach is the online calculation of bromine concentrations and emission/recycling that is required to simulate the hourly and daily variability of Arctic mercury depletion. We used this model to study coupling between reactive cycling of mercury, ozone, and bromine during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) spring season in 2020 and evaluated results compared to land-based, ship-based, and remote sensing observations. The model predicts that elemental mercury oxidation is driven largely by bromine chemistry and that particulate mercury is the major form of oxidized mercury. The model predicts that the majority (74%) of oxidized mercury deposited to land-based snow is re-emitted to the atmosphere as gaseous elemental mercury, while a minor fraction (4%) of oxidized mercury that is deposited to sea ice is re-emitted during spring. Our work demonstrates that hourly differences in bromine/ozone chemistry in the atmosphere must be considered to capture the springtime Arctic mercury cycle, including its integration into the cryosphere and ocean.

54 ENVIRONMENTAL SCIENCES↗

Lithium-Ion Battery Supply Chain for E-Drive Vehicles in the United States: 2010–2020

Understanding the battery supply chain is particularly important for the strategic planning and development of a battery recycling infrastructure to secure critical materials supply and enable a circular economy. Argonne has been tracking plug-in electric vehicle (PEV) sales in the United States (U.S.) by make and model since December 2010, when the Chevrolet Volt and Nissan Leaf were first sold in the U.S. Building on detailed monthly sales data, this report summarizes the manufacturing and production locations of lithium-ion (Li-ion, or LIB) battery cells and packs by make and model for PEVs sold in the U.S. from 2010 to 2020. It also summarizes the annual and cumulative Li-ion battery capacity installed in hybrid electric vehicles (HEVs) sold in the U.S. Overall, there are about 20 different battery cell and pack manufacturers, which are currently supplying about 20 gigawatt-hours (GWh) of batteries annually for the U.S. PEV market. Panasonic and LG Chem are the largest cell suppliers to the U.S. market. Beyond the U.S, South Korea and Japan are major countries supplying PEV batteries to the U.S. market.

25 ENERGY STORAGE↗

MicroResonators for Compacts Optical Sensors (μRCOS)

As the demand for continuous, in-situ surveillance of health of systems and environments rapidly increases, miniaturized sensors with fast responses are sought. Optical dielectric resonators supporting Whispering Gallery Modes (WGMs) have exceptional properties, like very high-power density, very narrow spectral linewidth, and extremely small mode volume. As the footprint of these sensors is drastically reduced, measurements of microvolumes samples with dramatic reduction in analysis time are possible, enabling large numbers of parallel analyses using microarrays. The high sensitivity and speed of WGM resonators combined with the ability to detect molecules in their native state have great future potential for basic and applied research such as reliable single molecule, trace-gas detection, environmental monitoring, chemical threat sensing, and biodefense Such appealing peculiarities motivated us developing WMG resonators (WGMRs) for Cavity Enhanced Absorption Spectroscopy (CEAS) for chem-bio detection. Specifically, we designed and batch-fabricated microspheres and fiber tapers for resonances excitation. We successfully detected gases (N 2 and CO 2 ) in customized environmental chambers, and bio-organisms (Inf. A and E. Coli) with integrated microfluidic systems. Background calibration and environmental isolation were always accounted for in proving the performances.

36 MATERIALS SCIENCE↗

MicroResonators for Compacts Optical Sensors (μRCOS)

As the demand for continuous, in-situ surveillance of health of systems and environments rapidly increases, miniaturized sensors with fast responses are sought. Optical dielectric resonators supporting Whispering Gallery Modes (WGMs) have exceptional properties, like very high-power density, very narrow spectral linewidth, and extremely small mode volume. As the footprint of these sensors is drastically reduced, measurements of microvolumes samples with dramatic reduction in analysis time are possible, enabling large numbers of parallel analyses using microarrays. The high sensitivity and speed of WGM resonators combined with the ability to detect molecules in their native state have great future potential for basic and applied research such as reliable single molecule, trace-gas detection, environmental monitoring, chemical threat sensing, and biodefense Such appealing peculiarities motivated us developing WMG resonators (WGMRs) for Cavity Enhanced Absorption Spectroscopy (CEAS) for chem-bio detection. Specifically, we designed and batch-fabricated microspheres and fiber tapers for resonances excitation. We successfully detected gases (N 2 and CO 2 ) in customized environmental chambers, and bio-organisms (Inf. A and E. Coli) with integrated microfluidic systems. Background calibration and environmental isolation were always accounted for in proving the performances.

