Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Synthetic Fuel”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 757 records · Page 42

Using porous random fields to predict the elastic modulus of unoxidized and oxidized superfine graphite

Nuclear graphite is a candidate material for Generation IV nuclear power plants. Porous materials such as graphite can contain complex networks of pores that influence the material's mechanical and irradiation response. A methodology known as the random finite element method (RFEM) was adapted to create synthetic microstructures and predict the influence of porosity on the elastic properties of graphite during oxidation. RFEM combines random field theory and the finite element method in a Monte Carlo framework to estimate the mechanical response of a given grade of graphite. In this research, the random fields were verified through experimental characterization to predict the elastic response of three nuclear graphite grades, ETU-10, IG-110, and 2114. Finite element models (FEM) were generated using segmentations of x-ray computed tomography (XCT) data known as image-based models (IBMs) to validate and compare with the RFEM results and better understand the effects of uniform oxidation in these graphite grades. The RFEM predictions appear to correlate well with the experimental values of the measured Young’s modulus of the three graphite grades and display the same trends as IBMs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Maximizing oil production from water alternating gas (CO 2 ) injection into residual oil zones: The impact of oil saturation and heterogeneity

Residual oil zones (ROZs) are widespread reservoirs, characterized by oil at residual saturation, either underlying oil fields (brownfield) or lateral (greenfield) to such fields. These reservoirs have the potential to produce volumes of oil sufficiently significant to make appreciable impacts on the US’s oil reserves and associated incidental CO 2 sequestration. The objective of this study is to improve our understanding the impact of heterogeneous and low oil saturations, in brownfield ROZs, on the effectiveness of water alternating gas (WAG) injection strategies. ROZs occur in the Permian Basin and elsewhere, and operators are using CO 2 injection for enhanced oil recovery (EOR) in these zones. The consensus model for the formation of ROZs is that they were formed by the effect of faster regional aquifer flow, acting over millions of years. Both the magnitude of oil saturation and the spatial distribution of oil differ from water-flooded main pay zones (MPZs). To explore the most effective injection strategies, we conducted simulations of CO 2 injection into synthetic geologic reservoirs. These simulations focused on injection into reservoirs subject to either man-made waterflooding or long-term natural waterflooding. By exploring the impact of varying: oil saturation; well patterns; reservoir heterogeneity; and permeability anisotropy, we attempt to quantify the factors that most influence the effectiveness of WAG injection. WAG ratios (the ratio of injected water and CO 2 , in reservoir volumes) of interest are those that either minimize the net CO 2 utilization ratios or maximize oil production rates. In general, the most effective WAG ratios for ROZs, are consistently less than those observed undergoing CO 2 injection in the same geologic reservoir models after traditional (man-made) waterflooding. This work demonstrates that most favorable WAG ratios for oil production in ROZs are different from those in traditional MPZs because of oil saturation differences. Therefore, CO 2 injection into both zones or directly copying WAG injection designs from MPZs to ROZs might not maximize oil production.

04 OIL SHALES AND TAR SANDS↗

Selective CO 2 electrocatalysis at the pseudocapacitive nanoparticle/ordered-ligand interlayer

Enzymes feature the concerted operation of multiple components around an active site, leading to exquisite catalytic specificity. Realizing such configurations on synthetic catalyst surfaces remains elusive. In this article, we report a nanoparticle/ordered-ligand interlayer that contains a multi-component catalytic pocket for high-specificity CO 2 electrocatalysis. The nanoparticle/ordered-ligand interlayer comprises a metal nanoparticle surface and a detached layer of ligands in its vicinity. This interlayer possesses unique pseudocapacitive characteristics where desolvated cations are intercalated, creating an active-site configuration that enhances catalytic turnover by two orders and one order of magnitude against a pristine metal surface and nanoparticle with tethered ligands, respectively. The nanoparticle/ordered-ligand interlayer is demonstrated across several metals with up to 99% CO selectivity at marginal overpotentials and onset overpotentials of as low as 27 mV, in aqueous conditions. Furthermore, in a gas-diffusion environment with neutral media, the nanoparticle/ordered-ligand interlayer achieves nearly unit CO selectivity at high current densities (98.1% at 400 mA cm -2 ).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plant Design for a Developing Bioeconomy Workshop Report: Frontier Science for the Bioeconomy Workshop Series

