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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Effect of reaction media on hydrogenolysis of polyethylene plastic waste: Polymer-surface interactions in small alkane/polymer blends

The polymer reaction media and its properties can be altered by recycling a fraction of liquid products or adding alkane solvents. Less clear is whether this strategy affects hydrogenolysis. Herein, we investigated the effect of short-chain alkanes C n consisting of n carbons (n=8, 16, and 32) on the upcycling of high-density polyethylene (HDPE) plastic waste to lubricant-range products over Ru/TiO 2 catalysts by multiscale simulations and experiments. First, we trained a force field for polymer/surface interactions on a Ru 22 nanoparticle (NP) supported on TiO 2 . Using replica exchange molecular dynamics simulations, we studied the effect of small hydrocarbons on the adsorption of a surrogate polymer, C 142 , on the catalyst. We found segregation of long chains (C 142 ) at the catalyst surface due to the enthalpy gained by adsorbing more C-C bonds of the long chains, compensating for entropic losses upon adsorption. Short-chain molecules decrease the adsorbed carbons of long chains on the Ru NP due to blocking Ru active sites. Compared to the bulk chains, competitive adsorption results in a broader, heavy-tailed distribution of end-to-end distance of adsorbed chains. Our experiments demonstrated that catalyst activity declines significantly beyond simple dilution due to changes in polymer adsorption, and tuning the reaction media by creating suitable blends impacts hydrogenolysis. Density distributions for a 50:50%wt mixture of PP and PE show that PE chains are segregated at the surface, so they are prone to C-C bond breaking much faster than PP chains. H/D exchange experiments show preferential deuteration of PE, while CH 3 groups of PP remain undeuterated. Furthermore, this may be explained by the preferential sorption of PE over PP, leading to specific distribution in the polymer blend.

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

Topological Effects Near Order–Disorder Transitions in Symmetric Diblock Copolymer Melts

The effects of polymer chain topology on the order–disorder transition of symmetric AB diblock copolymer melts are studied using coarse-grained molecular dynamics simulations. Specifically, we compared chain conformations near the lamellar-disordered transition in melts of symmetric (i.e., 50–50) AB diblock copolymers of linear chains, rings, and trefoil knots at the same chain lengths. The order (lamellar)–disorder transition temperature and the domain sizes both shifted to lower values with the introduction of topological constraints, leading to the following sequence: linear chains > rings > trefoil knots. Furthermore, investigation of the polymer chain conformations in terms of their radii of gyration, their writhe values (a measure for the degree of intertwining of a chain around itself), and their Jones polynomials (a method to measure entanglement of curves) showed that linear chains and rings remained stretched, while knots were stretched and tightened in disordered melts close to the lamellar-disorder transition. This work highlights chain topology as an important factor in affecting microphase separation in block copolymers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A modular and extensible CHARMM-compatible model for all-atom simulation of polypeptoids

Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single chains and their self-assembly into morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General Force Field has demonstrated success in accurate all-atom molecular modeling of peptoid structure and thermodynamics. Extension of this force field to new peptoid side chains has historically required reparameterization of side chain bonded interactions against ab initio data. This fitting protocol improves the accuracy of the force field but is also burdensome and precludes modular extensibility of the model to arbitrary peptoid sequences. In this work, we develop and demonstrate a Modular Side Chain CGenFF-NTOID (MoSiC-CGenFF-NTOID) as an extension of CGenFF-NTOID employing a modular decomposition of the peptoid backbone and side chain parameterizations, wherein arbitrary side chains within the large family of substituted methyl groups (i.e., –CH 3 , –CH 2 R, –CHRR', and –CRR'R") are directly ported from CGenFF. We validate this approach against ab initio calculations and experimental data to develop a MoSiC-CGenFF-NTOID model for all 20 natural amino acid side chains along with 13 commonly used synthetic side chains and present an extensible paradigm to efficiently determine whether a novel side chain can be directly incorporated into the model or whether refitting of the CGenFF parameters is warranted. We make the model freely available to the community along with a tool to perform automated initial structure generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Development of Coarse-Grained Models for Poly(4-vinylphenol) and Poly(2-vinylpyridine): Polymer Chemistries with Hydrogen Bonding

