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100 records · Page 6

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DOE OSTI2021

Controlling selectivity of modular microbial biosynthesis of butyryl-CoA-derived designer esters

Short-chain esters have broad utility as flavors, fragrances, solvents, and biofuels. Controlling selectivity of ester microbial biosynthesis has been an outstanding metabolic engineering problem. In this study, we enabled the de novo fermentative microbial biosynthesis of butyryl-CoA-derived designer esters (e.g., butyl acetate, ethyl butyrate, butyl butyrate) in Escherichia coli with controllable selectivity. Using the modular design principles, we generated the butyryl-CoA-derived ester pathways as exchangeable production modules compatible with an engineered chassis cell for anaerobic production of designer esters. We designed these modules derived from an acyl-CoA submodule (e.g., acetyl-CoA, butyryl-CoA), an alcohol submodule (e.g., ethanol, butanol), a cofactor regeneration submodule (e.g., NADH), and an alcohol acetyltransferase (AAT) submodule (e.g., ATF1, SAAT) for rapid module construction and optimization by manipulating replication (e.g., plasmid copy number), transcription (e.g., promoters), translation (e.g., codon optimization), pathway enzymes, and pathway induction conditions. To further enhance production of designer esters with high selectivity, we systematically screened various strategies of protein solubilization using protein fusion tags and chaperones to improve the soluble expression of multiple pathway enzymes. Finally, our engineered ester-producing strains could achieve 19-fold increase in butyl acetate production (0.64 g/L, 96% selectivity), 6-fold increase in ethyl butyrate production (0.41 g/L, 86% selectivity), and 13-fold increase in butyl butyrate production (0.45 g/L, 54% selectivity) as compared to the initial strains. Altogether, this study presented a generalizable framework to engineer modular microbial platforms for anaerobic production of butyryl-CoA-derived designer esters from renewable feedstocks.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Enhancing chemical bioproduction with rational control of bacterial post-translational modifications

Efficient conversion of inexpensive feedstocks to valuable chemicals by microbes is critical for a robust bioeconomy, but the ability to rationally design bacteria is hampered by insufficient knowledge of how post translational modifications (PTMs) control bacterial protein function and thus bioproduction phenotypes. Our study will focus on the lysine acetylation, a ubiquitous bacterial PTM that can affect the function of enzymes in central metabolism that are often critical for bioproduction processes, disrupt transcriptional regulation, and reduce translation. However, most lysine acetylation data is observational, which means that we do not know when, how, and what specific acetylated residues affect protein function and bacterial physiology. For our model host, we will use a Pseudomonas putida strain that we previously engineered to convert lignocellulosic feedstocks into chemicals such as itaconic acid (ITA). With this strain, we use a dynamic two-stage bioproduction process in which ITA is produced during a non-growth associated production phase. Production is highest during growth stages when lysine acetylation is low in other organisms (early stationary phase) and stalls in conditions where acetylation is highest (late stationary phase). The switch from high to stalled ITA production is also correlated with an unexpected increase in acetate levels – the precursor to non-enzymatic lysine acetylation. As such, we predict that lysine acetylation plays a substantial role in regulating the metabolic pathways required for ITA production. We will develop a generalizable approach that combines high-throughput genetic screens and cutting-edge genome engineering with state-of-the-art proteomics, metabolomics, and genetic code expansion methods to identify and modulate lysine acetylation patterns in bacteria. Ultimately, these strategies aim to manipulate protein expression and acetylation patterns to enhance bioproduction phenotypes (e.g., sustained ITA production in late stationary phase).