Recent advances in fundamental plant biology research, synthetic biology, and artificial intelligence (AI) are unlocking powerful new capabilities in plant biodesign, offering unprecedented potential to reimagine plants as programmable platforms for resource-efficient production of bioenergy, biomaterials, chemicals, and more. The U.S. Department of Energy (DOE) convened the Plant Design for a Developing Bioeconomy virtual workshop on March 12 through 14, 2025, to bring together leaders across plant science, engineering, and computation to assess the current landscape and define a bold vision for future research. Discussions during the workshop built upon findings included in DOE’s Biological and Environmental Research (BER) workshop report Overcoming Barriers in Plant Transformation: A Focus on Bioenergy Crops (U.S. DOE 2024; genomicscience. energy.gov/plant-transformation). Participants identified critical knowledge gaps, technical barriers, and emerging opportunities in the design and engineering of plant systems to support a robust, resilient domestic bioeconomy aligned with DOE’s mission.

09 BIOMASS FUELS↗

Development and flight-testing of modular autonomous cultivation systems for biological plastics upcycling aboard the ISS

Cultivation of microorganisms in space has enormous potential to enable in-situ resource utilization (ISRU) Here, we develop an autonomous payload with fully programmable serial passaging and sample preservation, termed the Modular Open Biological Platform (MOBP), and flight-test the MOBP aboard the International Space Station (ISS) by conducting enzymatic and microbial plastics upcycling experiments. The MOBP is a compact, modular bioreactor system that allows for sustained microbial growth via automated media transfers, such as those for sample collection and storage for terrestrial analyses, and precise data monitoring from integrated sensors. The MOBP was flight-tested with two experiments designed to evaluate biological upcycling of the plastic poly(ethylene terephthalate) (PET). The bioproduct βKA can be polymerized into a nylon-6,6 analog with improved properties for use in the production of a variety of materials. We posit the MOBP will aid in democratizing the execution of synthetic biology in spaceflight towards enabling ISRU.

09 BIOMASS FUELS↗

Acetyl-CoA Synthesis Through a Bicyclic Carbon-Fixing Pathway in Gas-Fermenting Bacteria

Gas-fermenting acetogens can upgrade one-carbon (C1) compounds (such as CO2 and CO) to the two-carbon (C2) metabolite acetyl coenzyme A (CoA) and convert sugar feedstocks to acetyl-CoA with minimal CO2 emissions. Fulfilling the biosynthetic potential of these microbes requires overcoming challenges in pathway engineering. Here we design a synthetic acetyl-CoA bi-cycle-in addition to the natural carbon-fixing pathways-for C2 metabolite synthesis. This pathway produces an acetyl-CoA by fixation of two CO2 equivalents via three functional modules acting in sequence: carbon fixation, gluconeogenesis and non-oxidative glycolysis. The pathway was examined by in silico thermodynamic and kinetic analyses. The prototypic pathway was implemented in a syngas-fermenting organism, Clostridium ljungdahlii DSM 13528, by expressing a heterologous phosphoketolase that can work with other native enzymes in the host acetogen. The carbon conversion pathway is possible under various growth conditions and is independent of the Wood-Ljungdahl pathway for the valorization of H2 and CO2. This study reports the improvement of carbon conversion using a reductive acetyl-CoA bi-cycle and the potential impact of redox homoeostasis in the acetogenic host for industrial applications of gas fermentation.