In this paper, we identify the modifications needed in a recently developed generic coarse-grained (CG) model that captured directional interactions in polymers to specifically represent two exemplary hydrogen bonding polymer chemistries—poly(4-vinylphenol) and poly(2-vinylpyridine). We use atomistically observed monomer-level structures (e.g., bond, angle and torsion distribution) and chain structures (e.g., end-to-end distance distribution and persistence length) of poly(4-vinylphenol) and poly(2-vinylpyridine) in an explicitly represented good solvent (tetrahydrofuran) to identify the appropriate modifications in the generic CG model in implicit solvent. For both chemistries, the modified CG model is developed based on atomistic simulations of a single 24-mer chain. This modified CG model is then used to simulate longer (36-mer) and shorter (18-mer and 12-mer) chain lengths and compared against the corresponding atomistic simulation results. We find that with one to two simple modifications (e.g., incorporating intra-chain attraction, torsional constraint) to the generic CG model, we are able to reproduce atomistically observed bond, angle and torsion distributions, persistence length, and end-to-end distance distribution for chain lengths ranging from 12 to 36 monomers. We also show that this modified CG model, meant to reproduce atomistic structure, does not reproduce atomistically observed chain relaxation and hydrogen bond dynamics, as expected. Simulations with the modified CG model have significantly faster chain relaxation than atomistic simulations and slower decorrelation of formed hydrogen bonds than in atomistic simulations, with no apparent dependence on chain length.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Developing a Carbon Negative Biorefinery for Organic Waste Valorization

Production of bio-based chemicals have become increasingly attractive as efforts to meet carbon neutrality goals expand. Diverse organic waste feedstocks can be valorized via arrested anaerobic digestion and chain elongation to produce important key intermediates, such as medium chain carboxylic acids. Our work aims to develop a carbon negative biorefinery that funnels multiple organic waste feedstocks into a chemically consistent stream of carboxylic acids that are then upgraded to exemplary carbon negative products. The pairing of a hydrolysis reactor with a chain elongation reactor will allow each biological step to be optimized to improve the ability to valorize a variety of organic waste streams. Specifically, this work has so far been aimed at screening for potential chain elongating organisms to produce VFAs and MCCAs of interest. Four chain elongating organisms were tested for their chain elongation potential with diverse single and mixed substrates. So far, Megasphaera elsdenii and Actinobacillus succinogenes have been tested to determine potential differences in titer as well as product speciation due to variations in pH. To do this, each organism was tested under 3 different substrate combinations with pH maintained at either 5.5, 6, or 7. With better understanding of their metabolic needs and optimal operating conditions, these chain elongating organisms could provide a valuable option to facilitate the chain elongation necessary to produce precursor molecules. In addition to optimizing the bioconversion steps, downstream processing of carboxylic acids is also a key component for the overall feasibility of the process. Our group previously developed a downstream in-situ product recovery (ISPR) process for continuously recovering bio-based carboxylic acids from fermentation broth. The ISPR includes: (i) a solid-liquid separation as a cell retention device, (ii) a liquid-liquid extraction (LLE) to selectively extract the desired bio-based acids, and (iii) a distillation to obtain the neat product. The integrated process was demonstrated at bench-scale and is now scaled up for pilot-scale operations. A more cost-efficient membrane-based emulsion separation is introduced for LLE in downstream separation process with greatly promoted mass transfer, leading to -2800 times smaller needed membrane area than membrane contactors to achieve the same butyric acid extraction rate.