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Developing Multi-Gene CRISPRa/I Programs to Accelerate DBTL Cycles in ABF Hosts Engineered for Chemical Production (CRADA 468)

Bacterial metabolism is comprised of large and complex gene networks that can produce valuable chemical products. Sophisticated organism engineering efforts are required to optimize production of high-value compounds from these networks. In principle, synthetic multi-gene transcriptional programs could be constructed to reengineer these networks for efficient industrial chemical production. In practice, however, our incomplete ability to understand and model the underlying networks, combined with our limited ability to predictably control the expression of multiple genes makes achieving this goal difficult. To overcome these challenges, we will combine new CRISPR-Cas multi-gene expression programs with computational modeling, machine learning, and multi-omics data to enhance the efficacy of design-build-test-learn (DBTL) cycles. For industrially promising microorganisms in early stages of development, creating technologies for rapidly engineering complex multi-gene programs could be transformative for accelerating data- and model-driven strain design. New CRISPR-Cas tools allow programmable gene activation (CRISPRa) or repression (CRISPRi) at multiple genes simultaneously, using the catalytically inactive Cas9 protein (dCas9) with guide RNAs that recognize DNA targets through predictable Watson-Crick base pairing. To enable accelerated DBTL cycles, we will combine these technologies with advanced Agile BioFoundry (ABF) capabilities for multi-omics data collection and machine learning. We will demonstrate the immediate applicability of these tools by rapidly improving the production of an industrial aromatic in multiple ABF organisms. We recently identified and optimized new transcriptional activators that can be linked to programmable CRISPR-Cas DNA binding domains to activate gene expression in E. coli. We can now use these CRISPRa tools as generalizable trans-acting regulators for combinatorial multi-gene expression tuning that can be easily transferred to new pathways and networks without additional genome engineering. We anticipate these tools will also transfer to new hosts. We have recently found that CRISPRa systems developed in E. coli can be readily ported to Pseudomonas putida, suggesting that multi-gene CRISPRa/i programs for diverse ABF organisms may be within reach.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

A Simulated Evaluation of Powder Flowability Through a Partially Obstructed Consumable in Blown Powder Directed Energy Deposition Systems

Abstract In the interest of continued industrialization of metal additive manufacturing in modern production environments, cost is often referenced as a primary deterrent to new adopters. Conventional economic models for additive systems, processes, and supply chains often focus on specific process applications with little generalizability, or they neglect significant costs associated with production such as machine maintenance and consumable part replacement. Compounding the latter issue are substantial knowledge gaps in consumable part wear characterization for additive and other convergent manufacturing systems. In coaxial blown powder directed energy deposition systems, gas atomized metal powder is wasted during material deposition at a rate that is partly dependent on present wear phenomena in a consumable nozzle housed in the cladding head assembly. The price and lead time required to replace the nozzle incentivizes its reuse even when visibly worn. Often this initiates a process quality decline in the form of underbuilt geometry and internal defects due to losses in powder catchment efficiency. While depositing H13 steel using a hybrid manufacturing machine tool equipped with such a deposition system, a unique partial clog with a bridge-like structure formed at the consumable nozzle exit when supporting argon gas flows failed mid-process. To further understand coaxial multi-phase powder flow in the event of support gas failure, a computational fluid dynamics simulation is tailored to relevant process parameters, H13 powder material profile, and machine operator observations collected after the incident. The resulting differences in powder flow compared to control gas flow parameters is presented and discussed. The powder flowability and performance of the clogged nozzle is then assessed by using an optical profilometer to extract the profile of the clog and recreate the clog geometry within the simulation environment. In past work this simulation has been experimentally validated for a 316L steel powder material profile and used specifically for analyzing powder stream geometry and catchment efficiency. After the initial powder flow characterization, the clog is removed, and the nozzle is reprofiled. After removing the obstructing clog, the newly unobstructed nozzle geometry, the original off the shelf nozzle geometry, and additional nozzle profiles exploring different consumable refurbishment strategies are reevaluated in the simulation. Powder catchment efficiency for all variant nozzle geometries and relevant flow variables are compared and discussed, along with potential mitigation strategies for optimizing powder flowability with worn consumables. This work expands on the known morphology of blown powder obstructions and wear defects present in consumable coaxial nozzles while discussing pragmatic simulation driven responses to unanticipated subsystem failure in hybrid manufacturing machining platforms.