Acetyl-CoA↗

A comprehensive and synthetic dataset for global, regional, and national greenhouse gas emissions by sector 1970–2018 with an extension to 2019

To track progress towards keeping global warming well below 2 °C or even 1.5 °C, as agreed in the Paris Agreement, comprehensive up-to-date and reliable information on anthropogenic emissions and removals of greenhouse gas (GHG) emissions is required. Here we compile a new synthetic dataset on anthropogenic GHG emissions for 1970–2018 with a fast-track extension to 2019. Our dataset is global in coverage and includes CO 2 emissions, CH 4 emissions, N 2 O emissions, as well as those from fluorinated gases (F-gases: HFCs, PFCs, SF 6 , NF 3 ) and provides country and sector details. We build this dataset from the version 6 release of the Emissions Database for Global Atmospheric Research (EDGAR v6) and three bookkeeping models for CO 2 emissions from land use, land-use change, and forestry (LULUCF). We assess the uncertainties of global greenhouse gases at the 90 % confidence interval (5th–95th percentile range) by combining statistical analysis and comparisons of global emissions inventories and top-down atmospheric measurements with an expert judgement informed by the relevant scientific literature. We identify important data gaps for F-gas emissions. The agreement between our bottom-up inventory estimates and top-down atmospheric-based emissions estimates is relatively close for some F-gas species (~ 10 % or less), but estimates can differ by an order of magnitude or more for others. Our aggregated F-gas estimate is about 10 % lower than top-down estimates in recent years. However, emissions from excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are cumulatively larger than the sum of the reported species. Using global warming potential values with a 100-year time horizon from the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), global GHG emissions in 2018 amounted to 58 ± 6.1 GtCO 2 eq. consisting of CO 2 from fossil fuel combustion and industry (FFI) 38 ± 3.0 GtCO 2 , CO 2 -LULUCF 5.7 ± 4.0 GtCO 2 , CH 4 10 ± 3.1 GtCO 2 eq., N2O 2.6 ± 1.6 GtCO 2 eq., and F-gases 1.3 ± 0.40 GtCO 2 eq. Initial estimates suggest further growth of 1.3 GtCO 2 eq. in GHG emissions to reach 59 ± 6.6 GtCO 2 eq. by 2019. Our analysis of global trends in anthropogenic GHG emissions over the past 5 decades (1970–2018) highlights a pattern of varied but sustained emissions growth. There is high confidence that global anthropogenic GHG emissions have increased every decade, and emissions growth has been persistent across the different (groups of) gases. There is also high confidence that global anthropogenic GHG emissions levels were higher in 2009–2018 than in any previous decade and that GHG emissions levels grew throughout the most recent decade. While the average annual GHG emissions growth rate slowed between 2009 and 2018 (1.2 % yr –1 ) compared to 2000–2009 (2.4 % yr –1 ), the absolute increase in average annual GHG emissions by decade was never larger than between 2000–2009 and 2009–2018. Our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. There are a number of countries that have reduced GHG emissions over the past decade, but these reductions are comparatively modest and outgrown by much larger emissions growth in some developing countries such as China, India, and Indonesia. There is a need to further develop independent, robust, and timely emissions estimates across all gases. As such, tracking progress in climate policy requires substantial investments in independent GHG emissions accounting and monitoring as well as in national and international statistical infrastructures. The data associated with this article (Minx et al., 2021) can be found at https://doi.org/10.5281/zenodo.5566761.

54 ENVIRONMENTAL SCIENCES↗

Discovery of multi-functional polyimides through high-throughput screening using explainable machine learning

