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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↗

Characterizing Complex Gas–Solid Interfaces with in Situ Spectroscopy: Oxygen Adsorption Behavior on Fe–N–C Catalysts

Electrocatalysts for the oxygen reduction reaction within polymer electrolyte membrane fuel cells based on iron, nitrogen, and carbon elements (Fe–N–C) are receiving significant research attention as they offer an inexpensive alternative to catalysts based on platinum-group metals. Although both the performance and the fundamental understanding of Fe–N–C catalysts have improved over the past decade, there remains a need to differentiate the relative activity of different active sites. Toward this goal, our study is focused on characterizing the interactions between O 2 and a set of five structurally different Fe–N–C materials. Detailed characterization of the Fe speciation was performed with 57 Fe Mössbauer spectroscopy and soft X-ray absorption spectroscopy of the Fe L 3,2 -edge, whereas nitrogen chemical states were investigated with X-ray photoelectron spectroscopy (XPS). In addition to initial sXAS and XPS measurements performed in ultra-high vacuum (UHV), measurements were also performed (at the identical location) in an atmosphere of 100 mTorr of O 2 at 80 °C (O 2 -rich). XPS and sXAS results reveal the presence of several types of FeNxCy adsorption sites. FeNxCy sites that are proposed as the most active ones do not show significant change (based on the techniques used in this study) when their environment is changed from UHV to O 2 -rich. Correlation with Mössbauer and sXAS results suggests that this is most likely due to the persistence of strongly adsorbed O 2 molecules from their previous exposure to air. However, other species do show spectroscopic changes from UHV conditions to O 2 -rich. This implies that these sites have a weaker interaction with O 2 that results in their desorption in vacuum conditions and re-adsorption when exposed to the O 2 -rich environment. The nature of these weakly and strongly O 2 -adsorbing FeN x C y sites is discussed in the context of different synthetic and processing parameters employed to fabricate each of these five Fe–N–C materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adsorptive recovery of volatile fatty acids from wastewater fermentation broth

This work developed an adsorptive separation and recovery process for anaerobically generated volatile fatty acids (VFAs) from swine wastewater fermentation. Batch adsorption studies were conducted using several weak anion exchange resins and synthetic adsorbent resins to identify a suitable candidate. Relite RAM2 with a tertiary amine functional group showed the highest adsorption (over 98%) of hexanoic acid. Under the different pH values (1.8–7.5) and extraction temperatures (30–50 ↑C), the highest adsorption was observed at a pH of 3.2, which is below the pKa of hexanoic acid, at all the evaluated temperatures. A full factorial design was used to optimize the resin and VFA concentrations, wherein over 99% adsorption could be achieved when the ratio of VFA to resin was below 0.23 (g/g) for model solution (VFAs in water). The adsorption equilibrium could be achieved within 30 min of contact time and 0.5% w/v NaOH was identified as a suitable desorption agent. Under the optimal conditions, 65–72% of VFAs present in fermentation broth was adsorbed, which was increased to 72–76% by using fresh resins. The VFAs adsorption and recovery efficiency were maintained for 9 successive cycles without requiring extensive resin washing and regeneration for both model solution and fermentation broth. Altogether, the work presents a comprehensive study for resin adsorption to recover VFAs and provides a potential industrial-relevant process to recover VFAs from fermentation broth.

09 BIOMASS FUELS↗

pH adjustment increases biofuel production from inhibitory switchgrass hydrolysates

Biofuels derived from renewable and sustainable lignocellulosic biomass, such as switchgrass, offer a promising means to limit greenhouse gas emissions. However, switchgrass grown under drought conditions contains high levels of chemical compounds that inhibit microbial conversion to biofuels. Fermentation of drought switchgrass hydrolysates by engineered Saccharomyces cerevisiae and Zymomonas mobilis results in lower ethanol production than does fermentation of hydrolyzed switchgrass from a typical rainfall year. Here, it is demonstrated that this inhibitory effect can be alleviated by altering the pH of drought switchgrass hydrolysates produced by two different pretreatment methods: Ammonia Fiber Expansion (AFEX) and Soaking in Aqueous Ammonia (SAA). Fermentation rates and biofuel production by Saccharomyces cerevisiae and Zymomonas mobilis were higher at pH 5.8 than at pH 5.0 from all feedstock years and following both pretreatment methods. SAA pretreatment of drought switchgrass furthermore enabled increased fermentation rates and biofuel titers compared to AFEX pretreatment. A synthetic mimic of switchgrass hydrolysate was developed and identified relief from pH-dependent inhibition by lignocellulose-derived inhibitors as the cause of increased biofuel production above a pH of 5.0. These results demonstrate that SAA pretreatment and pH adjustment can significantly improve fermentation and biofuel production from inhibitory feedstocks by industrial microorganisms.