DeWitte, Lisa↗

DOE OSTI2025

Interplay Between Stereochemically Active Lone Pair Repulsions, Sigma Hole Interactions, and Delocalized Redox Processes in Topochemical Fluoride‐Ion Insertion

Topochemical insertion/extraction of cations has emerged as a generalizable strategy for modulating the crystal and electronic structure of periodic solids. In contrast, strategies for topochemical anion insertion are poorly explored and fundamental principles for designing insertion hosts to accommodate anions remain scarce. Here, we observe reversible room-temperature fluoride-ion insertion within tunnels of Sn 2 TiO 4 defined by the stereochemical expression of Sn 5 s 2 lone pairs. X-ray scattering studies of fluoride-ion-insertion-induced crystal structure modulation and X-ray absorption/emission spectroscopy probes of electronic structure along with magnetic susceptibility measurements and first-principles calculations are used to decipher design principles underpinning reversible fluoride-ion insertion and bulk diffusion. Fluoride-ion insertion is enabled by a combination of a large, polarizable tunnel, delocalized redox at Ti─O─Sn centers, inherent repulsion between the fluoride-ion and Sn 5 s 2 electron lone pairs, and the formation of dative interactions between Sn-centered σ-holes and fluoride-ions, yielding a reversible capacity of 0.5 fluoride-ions per Sn 2 TiO 4 formula unit. Our results demonstrate that the complex interplay between dative interactions and stereochemically active lone pair repulsions is critical to defining the thermodynamics and kinetics controlling fluoride-ion insertion and diffusion. As such, the design of fluoride-ion insertion hosts for anion batteries requires site-selective modification to modulate lattice—ion interactions.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds

Abstract Quantifying the relative influence of factors and processes controlling riverine ecosystem function is essential to predicting future conditions under global change. Dissolved organic matter (DOM) is a fundamental component of riverine ecosystems that fuels microbial food webs, influences nutrient and light availability, and represents a significant carbon flux globally. The heterogeneous nature of DOM molecular composition and its propensity for interaction (i.e., functional diversity) can characterize riverine ecosystem function across spatiotemporal scales. To investigate fundamental drivers of DOM diversity, we collected seasonal water samples from 42 nested locations within five watersheds spanning multiple watershed sizes (~ 5 to 30,000 km 2 ) across the United States. Patterns in DOM molecular richness, aromaticity, relative abundance of N-containing formulas, and putative biochemical transformations derived from high-resolution mass spectrometry were assessed across gradients of explanatory variables associated with watershed characteristics (e.g., watershed area, water residence time, land cover). We found that putative biochemical transformations were more strongly related to explanatory variables across watersheds than common bulk DOM parameters and that watershed area, surface water residence time and derived Damköhler numbers representing DOM reactivity timescales were strong predictors of DOM diversity. The data also indicate that catchment-specific land cover factors can significantly influence DOM diversity in diverging directions. Overall, the results highlight the importance of considering water residence time and land cover when interpreting longitudinal patterns in DOM chemistry and the continued challenge of identifying generalizable drivers that are transferable across watershed and regional scales for application in Earth system models. This work also introduces a Findable Accessible Interoperable Reusable (FAIR) dataset (> 300 samples) to the community for future syntheses.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Selective Ion Enrichment and Charge Storage through Transport Hysteresis in Conical Nanopipettes