Polyimides have been widely used in modern industries because of their excellent mechanical and thermal properties, e.g., high-temperature fuel cells, displays, and aerospace composites. However, it usually takes decades of experimental efforts to develop a successful product. Aiming to expedite the discovery of high-performance polyimides, we utilize computational methods of machine learning (ML) and molecular dynamics (MD) simulations. Our study provides compelling evidence for the effectiveness of a data-driven approach in discovering novel polyimides. We first build a comprehensive library of more than 8 million hypothetical polyimides based on the polycondensation of existing dianhydride and diamine/diisocyanate molecules. Then we establish multiple ML models for the thermal and mechanical properties of polyimides based on their experimentally reported values, including glass transition temperature, Young’s modulus, and tensile yield strength. The obtained ML models demonstrate excellent predictive performance in identifying the key chemical substructures influencing the thermal and mechanical properties of polyimides. The use of explainable machine learning describes the effect of chemical substructures on individual properties, from which human experts can understand the cause of the ML model decision. Applying the well-trained ML models, we obtain property predictions of the 8 million hypothetical polyimides. Then, we screen the whole hypothetical dataset and identify three (3) best-performing novel polyimides that have better-combined properties than existing ones through Pareto frontier analysis. For an easy query of the discovered high-performing polyimides, we also create an online platform https://polyimide-explorer.herokuapp.com/ that embeds the developed ML model with interactive visualization. Furthermore, we validate the ML predictions through all-atom MD simulations and examine their synthesizability. The MD simulations are in good agreement with the ML predictions and the three novel polyimides are predicted to be easy to synthesize via Schuffenhauer’s synthetic accessibility score. Following the proposed ML guidance, we successfully synthesized a novel polyimide and the experimentally obtained high glass transition/thermal decomposition temperature demonstrated its excellent thermal stability. Here our study demonstrates an efficient way to expedite the discovery of novel polymers using ML prediction and MD validation. The high-throughput screening of a large computational dataset can serve as a general approach for new material discovery in other polymeric material exploration problems, such as organic photovoltaics, polymer membranes, and dielectrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Glycosylation of hyperthermostable designer cellulosome components yields enhanced stability and cellulose hydrolysis

Biomass deconstruction remains integral for enabling second-generation biofuel production at scale. However, several steps necessary to achieve significant solubilization of biomass, notably harsh pretreatment conditions, impose economic barriers to commercialization. By employing hyperthermostable cellulase machinery, biomass deconstruction can be made more efficient, leading to milder pretreatment conditions and ultimately lower production costs. The hyperthermophilic bacterium Caldicellulosiruptor bescii produces extremely active hyperthermostable cellulases, including the hyperactive multifunctional cellulase CbCel9A/Cel48A. Recombinant CbCel9A/Cel48A components have been previously produced in Escherichia coli and integrated into synthetic hyperthermophilic designer cellulosome complexes. Since then, glycosylation has been shown to be vital for the high activity and stability of CbCel9A/Cel48A. Here, we studied the impact of glycosylation on a hyperthermostable designer cellulosome system in which two of the cellulosomal components, the scaffoldin and the GH9 domain of CbCel9A/Cel48A, were glycosylated as a consequence of employing Ca. bescii as an expression host. Inclusion of the glycosylated components yielded an active cellulosome system that exhibited long-term stability at 75 degrees C. The resulting glycosylated designer cellulosomes showed significantly greater synergistic activity compared to the enzymatic components alone, as well as higher thermostability than the analogous nonglycosylated designer cellulosomes. These results indicate that glycosylation can be used as an essential engineering tool to improve the properties of designer cellulosomes. Additionally, Ca. bescii was shown to be an attractive candidate for production of glycosylated designer cellulosome components, which may further promote the viability of this bacterium both as a cellulase expression host and as a potential consolidated bioprocessing platform organism.

09 BIOMASS FUELS↗

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an↗

Elevated Temperature Graphite Mechanical Testing

High purity graphite will be used for core components within most High Temperature Reactor (HTR) designs. Several "high tech” industries currently utilize synthetic, high-purity, commercially available graphite components to fabricate photovoltaic cells, semi-conductors, optical fibers, and other high value electronic industry products. New advanced HTR designs are also interested in using these graphite grades for long-term, internal core component applications. Consequently, the US Department of Energy, Advanced Reactor Technologies (DOE-ART) program has spent several years testing different high purity graphite grades for potential use within these new nuclear reactor designs. A significant part of that effort has been in the development and improvement of American Society for Testing and Materials (ASTM) test standards specifically for nuclear graphite grades. Nearly all ASTM test standards have either been developed or improved by the DOE-ART program over the past 25 years. The ART program continues to assist in the development of new ASTM test standards in support of the future commercial HTR fleet currently being designed and built in the USA. The newest effort undertaken by ART is the development of high temperature mechanical testing practices that may be acceptable for a future ASTM test standard (or guide) for this critical material property measurement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Burning velocities of R-32/O 2 /N 2 mixtures: Experimental measurements and development of a validated detailed chemical kinetic model