BIOMASS FUELS↗
DOE OSTI2021

Specific molecular design of polycarboxylate polymers exhibiting optimal compatibility with clay contaminants in concrete

Highlights: • Allyl ether-based PCEs with short side chain length and low side chain density presented superior clay resistance. • PCEs with medium side chain density exhibited best clay robustness when compared at the absolute dosed quantities. • The proportion of PCE being intercalated into the layered structure of clay was quantified. It is widely recognized that the dispersing ability of polycarboxylate superplasticizers (PCEs) could be hindered due to the presence of clay contaminants in concrete. In this study, a series of allyl ether-based polycarboxylate superplasticizers possessing short polyethylene glycol side chains was successfully synthesized and probed for their clay tolerance. The resulting PCE polymers were characterized via Size Exclusion Chromatography (SEC) to obtain their molecular properties. Thereafter, their dispersing ability was probed in the absence and presence of sodium bentonite. Allyl ether-based polycarboxylate (APEG) polymers possessing short side chains were found to exhibit enhanced clay resistance as compared to that of conventional MPEG PCEs holding long pendant chains. The mode of interaction between APEG PCEs and bentonite was investigated via sorption and XRD measurements. The data revealed that APEG PCEs possessing a lower side chain density intercalate less into the interlayer space of bentonite than those exhibiting higher side chain density.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Understanding the origin of softness in structurally tailored and engineered macromolecular (STEM) gels: A DPD study

Structurally tailored and engineered macromolecular (STEM) gels are polymer networks containing a primary network (the “STEM-0” gel) and side chains that are anchored to this network (forming the “STEM-1” gel). The ability to vary the features of the side chains provides a robust means of tailoring the macroscopic properties of the material. We use dissipative particle dynamics (DPD) simulations to determine the mechanical response of STEM-1 gels to uniaxial compression for various values of the side chain length, n sc . While the Young’s modulus of the material is significantly decreased with increasing n sc (at a fixed density of grafted side chains), above a certain saturation value, increasing n sc does not lead to any further softening of the sample. Using the simulations, we calculate the relevant stresses, which are related to the Young’s modulus and the number of entanglements in the network. We show that the backbone chains become more spread out upon addition of sidechains, leading to a decrease in the physical entanglements between backbone segments. This observation accounts for the decrease of stress in the backbone network and the softening of the networks through the addition of sidechains. For long chains, however, the number density of physical crosslinks between side chains is independent of side chain length; this observation explains the observed stress saturation in the STEM-1 gels. Our approach allows us to correlate the molecular architecture of the gels to the resultant macroscopic mechanical behavior and provide guidelines for fabricating STEM gels with well-defined mechanical properties, which allow the materials to be used for a variety of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Investigation of Hierarchical Structure Formation in Merocyanine Photovoltaics

Merocyanines (MCs) are a versatile class of small-molecule dyes. Their optoelectronic properties are easily tunable by chemically controlling their donor–acceptor strength, and their structural properties can be tuned by simple side-chain substitution. This paper demonstrates a novel series of MCs featuring an indoline donor with varying hydrocarbon side-chain length (from 6 to 12 carbons) and a tert-butyl-thiazole acceptor, labeled InTBT. Bulk heterojunction organic photovoltaics are fabricated with a [6,6]-phenyl-C 61 -butyric acid methyl ester (PCBM) acceptor and characterized. Films composed of I8TBT:PCBM and I9TBT:PCBM produced the highest power conversion efficiency of 4.5%, which suggests that the morphology is optimized by controlling the side-chain length. Hierarchical structure formation in InTBT:PCBM films is studied using grazing incidence X-ray diffraction (GIXRD), small-angle neutron scattering (SANS), and atomic force microscopy (AFM). When mixed with PCBM, InTBTs with ≤8 side-chain carbons form pure crystalline domains, while InTBTs with ≥9 side-chain carbons mix well with PCBM. SANS demonstrates that increasing side-chain length increases the InTBT-rich domain size. In addition, a branched hexyl–dodecyl side-chain IHDTBT:PCBM film was studied and found to exhibit the worst-performance organic photovoltaic (OPV) device. The large-branched side chain inhibited mixing between IHDTBT and PCBM resulting in large segregated phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Cyclic Topology Enhancing Structural Ordering and Stability of Comb-Shaped Polypeptoid Thin Films against Melt-Induced Dewetting