09 BIOMASS FUELS↗

Impact of Concurrent Solubilization and Fines Migration on Fracture Aperture Growth in Shales during Acidized Brine Injection

Acidic hydraulic fracturing fluid chemically and physically alters shale rock fabric during injection and shut-in, creating a “reaction-altered zone” along the fracture faces. To better characterize the variable thickness and composition of this reaction-altered zone under advective flow, we take a coupled experimental and modeling approach. A fluidic cell, with six fiducial markers, is first fabricated to keep the rock sample in place during the core floods and to allow image alignment of acquired images. Then, we conduct a series of reactive core floods in a clay-rich siliceous Wolfcamp shale sample with 10 wt % carbonate, using a synthetic fracturing fluid under no confining stress and at room temperature. High-resolution computed tomography (CT) scans are periodically conducted to observe the spatial alteration of the fracture network. We then perform scanning electron microscopy (SEM-EDS) on the two orthogonal surfaces (fracture surface and freshly cut profile face) to generate high-resolution elemental maps that show the change in mineralogy, both with distance along a given flow path along a fracture surface and with depth from the fracture surface into the shale matrix. These results are contrasted against a two-dimensional (2D) advection-diffusion reaction model developed previously for batch reactions between shale and synthetic fracturing fluids. The model simulates the geochemical interaction occurring at the fracture/matrix interface and penetrating into the shale matrix during the reactive core flood. Both model and experimental results show that the acidic brine is neutralized during the core flood, corresponding to an increase in fracture aperture as a function of fluid volume injected with the greatest change near the inlet. SEM-EDS scans reveal significant dissolution of carbonates on the fracture surface without pyrite oxidation. The reactive transport model indicates that carbonate depletion into the shale interior should be observable, yet SEM-EDS shows no discernible loss of carbonate in the orthogonal profile face. The combination of these observations suggests an additional fracture evolution mechanism in the reactive system, i.e., fines migration. We show that fines migration enhances the access of fracturing fluid to the matrix resulting in a more pronounced fracture widening. Finally, we conclude that coupled mineral dissolution and fines migration govern fracture aperture growth during acidized brine injection. In this work, we effectively show the underlying risk of relying solely on models that do not include an important (transport) process that can alter the system significantly and propose a combined chemomechanical mechanism for fracture evolution appropriate for this shale mineralogy.

58 GEOSCIENCES↗

Computer-aided design of stability enhanced nicotinamide cofactor biomimetics for cell-free biocatalysis

Cell-free biocatalysis (CFB) is an efficient and environmentally friendly method to synthesize molecules such as pharmaceuticals, biochemicals, and biofuels through the in vitro use of enzyme cascades. These enzymes often require redox cofactors to drive chemical reactions. Natural redox cofactors (NAD(P)H) are expensive to isolate, motivating synthetic nicotinamide cofactor biomimetics (NCBs) as a cost-effective solution. A select handful of NCBs have been identified as potential NAD(P)H alternatives with comparable or improved redox capabilities, however, they display a tendency to degrade in common buffers. In this study, a library of 132 NCB candidates is systematically generated, over 85% of which have not been characterized in the literature, to expand the diversity of currently explored NCBs. The decomposition mechanism of NCBs in phosphate is evaluated using density functional theory (DFT), revealing protonation at the nicotinamide C5 position as a reporter of cofactor stability. Based on this result, we trained a linear regression model on DFT calculated descriptors to predict NCB stability in phosphate buffer, achieving mean absolute error (MAE) and root mean squared error (RMSE) values within computational accuracy. Analysis of key atomic descriptors and qualitative trends in our dataset informed the design of novel NCB candidates we propose with optimized stability. This work enables researchers to predict the relative stability of NCBs before synthesis, thereby streamlining the process to make CFB more affordable and viable at industry scales.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NPP Simulators for Coupled Thermal and Electric Power Dispatch