36 MATERIALS SCIENCE↗

Testing of the Defense Waste Processing Facility Cold Chemical Dissolution Method in Sludge Batch 10 Qualification

For each sludge batch that is processed in the Defense Waste Processing Facility (DWPF), the Savannah River National Laboratory (SRNL) tests the applicability of the digestion methods used by the DWPF Laboratory for elemental analysis of Sludge Receipt and Adjustment Tank (SRAT) Receipt samples and SRAT Product process control samples. DWPF SRAT samples are typically dissolved using a method referred to as the DWPF Cold Chemical or Cold Chem Method (CC), (see DWPF Procedure SW4-15.201- 2.1).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Biological particles and aerosol-cloud interactions in the Southern Great Plains (Final Report)

The United States Southern Great Plains (SGP) is the genesis for much of the warm season precipitation in the central and eastern United States. While atmospheric thermodynamics and large-scale dynamics play an important role in formation of precipitation, precipitation mechanisms are also sensitive to aerosols. Aerosols can suppress precipitation as cloud condensation nuclei (CCN) or act as ice nucleating particles (INP) in deep convective clouds. This project focused on understanding the role of primary biological aerosol particles (PBAP) in the region and its influence on cloud formation. Specifically, we focused on biological aerosol in the form of pollen, one type of PBAP that is emitted in large yet variable quantities from vegetation in the mid latitudes. Field observations provide evidence of pollen in the planetary boundary layer and pollen components in cloud droplets and fine particulate matter. Further, pollen grains can easily rupture when wet, forming smaller, sub pollen particles with sizes less than one micron. We evaluated the potential for PBAP events at the Department of Energy (DoE) SGP Atmospheric Radiation Measurement (ARM) research facility due to the rich dataset available. We also developed model simulations that accounted for pollen emission and the generation of sub pollen particles, which have been shown to be both cloud condensation nuclei and ice nucleating particles. The proposed work was designed to address the following questions: 1. What are the physical and chemical signatures of biological aerosol such as pollen in SGP ARM measurements? 2. What is the role of pollen-derived particles on deep convection and precipitation in the Central US? Using measurements from the DoE SGP ARM site and recent airborne campaigns, we evaluated the signatures of pollen and pollen-derived aerosols on optical properties, cloud properties and precipitation (Subba et al., 2021). We identified pollen-driven events over the data record and used the Weather Research and Forecasting Model with fully coupled chemistry (WRF-Chem) to conduct chemically realistic simulations of aerosols during and summer mesoscale convective events in the Southern Great Plains (Subba et al., in review). This work improved our understanding of the role of biological aerosol on clouds and precipitation in the Central United States and placed these results in context with anthropogenically-driven processes.

54 ENVIRONMENTAL SCIENCES↗

Biological particles and aerosol-cloud interactions in the Southern Great Plains

The United States Southern Great Plains (SGP) is the genesis for much of the warm season precipitation in the central and eastern United States. While atmospheric thermodynamics and large-scale dynamics play an important role in formation of precipitation, precipitation mechanisms are also sensitive to aerosols. Aerosols can suppress precipitation as cloud condensation nuclei (CCN) or act as ice nucleating particles (INP) in deep convective clouds. This project focused on understanding the role of primary biological aerosol particles (PBAP) in the region and its influence on cloud formation. Specifically, we focused on biological aerosol in the form of pollen, one type of PBAP that is emitted in large yet variable quantities from vegetation in the mid latitudes. Field observations provide evidence of pollen in the planetary boundary layer and pollen components in cloud droplets and fine particulate matter. Further, pollen grains can easily rupture when wet, forming smaller, sub pollen particles with sizes less than one micron. We evaluated the potential for PBAP events at the Department of Energy (DoE) SGP Atmospheric Radiation Measurement (ARM) research facility due to the rich dataset available. We also developed model simulations that accounted for pollen emission and the generation of sub pollen particles, which have been shown to be both cloud condensation nuclei and ice nucleating particles. The proposed work was designed to address the following questions: 1. What are the physical and chemical signatures of biological aerosol such as pollen in SGP ARM measurements? 2. What is the role of pollen-derived particles on deep convection and precipitation in the Central US? Using measurements from the DoE SGP ARM site and recent airborne campaigns, we evaluated the signatures of pollen and pollen-derived aerosols on optical properties, cloud properties and precipitation (Subba et al., 2021). We identified pollen-driven events over the data record and used the Weather Research and Forecasting Model with fully coupled chemistry (WRF-Chem) to conduct chemically realistic simulations of aerosols during and summer mesoscale convective events in the Southern Great Plains (Subba et al., in review). This work improved our understanding of the role of biological aerosol on clouds and precipitation in the Central United States and placed these results in context with anthropogenically-driven processes.