Greater selectivity and controls in the ion transport dynamics are essential in fields such as charge storage, separation, energy storage and conversion, neuromorphic computing and learning, electrochemistry, to name a few. Mechanistic insights into the intriguing hysteresis effects in the rectified electrokinetic transport through single conical nanopipettes are unveiled by combining time-resolved electroanalytical experiments with numeric simulation. Cations as counterions for surface charges are found to dominate not just the through-nanopore flux but also the hysteresis charges, that is, the net enriched or expelled charges during the transport process. Built on our earlier report on the through-nanopore ion flux dominated by counterions for surface charges, the “trapped ions” or hysteresis charges are analyzed herein. Cation selectivity is almost 100% in the hysteresis charges during the potential scans in low conductivity states driven by the combined applied and intrinsic surface electrical fields. Surprisingly, the cation selectivity in the total hysteresis charges remains high at 70–80% over a wide bulk concentration range in the high conductivity (HC) states, where higher ionic strength due to ion enrichment would decrease electrostatistic effects and thus ion selectivity. The retained high selectivity at HC is explained by the competition effects of electroosmotic flow against the co-ion migration. Furthermore, the respective cation and anion portions in the total hysteresis charges over a wide range of ionic strength and measurement conditions provide generalizable strategies for improvements in both transport throughput and selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Raspberry colloid-templated approach for the synthesis of palladium-based oxidation catalysts with enhanced hydrothermal stability and low-temperature activity

It is becoming increasingly urgent to develop and utilize novel, more efficient and stable materials for mobile and stationary emission control applications as the deleterious consequences of anthropogenic air pollution are becoming more evident and pressing. Tightening regulations, particularly related to automotive exhaust treatment, together with continued improvements in engine design, that result in lowering the engine operating temperatures and inadvertently lead to the release of an overwhelming proportion of pollutants during the cold start, present new challenges for materials design, specifically for oxidation catalysts. In particular, improvements in the low-temperature activity while maintaining catalyst stability at high temperatures are required from the next-generation catalyst. Typical catalysts for removal of pollutants from automotive exhaust streams incorporate platinum group metals (PGMs). They tend to be inefficient at low temperatures (below 250 °C), thus accounting for the cold start problem, yet sinter and lose their activity at high temperatures that are frequently encountered during catalyst operation. High PGM loadings are often employed to compensate for catalyst inefficiencies and fast degradation, ultimately resulting in high-cost catalytic converters. Here, we have developed a new approach for the design and formation of catalytic materials that allows for both significantly more efficient PGM incorporation and improved overall catalyst performance at reduced PGM loadings. The method provides control over the composition and geometry of the support through self-assembly of sacrificial composite template — “raspberry” polymeric colloids decorated with catalytic particles — accompanied by infiltration with metal-oxide precursor and subsequent removal of the colloids. This method simultaneously structures the porous network and organizes the catalytic particles within it. Uniquely, the resulting catalytic particles are partially embedded in the support matrix and partially exposed to the pore interior, producing catalytic sites that are both stable and accessible. Herein, the feasibility of this novel and versatile approach for automotive catalytic conversion is demonstrated: the studies include testing alumina-based raspberry-colloid-templated (RCT) catalysts containing Pd nanoparticles (RCT Pd/Al2O3) for oxidation of propane and carbon monoxide under simulated diesel exhaust conditions and hydrothermal aging at 800 °C for 50 h in the simulated stream. The RCT Pd/Al2O3 catalysts exhibit exceptional activity toward CO oxidation, reduced reaction onset temperature, and high stability to elevated temperatures (demonstrated through prolonged exposure to temperatures up to 950 °C) and reactive gas streams, without migration, sintering or loss of the precious metal NPs. Notably, the novel catalyst shows the same or slightly better performance than the commercial catalysts even when the PGM load is reduced by ~80 % compared to the commercial counterparts. These results provide confidence for the utilization of the RCT approach for the fabrication of robust nanostructured catalysts for next-generation, energy-efficient catalytic converters with improved performance at low and high temperatures and reduced costs. The RCT methodology is, in addition, highly generalizable, and can thus be applied for the design of a wide range of catalytic systems in the automotive sector and beyond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Using Best Basis Inventory Data to Direct Strategies for Real Time Monitoring of Hanford High Level Waste – 26226