We investigated the effect of cyclic chain topology on the molecular ordering and thermal stability of comb-shaped polypeptoid thin films on silicon (Si) substrates. Cyclic and linear poly(N-decylglycine) (PNDG) bearing long n-decyl side chains were synthesized by ring-opening polymerization of N-decylglycine-derived N-carboxyanhydrides. When the spin-coated thin films were subjected to thermal annealing at temperatures above the melting temperature (T > T m ), the cyclic PNDG films exhibited significantly enhanced stability against melt-induced dewetting than the linear counterparts (l-PNDG). When recrystallized at temperatures below the crystallization temperature (T < T c ), the homogeneous c-PNDG films exhibit enhanced crystalline ordering relative to the macroscopically dewetted l-PNDG films. Both cyclic and linear PNDG molecules adopt cis-amide conformations in the crystalline film, which transition into trans-amide conformations upon melting. A top-down solvent leaching treatment of both l/c-PNDG films revealed the formation of an irreversibly physisorbed monolayer with similar thickness (ca. 3 nm) on the Si substrate. The physisorbed monolayers are more disordered relative to the respective thicker crystalline films for both cyclic and linear PNDGs. Upon heating above T m , the adsorbed c-PNDG chains adopt trans-amide backbone conformation identical with the free c-PNDG molecules in the molten film. By contrast, the backbone conformations of l-PNDG chains in the adsorbed layers are notably different from those of the free chains in the molten film. We postulate that the conformational disparity between the chains in the physically adsorbed layers versus the free chains in the molten film is an important factor to account for the difference in the thermal stability of PNDG thin films. These findings highlight the use of cyclic chain topology to suppress the melt-induced dewetting in polymer thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Structure, Dynamics, and Hydrogen Transport in Amorphous Polymers: An Analysis of the Interplay between Free Volume Element Distribution and Local Segmental Dynamics from Molecular Dynamics Simulations

Polymers are attractive membrane materials owing to their mechanical robustness and relatively inexpensive fabrication. An important indicator of membrane performance are free volume elements (FVE): microporous void spaces created by the inefficient packing of bulky groups along the polymer chain. FVEs tend to degrade over time, as polymer chains reorganize irreversibly. While it is widely accepted that polymer flexibility has an impact on membrane transport properties, the molecular nature of this impact is still not well understood. By the establishment of a correlation between local chain dynamics and the distribution of free volume elements (FVEs), penetrant transport can be regulated more efficiently in amorphous polymer membranes. In this work, we implement all-atom molecular dynamics (MD) simulations to explore the relationship between chain dynamics and free volume in three polymers with different levels of backbone flexibility: polymethylpentene (PMP), polystyrene (PS), and HAB-6FDA thermally rearranged polymer (TRP). We construct these polymers at different temperatures and examine how temperature impacts the FVE distribution and segmental mobility. Our analysis shows that chain segments near FVEs have higher mobility compared with the atoms in the bulk; the extent of this difference increases with chain flexibility. Increasing the chain flexibility by increasing the temperature results in a broader FVE distribution. Rigid polymers such as TRP show the most robust FVE distribution and are not significantly affected by the temperature change. To capture penetrant diffusion through the polymer matrix, hydrogen is inserted and the diffusion is measured at different temperatures; hydrogen mobility is influenced by the FVE structure and overall mobility of polymer chains. Lastly, at low temperatures, hydrogen mobility is influenced by void distribution, while at high temperatures, polymer dynamics dictate hydrogen transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Crystallization of Bottlebrush Statistical Copolymers of Polystyrene and Poly(ethylene oxide)