This work entails characterizing the flammability of the refrigerant R-32 (CH 2 F 2 ) by both experimental measurements and modeling. Burning velocities S u were measured using a constant-volume spherical-flame method for R-32/O2/N 2 mixtures with O 2 /N 2 ratios ranging from 21% (synthetic air) to 40%, pressures of (1 to 3) bar, and equivalence ratios $\phi$ of (0.8 to 1.3). Based on a critical assessment of available data, and extended by our own calculations, a detailed chemical kinetic model was developed and key reactions determined using reaction path and sensitivity analyses. Initiation and combustion were identified as distinct kinetic regimes and burning velocities were found to be controlled by two primary reactions: unimolecular decomposition of CH 2 F 2 → CHF + HF and the subsequent reaction, CHF + O 2 → CHFO + O, the latter reaction initiating the radical chain propagating and branching by producing O atoms. Sensitive rate constants in the kinetic model were critically adjusted within their uncertainties and current knowledge bounds to best fit the experimental burning velocities. We found that rate constants in the model could be adjusted to match a given experimental S u for specific conditions (O 2 loading, P, T, $\phi$). This, however, then fixes predicted burning velocities for other all conditions within (3 to 4)% if physically realistic rate parameters are maintained. Thus, the entire set of experimental data is fit, not just to particular conditions. Relative random uncertainties in the experimental Su measurements were (4 to 6)%, but assumptions made for thermal radiation lost by the burned gas in the spherical-flame experiments add an additional systematic uncertainty. Systematic differences between the limiting cases of adiabatic (no thermal radiation lost) and optically-thin (all thermal radiation lost) varied significantly with conditions and ranged from (4 to 30)% at high to low velocities, respectively, translating into uncertainties of (2 to 15)% considering the average of two limiting cases. Comparison of experimental and kinetically modeled Su values suggests that the burned gas tends towards the optically-thin limit at the lowest pressures and fuel loadings and toward the adiabatic limit at the highest pressures and loadings. We tested and found support for this conclusion with a detailed analysis as a function of all the conditions (T, P, % O 2 , $\phi$). This behavior appears to transition from optically-thin to adiabatic as the density of the initial fuel increases, which results in increased CO 2 in the burned gas and thus increased absorption of the thermal radiation (consistent with the Beer-Lambert Law). The validated detailed model based on evaluated kinetics is shown to accurately predict burning velocities for R-32 O 2 /N 2 mixtures over a wide range of conditions and provides a reliable basis for extrapolation to other conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Separation of thorium, uranium, and rare earths from a strip solution generated from coarse coal refuse

This work systematically evaluated the separation performance of thorium, uranium, and rare earths when coal and coal byproduct were utilized as a non-traditional feedstock for rare earth production. A synthetic solution was prepared following the elemental composition of a strip solution generated from coarse coal refuse and used throughout the study. Various separation techniques including selective precipitation, solvent extraction, and a modified experimental protocol incorporating the two were applied to extract rare earths while minimizing the non-selective recovery of thorium and uranium into the product stream. Test results indicate that selective precipitation was effective for the removal of thorium at a pH value approaching 5 while solvent extraction preferentially removed uranium from rare earths. Therefore, a modified experimental protocol consisting of both selective precipitation and solvent extraction was subsequently developed and implemented. The findings following the modified experimental protocol indicate that extractant concentration, solvent extraction feed pH, and organic to aqueous (O/A) ratio all played a significant role in the removal of uranium. Among all the tests conducted, the best separation performance was achieved using a one-stage precipitation at a pH value of 4.8, 50 v% TBP, solvent extraction feed pH of 3.5, and an O/A ratio of 3, which corresponded to an overall rare earth, thorium, and uranium recovery of 79.6%, 0%, and 3.1%, respectively.