The Light Water Reactor Sustainability (LWRS) program within the United States Department of Energy supports extending the operation of the U.S. commercial nuclear power plant (NPP) fleet. Within the LWRS program, the Flexible Plant Operation and Generation (FPOG) Pathway works to diversify the revenue streams of light water reactors (LWRs) by opening opportunities for the co-generation of non-electric products in addition to supplying electrical power to the grid. Recent events have added greater motivation to these efforts. For example, the recent Inflation Reduction Act (IRA) passed by the U.S. federal government offers substantial tax incentives for producing clean hydrogen, the technology readiness level of dispatchable and high-efficiency hydrogen production has dramatically increased in a short time, and societal response to world climate change is driving a transition away from fossil fuels. Producing hydrogen with maximum efficiency using nuclear power requires dispatching both electrical and thermal power from the nuclear plant to the hydrogen plant, so testing concepts of operations for combined electrical and thermal power dispatch (TPD) from an NNP to a hydrogen plant is of interest. This report documents achievement of the Light Water Reactor Sustainability (LWRS) program milestone “Install and demonstrate a vendor-developed simulator on the Human Systems Simulation Laboratory (HSS) for dispatch of LWR electrical power to a close-coupled electrolysis plant” with a due date of Dec. 22, 2022. Several factors provide motivation for this effort. Coupling the power generation deck of a nuclear power plant to a hydrogen production facility introduces new possibilities for operational transients that must be addressed. In particular, the performance of the integrated system during startup and shutdown of the hydrogen production facility, as well as offnormal conditions, need to be evaluated to ensure there are no adverse effects on the operation of the existing NPP. The concept of operations involving the NPP, the hydrogen plant, and the electric power grid must be tested using NPP simulators and operating procedures that have been modified for TPD operations. These tests must also include dynamic simulations of the coupled tertiary thermal and electric loads as well as coordinated activities with NPP operators, tertiary load operators and grid power coordinators. The report summarizes progress in developing and testing full-scope NPP simulators at the HSSL, including a generic BWR simulator from GSE Systems, Inc. and generic PWR simulator from Westinghouse. In the case of the TPD-GBWR Simulator from GSE Systems, Inc., a BWR is thermally coupled to a high temperature electrolysis (HTE) plant that produces hydrogen and oxygen from de-ionized water. The hydrogen plant is not explicitly simulated but only included as a transient heat sink. A thermal power dispatch (TPD) system transfers heat between the steam systems at the BWR and the hydrogen plant. Operational results from two versions of the modified simulator are presented. The first version uses synthetic oil as a heat transfer fluid in a closed delivery heat loop (DHL) that generates steam at the hydrogen plant. The second version uses steam as the heat transfer fluid in a delivery steam line (DSL) to provide steam to the hydrogen plant. For both versions, the estimated thermal power delivery distance is approximately one kilometer. The amount of thermal power dispatched in the simulators is 15% of the total reactor thermal power such that the simulators provide a tool to study the feasibility of coupling a BWR to industrial processes that benefit from a combination electrical and thermal power dispatch. Ongoing work within a CRADA is also developing a full-scope PWR simulator provided by Westinghouse for both thermal and electric power coupling. This simulator is based on a PWR plant with two three-loop Westinghouse reactors. Westinghouse PWRs are sufficiently similar that a simulator of a three-loop reactor is an appropriate representation for two-loop and four-loop PWR reactors. The three-loop simulator will initially be modified for close-coupling to a 100 MW HTE hydrogen production plant that will require approximately 25 MW of thermal power while operating at its maximum rated capacity. The simulator testing will include full coupling to dynamic simulations of a hydrogen production plant and a representative bulk electric grid. The simulator provided by Westinghouse is similar to the GPWR simulator that INL has already obtained from GSE Systems but has a few important added benefits. First, the Westinghouse simulator is based on digital controls and has additional screens that can be called up to show parameter trends to assist operators in decision-making. The Westinghouse simulator also has upgrades to the controls and hardware representations, such as valve actuators, that make it more realistic and flexible in terms of accurately sim

99 GENERAL AND MISCELLANEOUS↗