Here, bottlebrush statistical copolymers (BSCPs) with poly(ethylene oxide) (PEO) and polystyrene (PS) side chains grafted to a polynorbornene (PNB) backbone were synthesized by ring-opening metathesis polymerization (ROMP). The impact of the glassy PS side chains on the crystallization of the PEO side chains as a function of the backbone length, grafting densities, and fraction of the PS and PEO side chains is described. The bottlebrush architecture, where the side chains are anchored to the backbone, inherently constrains the mobility of PEO. Compared with the bulk crystallization temperature of PEO, the higher glass transition temperature of PS places further constraints on PEO crystallization. The limited mobility of PEO leads to cold crystallization behavior during heating. Reduced grafting densities, in turn, reduce side-chain crowding, leading to less extended pendant structures. The degree of crystallinity of PEO was found to decrease at lower grafting densities to a point where crystallization was not observed. The average distance between bottlebrush backbones increased linearly with the backbone length, suggesting that the backbone forms a distinct mesodomain. For BSCPs with asymmetric volume fractions of PS and PEO side chains, the degree of crystallinity of PEO increases with a change from cold crystallization to normal nucleation and growth during cooling, as a result of reduced constraints on PEO mobility by the glassy PS side chains.

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

Short Range Order in Disordered Spinel and the Impact on Cation Vacancy Transport

Spinels are important complex oxides for use in radiation damage environments and resulting from the corrosion of steels. It is known that, in these environments, normal spinels exist with some concentration of antisite cation pairs known as inversion. In this work we show that even in highly disordered states characterized by high levels of inversion, spinel still shows some short range order (SRO) that manifests itself in antisite chains. The propensity to form these antisite chains is confirmed through Monte Carlo simulations which find that the length of chains which can form depend on the spinel chemistry. We also consider the effect of antisite chains on the diffusivity of cation vacancies and find the effect strongly depends on the spinel chemistry. At the extremes, chains in FeCr2O4 significantly increase vacancy transport but in MgAl2O4 chains have the inverse effect of drastically reducing vacancy mobility. The explanation of these dramatically different effects results from the assessment of the thermodynamic stability of the antisite chains and contrasting attractive/repulsive interactions of vacancies with the chains.