The potential to accelerate the processing of low- and high-level tank waste by applying real-time monitoring (RTM) of chemical and physical properties has prompted research into the suitability of multiple analytical methods for that purpose. The broad variety of waste stream properties and the large number of analytes of interest (as evidenced by Waste Acceptance Criteria (WAC) and Process Control Limit (PCL) lists) lead to an overwhelming set of possible analytical scenarios. This report describes the use of Best Basis Inventory (BBI) data to find the most relevant analytical targets for the specific case of monitoring the blending of High Level Waste from multiple tanks prior to introduction into a vitrification facility. Campaigns for blending this waste to minimize the risk of exceeding WACs and PCLs have been proposed. However, the predicted compositions of the blended materials do not incorporate any uncertainties that may be associated with the representativeness of the waste layer samples or the laboratory analyses that generated the BBI data. Also, they do not include any uncertainty associated with the precision of collecting highly specific fractions of the layers during a blending campaign or any inhomogeneities that may exist in those layers. Monte Carlo methods are used to apply uncertainties to the compositions of the individual layers specified in the campaign recipes. The resulting variations in the compositions of the blended materials allow estimation of the risks of exceeding WACs and PCLs for each campaign. A critical subset of WACs/PCLs – NOx, NaK, AlFeZr, and S – are especially at risk of being exceeded in multiple campaigns. These analytes should be the focus of instrument development. We also have extracted the expected solid/supernate distribution for these analytes, which establishes important performance criteria for individual analytical methods. The BBI data also permits an understanding of the different chemical forms in which the analytes appear. Thus, the need to establish instrumental sensitivity to these forms can be gainfully addressed. Although concentrating on one specific application – the blending of tank waste - this approach should be generalizable for the analysis of other possible RTM applications for waste processing.

Lascola, Robert [Savannah River National Laborator↗

DOE OSTI2026

Site-Selective Modification of Lanthanum Oxychloride to Modulate Halide-Ion Conduction

Design principles for solid-state halide-ion conduction remain poorly defined despite the increasing importance of halide ions as charge carriers in a variety of energy storage and electrochemical computing technologies. Here, we employ a siteselective modification strategy in which aliovalent cations are preferentially introduced at the La 3+ crystallographic site of LaOCl in the 2c Wyckoff position, enabling controlled generation of chloride vacancies and modification of lattice dynamics to enhance chloride-ion conductivity. Aliovalent substitution of La 3+ with Mg 2+ , Ca 2+ , and Sr 2+ generates charge-compensating Cl vacancies while preserving the matlockite crystal structure. X-ray excited optical luminescence measurements with Dy 3+ as a reporter chromophore evidence vacancy-derived midgap electronic states and an extended energy range of radiation-less Auger electron emission corresponding to substantial modification of electronic structure and local electrostatic potentials. Ca alloying at 8−10 at. % increases the chloride-ion conductivity by three- to 4 orders of magnitude as compared to unalloyed LaOCl, whereas comparable amounts of Sr- and Mg-alloying in LaOCl imbue less pronounced conductivity enhancements. Temperature-dependent Raman spectroscopy measurements reveal that Ca- and Sr-alloying substantially soften the La−Cl sublattice and yield a more compliant crystal lattice that can deform to accommodate Cl-ion migration. Structure solutions derived from Rietveld refinements to powder Xray diffraction reveal larger O−La−Cl bond-angle deviations and enhanced out-of-plane cation displacements for Ca- and Sr-alloyed compositions as compared to Mg-alloyed LaOCl. Such local distortions enhance chloride-ion mobility by reshaping and flattening vacancy migration energy landscapes and by modulating lattice dynamics governing anion conduction. We further illustrate that coalloying of Ca with Mg and Sr induces a nonmonotonic conductivity−defect stoichiometry relationship that can be rationalized based on cooperative interactions. Together, these results establish site-selective aliovalent alloying of LaOCl as an effective route to halide-ion solid electrolytes and provide broadly generalizable design principles for site-selective modification to induce vacancy formation and lattice softening to engender facile anion transport

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