01 COAL, LIGNITE, AND PEAT↗

Data reduction considerations for the burning velocity of spherical constant volume flames of R32 (CH 2 F 2 ) with air

Here, the present work explores data reduction techniques for the measurement of the laminar burning velocities of R32(CH 2 F 2 )-air mixtures using a constant volume combustion device, in which the pressure-time history is the only measured parameter. To allow clear assessment of the accuracy of the data reduction methods, the pressure-time histories used for analysis are synthetically generated via a detailed numerical simulation employing full kinetics and with and without an optically-thin radiation model. Various data reduction models are employed, including a two-zone model and two multi-zone models, and these are compared with the results from the burning velocity obtained from the output of the numerical simulation. The data reduction schemes are shown to be accurate if the same radiation model is employed in the data reduction as was used in the flame simulation to generate the pressure trace used for post-processing. If the incorrect radiation model is employed, however, the errors can be quite large. The effects of stretch, radiation, and different data post-processing methodologies are explored and the errors quantified. Stretch is shown to be important for the early stages and the selected data range that is used for extrapolation has a significant effect on the extrapolated burning velocity. However, with an appropriate choice of data considered for extrapolation, the prediction of the unstretched burning velocity can be quite accurate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental Evaluation of Geopolymer, Nano-Modified, and Neat Class H Cement by Using Diametrically Compressive Tests

Abstract Cement is the prime barrier material to maintain zonal isolation during wellbore life-cycle. Different types of the cement have different performances on sealability. The primary objective of this study is evaluation of three types of cement systems, neat Class H, nano-synthetic graphite, and rock-based geopolymer cements, on interfacial bond integrity. Diametrical compressive tests are used on casing–cement–formation systems. Cement performances are tested in a conventional configuration (Berea Sandstone). A universal testing system is utilized to analyze the relationship applied load–axial strain and the digital image correlation (DIC) technique is used to generate the strain field maps. Based on the relationship and DIC results, bond strengths in different cement systems are evaluated. Additionally, microscope images provide insight explanations of the bond from micro-view. Based on the experimental results, failures of all cases initiate and propagate from the casing–cement interface. Then, radial cracks develop through the formation. This is because the mechanical interlocking bonds are formed only at the cement–sandstone interface to enhance the bond strength. The comparison of geopolymer and nano-modified cements with the conventional cement (neat Class H) shows that the unconventional cements have a lower maximum load and higher axial strain before failure of the samples. It indicates that both the two kinds of cements are more ductile than conventional cement and can support more deformation before the initiation of cracks.

Energy & Fuels↗

Plasma-Initiated Graft Polymerization of Acrylic Acid onto Fluorine-Doped Tin Oxide as a Platform for Immobilization of Water-Oxidation Catalysts

The discovery of new and versatile strategies for the immobilization of molecular water-oxidation catalysts (WOCs) is crucial for developing clean energy conversion devices [e.g., (photo)electrocatalytic cells for water splitting]. The traditional approach for surface attachment to transparent conductive oxides [e.g., fluorine doped tin oxide (FTO)] is via synthetic modification of the ligand architecture to incorporate functional groups such as carboxylic acids (-COOH) or phosphonates (-PO 3 H 2 ) prior to immobilization. However, challenges arising from desorption and the cumbersome derivatizations steps have limited the scope and applications of surface-bound WOCs. Herein, we report the successful immobilization of underivatized Ru(II)-based WOCs (Ru–Cat1 = [Ru(tpy) (bpy) (H 2 O)] 2+ (tpy = 2,2':6'2"–terpyridine and bpy = 2,2;-bipyridine) and Ru–Cat2 = [Ru(Mebimpy) (bpy) (H 2 O)] 2+ (Mebimpy = 2,6-bis(1-methylbenzimidazol-2-yl) pyridine)) and the Ru(II) polypyridyl chromophore Ru–C3 = [Ru(bpy) 3 ] 2+ onto a FTO plasma-grafted poly(acrylic acid) surface (PAA|FTO). Various characterization techniques such as attenuated total reflectance Fourier transform infrared spectroscopy, scanning electron microscopy, atomic force microscopy, and cyclic voltammetry measurements provide evidence for the plasma-induced grafted PAA|FTO film and immobilization. Surface stability and electrocatalytic properties of these new hybrid composite films upon cycling were investigated at different pH values. Immobilized Ru–Cat1 and Ru–Cat2 onto PAA|FTO displayed pH-dependent (RuIII/RuII) couples and onset potentials indicative of PCET (proton-coupled electron transfer) reactions. Based on cyclic voltammetry results and spectroscopic monitoring, the immobilized WOCs Ru–Cat1 and Ru–Cat2 exhibited a higher surface stability in neutral aqueous solutions relative to Ru–C3 upon electrochemical oxidation. Furthermore, we attribute the surface PCET and stability to the presence of a water ligand in the coordination sphere of immobilized Ru–Cat1 and Ru–Cat2 which can H-bond with negatively charged carboxylate groups of the cross-linked PAA brushes. Our findings demonstrate that the plasma-grafted polymeric network onto FTO offers a versatile platform to directly anchor unmodified homogeneous WOCs or chromophores for potential applications in solar-to-fuel energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Developing Advanced Genetic and Synthetic Biology Tools for Improved Algae Productivity