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

2023 Critical Materials Strategy

The global effort to curb carbon emissions is accelerating demand for clean energy technologies and the materials they rely on. Demand for these materials will only continue to grow, especially as some nations aim to achieve net zero emissions by 2050. While some major materials like steel, copper, and aluminum are already powering the fossil fuel economy, others are more minor materials with potential supply risks. These risks could jeopardize the ability to reduce greenhouse gas emissions within the desirable timeframe to avoid significant climate change. In some cases, it may be necessary to take action to improve the resilience of material supply chains and mitigate supply risks. Understanding the importance of individual materials to clean energy and the supply risks associated with them is necessary to identify which materials may serve as potential roadblocks to a clean energy future. The U.S. Department of Energy (DOE) issued a series of 13 supply chain deep dive assessment reports on various energy technologies in 2022 in response to President Biden’s Executive Order on America’s Supply Chains (E.O. 14017). These reports emphasized that supply chain bottlenecks can occur at any stage of the value chain from mining and refining to component and even sub-system manufacturing. The bottlenecks are a combination of factors such as material availability, equipment availability, work force availability and quality, logistics, regulatory framework, and market conditions. These bottlenecks were worsened during the global Covid-19 pandemic. Its lingering impacts have hindered capacity expansion for material supply chains and prevented product lead-time recovery. One approach to reduce supply chain risks for the United States is to have a strong domestic manufacturing sector with a diverse set of producers. Boosting responsible domestic production would require leveraging the latest science not only in material extraction but also in developing substitutes, recycling, reuse, and remanufacturing. This report is an updated analysis of previous Critical Materials Strategy (CMS) reports published by the DOE in 2010, 2011, and 2019 based on national and global priorities, technology advancement, and technology adoption trends. Like the CMS reports, this analysis presents the results of a formal material criticality assessment to identify which materials are critical to the continued deployment of clean energy technologies globally. The analysis in this report leveraged the DOE supply chain deep dive assessments to develop the initial list of materials to evaluate. This DOE Critical Materials Assessment (CMA) is conducted independently of criticality assessments performed by other U.S. government agencies, such as that conducted by the U.S. Geological Survey (USGS). This analysis complements the USGS critical minerals determination in three aspects. First, the DOE assessment is performed from a global perspective, while the USGS analysis focusses on the importance of minerals to the U.S. economy. Second, this report focuses on the importance of materials to clean energy technologies, rather than to the economy in general. Lastly, this study is forward looking to 2035 based on clean energy deployment scenarios, whereas the USGS assessment is retrospective. Materials evaluated in this report that do not appear in the USGS Critical Minerals List include copper, uranium, electrical steel, and SiC. A draft version of this report received ~80 public comments related to supporting data and methodological improvement. Those comments have been incorporated as much as possible where appropriate. Highlights of findings from this 2023 CMA include: Rare earth materials (neodymium, praseodymium, dysprosium, and terbium) used in magnets in electric vehicle (EV) motors and wind turbine generators continue to be critical. While dysprosium (Dy) and terbium (Tb) are both heavy rare earth elements that serve the same function in magnets, the criticality of Tb is slightly lower than that for Dy in the short term due to the widespread use of Dy in high-grade magnets and Tb’s present role as a substitute. Similarly, praseodymium (Pr) is critical in the medium term but only near critical in the short term because it is more substitutable in magnets than neodymium (Nd); Materials used in batteries for EVs and stationary storage are now considered to be critical. While cobalt (Co) was found to be critical in this and previous reports, lithium (Li) becomes critical in the medium term due to its broader use in various battery chemistries and the rampant growth of the EV industry. Natural graphite is a new addition in this assessment and is also found to be critical; Platinum group metals used in hydrogen electrolyzers, such as platinum (Pr) and iridium (Ir), are critical due to an increased focus on hydrogen technologies to achieve net zero carbon emissions, while those used in catalytic converters, such as rhodium (Rh) and palladium (Pd), were screened out due to the decreased importance of catalytic converters in the medium term; Gallium (Ga) continues to be critical due to its use in light-emitting diodes (LEDs). In addition, the use of Ga has increased in magnet manufacturing and in semiconductor in forms such as gallium arsenide (GaAs) or gallium nitride (GaN); Major materials like Aluminum (Al), copper (Cu), nickel (Ni), and silicon (Si) move from noncritical in the short term to near critical in the medium term due to their importance in electrification; Electrical steel is near critical due to its use in transformers for the grid and electric motors in EVs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Next-Generation Reverse Logistics Networks of Photovoltaic Recycling: Perspectives and Challenges

With the growing adoption of solar energy as a key component of the global energy transition and its new industrial policy (the Inflation Reduction Act and others), the United States is witnessing a significant increase in solar investments. This surge in installations and domestic and reshored manufacturing of solar photovoltaic (PV) panels brings with it a pressing issue: the proper management of end-of-life (EoL) PV panels. As these panels are decommissioned, either due to reaching the end of their lifespans or due to breakage across the various stages of the forward supply chain, it becomes crucial to establish efficient reverse supply chain logistics systems to address the challenges associated with their disposal, while also unlocking the value of the inherent materials that are of critical value for other forward supply chains. This perspective article examines the challenges regarding EoL PV panels and relevant reverse supply chain and logistics networks, and proposes future research directions based on the gaps observed among academic research, industry, and policy-making challenges. We identify the main bottlenecks and hurdles including, among others, the lack of supportive regulations and absence of structured, optimized recycling infrastructure. To this end, it is proposed that the key to achieving a sustainable reverse supply chain network for solar PV panels lies in relentless end-to-end supply chain cost optimization efforts supported by enabling policies. Moreover, it is proposed that designing systematic decision-making modeling frameworks is vital for examining different possibilities and scenarios for state, region or nation-wide optimization of solar PV reverse supply chain networks. Indicative to this effect, we discuss the development of a Resource-Task-Network (RTN)-based model and demonstrate its application and benefits through a case study. We wrap up with conclusions and future research directions.