54 ENVIRONMENTAL SCIENCES↗

Controlling Molecular Structure and Spin with Multiconfigurational Quantum Chemistry (Final Technical Report)

For many first-row transition metal complexes, structure-property relationships can be obtained from high-level molecular geometry optimizations and subsequent electronic structure studies. The project funded under this award utilized newly implemented fully internally contracted (FIC) nuclear gradients for extended multi-state (XMS) complete active space second-order multireference perturbation theory (CASPT2) to explore geometry changes in first-row transition metal coordination complexes. At the start of the project, only one full geometry optimization using FIC-CASPT2 analytical gradients had been reported (J. Chem. Theory Comput., 2016, 12 (8), 3781), and many open-questions regarding the performance and achievable accuracy in applying such computations to larger complexes persisted. Key deliverables in the report include the implementation of the numerical Hessian and subsequent vibrational analysis in the BAGEL program package. This includes both full Hessian vibrational analysis (FHVA) and a partial Hessian vibrational analysis (PHVA). The latter of which allows us to reduce the significant cost of computing the vibrational frequencies in a large molecule by focusing on the modes of highest interest. The gradient code also proved useful in the development of an approach to improve the Hubbard-U correction by removing bias in predicting spin-splitting in Fe(II) complexes via plane-wave density functional theory (DFT). Finally, we showed for three families of complexes (spin-crossover (SCO) complexes, metallocorroles complexes, and those with metal-metal bonds) that CASPT2 can result in good molecular geometries and established best practices in undertaking this work. We are now using this approach in collaborative projects with experimental groups, which would not have been possible at the start of this project. A common theme also arose through this work that static and dynamic correlation must be recovered in a balanced way to yield quantitative results. By systematically varying how both effects were included, we were able to make key chemical insights. This work supported the training of two postdoctoral scholars, one graduate student, and one undergraduate student in applying high-level wavefunction based methods to challenging systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adaptive Discovery and Mixed-Variable Optimization of Next Generation Synthesizable Microelectronic Materials

Design of new microelectronic materials is characterized by several challenges such as high-dimensionality of the atomic structure-composition variable space, formidable cost of directly using high-fidelity simulations for design optimization, dispersity in literature-reported similar materials and synthesis methods, complex physical mechanisms, and mixed qualitative and quantitative design variables that lead to a disjointed design space. Even though machine learning (ML) techniques have been employed to expedite materials innovation, existing methods treat ML and design optimization as two separate processes, failing to resolve the fundamental challenges associated with high dimensionality and mixed-variable complexity. We have developed a ML enhanced mixed-variable material design optimization framework to efficiently extract useful information from existing data in literature and physics-based simulations to guide the autonomous search for optimal materials. Our proposed framework is composed of four computational modules: (1) a natural language processing (NLP) based virtual screening module, (2) classification based concept exploration module, (3) a density functional theory (DFT)-based high-fidelity evaluation model, and (4) a novel latent-variable Gaussian process (LVGP) ML model for mixed-variable problems with uncertainty quantification, which seamlessly integrates with Bayesian Optimization (BO) and achieves superb efficiency through embedded physics-based dimension reduction. Our approach is demonstrated and validated using the testbed of functional materials exhibiting metal-insulation transitions (MITs), with the targeted reversible resistivity changes (∼10^5) near room temperature. At the end of the 30-month project, we have developed a series of new ML techniques using NLP, conditional variational autoencoders, active learning, latent-variable Gaussian processes, integrated with Bayesian optimization. Our project has resulted in new predicted MITs compounds and improved understanding of MITs microscopic mechanisms, which in turn will revolutionize microelectronics science to provide energy-saving solutions. Our research has improved both creativity and efficiency in transforming rare-event discoveries of new functional materials to persistent innovations. In addition to open-sourcing the online MIT database and the classification model, the LVGP open source code has been downloaded more than 15,000 times within two years. More than 40 MIT compounds have been identified and many have been pursued experimentally via collaborators. The research results are published in close to 20 collaborative papers in high-impact journals, such as Chem. Mater., Appl. Phys. Rev., Sci. Rep., among others of design space.

36 MATERIALS SCIENCE↗

Development of a scalable, robust electrocatalytic technology for conversion of CO 2 to formic acid via microstructured materials

This project was funded by the Bioenergy Engineering for Product Synthesis (BEEPS) program under the Funding Opportunity Announcement (FOA) DE-FOA-0001916 Topic Area 5 “Rewiring Carbon Utilization”. This FOA sought projects that would electrocatalytically reduce CO 2 to a carbon intermediate and then upconvert to a multi-carbon product or fuel via non-photosynthetic biological system engineering. The project sought to combine the expertise of OCO Chem, whose chief scientist had previously developed an efficient electrocatalytic reactor for conversion of CO 2 to formate with potential to scale, Montana State University investigators who had recently patented a method for laterally grading membranes with the potential of improving reactant distribution and more uniform efficiency across membrane-based reactors, and University of South Florida which had recently discovered a novel C-C bond forming reaction not known to naturally occur in biological systems and which uses C1 substrates and circumvents the central microbial metabolism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