Under the UCSD-led Productivity Enhanced Algae and ToolKits (PEAK) project we sought to develop tools to enable the production of valuable co-products, as well as strategies to decrease the cost of cultivation, with an intended outcome of enabling the economic production of algae-based biofuel. We have developed new genetic tools and high throughput selection methods for eukaryotic green algae and used them to express a high value recombinant protein; a growth factor known as Osteopontin (OPN). Recombinant OPN protein expression levels were improved through a newly developed rapid breeding and mutagenesis strain improvement method to generate a robust strain capable of growing in outdoors raceway conditions in brackish water that tolerated high pH and large temperature swings. We further applied the new genetic tools to express recombinant protein in a recently bioprospected strain with even more robust growth characteristics. In response to the COVID-19 pandemic we used our improved workflow to rapidly express, purify, and characterize a recombinant SARS-CoV-2 spike protein Receptor Binding Domain (RBD) and demonstrate that it functionally interacts with its cognate human host receptor ACE2. The newly identified extremophile strain Chlamydomonas sp (402), both mating type (mt+) and mating type (mt-), have been deposited in the Chlamydomonas Resource Center (https://www.chlamycollection.org/), making them available world-wide with no restrictions. In addition, all of genetic tools are also deposited at this site and are also available world-wide with no restrictions.

09 BIOMASS FUELS↗

Molecular-Level Control over Ionic Conduction and Ionic Current Direction by Designing Macrocycle-Based Ionomers

Poor ionic conductivity of the catalyst-binding, submicrometer- thick ionomer layers in energy conversion and storage devices is a huge challenge. However, ionomers are rarely designed keeping in mind the specific issues associated with nanoconfinement. Here, we designed nature-inspired ionomers (calix-2) having hollow, macrocyclic, calix[4]arene-based repeat units with precise, sub-nanometer diameter. In ≤100 nm-thick films, the in-plane proton conductivity of calix-2 was up to 8 times higher than the current benchmark ionomer Nafion at 85% relative humidity (RH), while it was 1-2 orders of magnitude higher than Nafion at 20-25% RH. Confocal laser scanning microscopy and other synthetic techniques allowed us to demonstrate the role of macrocyclic cavities in boosting the proton conductivity. The systematic self-assembly of calix-2 chains into ellipsoids in thin films was evidenced from atomic force microscopy and grazing incidence small-angle X-ray scattering measurements. Moreover, the likelihood of alignment and stacking of macrocyclic units, the presence of one-dimensional water wires across this macrocycle stacks, and thus the formation of long-range proton conduction pathways were suggested by atomistic simulations. We not only did see an unprecedented improvement in thin-film proton conductivity but also saw an improvement in proton conductivity of bulk membranes when calix-2 was added to the Nafion matrices. Nafion-calix-2 composite membranes also took advantage of the asymmetric charge distribution across calix[4]arene repeat units collectively and exhibited voltage-gating behavior. The inclusion of molecular macrocyclic cavities into the ionomer chemical structure can thus emerge as a promising design concept for highly efficient ion-conducting and ion-permselective materials for sustainable energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