circular economy↗
DOE OSTI2026

Genetic and metabolic drivers of membrane remodeling in Clostridium thermocellum under alcohol stress

Clostridium thermocellum is a leading candidate for consolidated bioprocessing of lignocellulosic biomass into biofuels due to its native cellulolytic capabilities. Beyond ethanol, C. thermocellum is being developed as a platform for producing higher-chain alcohols such as isobutanol and n-butanol. However, its physiological adaptations to alcohol stress remain poorly understood. Here, we investigate how C. thermocellum remodels its membrane lipid composition in response to exogenous ethanol, n-butanol, isobutanol, and butyrate. Exposure to linear alcohols such as n-butanol or to organic acids like butyrate increased the proportion of straight-chain fatty acids in the membrane at the expense of branched-chain species, whereas exposure to the branched alcohol isobutanol produced the opposite effect. Isotope tracer experiments demonstrated that C. thermocellum directly incorporates the carbon backbones of exogenous alcohols and acids into fatty acids, providing a mechanistic basis for these contrasting shifts. We show that the bifunctional aldehyde/alcohol dehydrogenase AdhE is essential for the assimilation of exogenous alcohols into fatty acids, acting through its oxidative activity by first oxidizing alcohols to aldehydes and then converting them to acyl-CoA intermediates. Deletion of the pyruvate:ferredoxin oxidoreductase isozyme pfor4 abolished branched-chain fatty acid synthesis, but supplementation with isobutanol restored production, indicating that Pfor4 substitutes for the canonical branched-chain α-keto acid dehydrogenase complex. These findings reveal two distinct routes for branched-chain fatty acid production in C. thermocellum: a Pfor4-dependent pathway from α-keto acid intermediates derived from amino acid synthesis, and an AdhE-dependent salvage pathway that assimilates exogenous branched-chain alcohols.

Acetivibrio thermocellus↗
DOE OSTI2021

Bio-project “derisking” through development of systematic methodologies and frameworks for risk assessment

One of the primary hindrances to producing a viable, sustainable domestic biomass industry for renewable biofuels, bio-products and bio-power is the lack of understanding and quantification of the risks associated with both the biomass supply chain and preprocessing and conversion technologies. Currently a consistent method for assessing, comparing, and quantifying risks in biomass supply chains does not exist, creating a major investment barrier to bioenergy projects in the U.S. The lack of a standardized approach has resulted in bioenergy stakeholders independently using inconsistent approaches and evaluation criteria, leading to unreliable and incomparable assessments of risks and financing barriers to bio-project development. Along with the challenges of inconsistent risk assessment for supply chain risk, technology specific risks based on variability in biomass properties are not fully understood and can pose significant unforeseen challenges for bioenergy projects. In many cases these properties have not yet been identified and the impacts on the proposed technology and products unquantified. This is particularly challenging for emerging preprocessing and conversion technologies. Without a firm understanding of the preprocessing/conversion technology-specific critical properties, the risk of a proposed bio-project cannot be fully evaluated. To address inconsistent risk evaluation in the biomass supply chain supporting project financing, a Biomass Supply Chain Risk Standards (BSCRS) framework was developed. The BSCRS framework includes a comprehensive list of known and perceived risks (Risk Indicators) to the supply chain developed through 100’s of interviews with bioenergy industry experts spanning from feedstock growers and suppliers to representatives from the financial sector. These risks have been organized into a manageable hierarchy of Risk Categories and Risk Factors that can be practically assessed. This BSCRS framework also provides mitigation strategies for multiple Risk Indicators from best available industry practices and research findings. Additionally, a risk quantification methodology for each Risk Factor, Risk Category, and the bio-project as a whole was developed to enable capital markets to assess feedstock risk more efficiently and more accurately. Multiple case studies representing existing bio-projects have been used to evaluate and verify the BSCRS framework and scoring methodology. To address technological risk along with the supply chain risk captured in the developed BSCRS framework, this work also focuses on development of a systematic criticality assessment tool using well-accepted, quantitative risk analysis methods to evaluate bioenergy feedstock critical properties impacting system unit operations. The proposed Failure Mode and Effect Analysis (FMEA) approach uses a team of subject area experts (SAEs) for each targeted unit operation within a system. Collectively, the team will develop and use a quantitative scoring system to assess the material attributes, process parameters, and quality attributes for key unit operations that have already been identified. The FMEA process generates Risk Priority Numbers (RPNs) for the various failures and predominant causes for each material/process unit/product combination resulting in a semi-quantitative, standardized methodology for assessing technological risk and biomass properties contributing to that risk.

09 BIOMASS FUELS↗
DOE OSTI2021

A structural explanation for the mechanism and specificity of plant branching enzymes I and IIb

Branching enzymes (BEs) are essential in the biosynthesis of starch and glycogen and play critical roles in determining the fine structure of these polymers. The substrates of these BEs are long carbohydrate chains that interact with these enzymes via multiple binding sites on the enzyme’s surface. By controlling the branched-chain length distribution, BEs can mediate the physiological properties of starch and glycogen moieties; however, the mechanism and structural determinants of this specificity remain mysterious. In this study, we identify a large dodecaose binding surface on rice BE I (BEI) that reaches from the outside of the active site to the active site of the enzyme. Mutagenesis activity assays confirm the importance of this binding site in enzyme catalysis, from which we conclude that it is likely the acceptor chain binding site. Comparison of the structures of BE from Cyanothece and BE1 from rice allowed us to model the location of the donor-binding site. We also identified two loops that likely interact with the donor chain and whose sequences diverge between plant BE1, which tends to transfer longer chains, and BEIIb, which transfers exclusively much shorter chains. When the sequences of these loops were swapped with the BEIIb sequence, rice BE1 also became a short-chain transferring enzyme, demonstrating the key role these loops play in specificity. Taken together, these results provide a more complete picture of the structure, selectivity, and activity of BEs.

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

Multi-variance replica exchange SGMCMC for inverse and forward problems via Bayesian PINN

Physics-informed neural network (PINN) has been successfully applied in solving a variety of nonlinear non-convex forward and inverse problems. However, the training is challenging because of the non-convex loss functions and the multiple optima in the Bayesian inverse problem. In this work, we propose a multi-variance replica exchange stochastic gradient Langevin dynamics method to tackle the challenge of the multiple local optima in the optimization and the challenge of the multiple modal posterior distribution in the inverse problem. Replica exchange methods are capable of escaping from the local traps and accelerating the convergence; two chains with different temperatures are designed where the low temperature chain aims for the local convergence, and the target of the high temperature chain is to travel globally and explore the whole loss function entropy landscape. However, it may not be efficient to solve mathematical inversion problems by using the vanilla replica method directly since the method doubles the computational cost in evaluating the forward solvers (likelihood functions) in the two chains. To address this issue, we propose to make different assumptions on the energy function estimation and this facilities one to use solvers of different fidelities in the likelihood function evaluation. More precisely, one can use a solver with low fidelity in the high temperature chain while using a solver with high fidelity in the low temperature chain. Our proposed method significantly lowers the computational cost in the high temperature chain, meanwhile preserving the accuracy and converging very fast. Here we give an unbiased estimate of the swapping rate and give an estimation of the discretization error of the scheme. To verify our idea, we design and solve four inverse problems which have multiple modes. The proposed method is also employed to train the Bayesian PINN to solve the forward and inverse problems; faster and more accurate convergence has been observed when compared to the stochastic gradient Langevin dynamics (SGLD) method and vanilla replica exchange methods.

97 MATHEMATICS AND COMPUTING↗