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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Molecular dynamics simulations of uranyl and plutonyl cations in a task-specific ionic liquid

Ionic liquids (ILs) are a unique class of solvents with potential applications in advanced separation technologies relevant to the nuclear industry. ILs are salts with low melting points and a wide range of tunable physical properties, such as viscosity, hydrophobiciy, conductivity, and liquidus range. ILs have negligible vapor pressure, are often non-flammable, and can have high thermal stability and a wide electrochemical window, making them attractive for use in separations processes relevant to the nuclear industry. Metal salts generally have a low solubility in ILs; however, by incorporating new functional groups into the IL cation or anion that promote complexation with the metal, the solubility can be greatly increased. One such task-specific ionic liquid (TSIL) is 1-carboxy-N, N, N-trimethylglycine bis(trifluoromethylsulfonyl)imide ([Hbet][Tf 2 N]). Water, which is detrimental for electrochemical separations, is a common impurity in ILs and can coordinate with actinyl cations, particularly in ILs containing only weakly coordinating components. Understanding the behavior of actinides in TSIL/water mixtures on a molecular level is vital for designing improved separations processes. Classical molecular dynamics simulations of uranyl(VI) and plutonyl(VI) in 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][Tf 2 N]) with deprotonated Hbet (betaine) and water have been performed to understand the coordination and dynamics of the actinyl cations. We find that betaine is a much stronger ligand than water and prefers to coordinate the metal in a bidentate manner. Potential of mean force simulations yield a relative free energy for betaine coordination of approximately -120 to -90 kJ/mol in mixtures with water. As the amount of betaine coordinated to the actinide increases, the diffusion coefficient of the actinyl cation decreases. Moreover, the betaine ligand is able to bridge between two metal centers, resulting in dimeric complexes with actinide–actinide distances of ~5 Å. Potential of mean force simulations show that these structures are stable, with relative free energies of up to -40 kJ/mol. The crystal structure for [(UO 2 ) 2 (bet) 6 (H 2 O) 2 ][Tf 2 N] 4 shows that the betaine bridges between two uranium atoms to form dimeric complexes similar to those found in our simulations.

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

Elucidating the Reaction Pathways of Veratrylglycero-β-Guaiacyl Ether Degradation over Metal-Free Solid Acid Catalyst with Hydrogen

Efficient cleavage of β-O-4 bonds in lignin to high-yield aromatic compounds for the potential production of fuels and chemicals is vital for the economics of the modern biorefinery industry. This work is distinct in that a detailed mechanistic analysis of the reaction pathways of veratrylglycero-β-guaiacyl ether (VGE) catalyzed by transition-metal-free solid acid zeolite in aqueous conditions at high hydrogen pressure has been performed. VGE degradation produced high monomers yields (≈87 %), including guaiacol (48.2 %), 1-(3,4-dimethoxyphenyl)ethanol (10.3 %), 1-(3,4-dimethoxyphenyl)-2-propanol (6.1 %), 3,4-dimethoxyphenylpropanol (4.7 %), 3,4-dimethoxycinnamyl alcohol (4.1 %), and 1,2-dimethoxy-4-propylbenzene (2 %). The products were identified and confirmed by the in situ solid-state magic angle spinning (MAS) 13 C NMR spectroscopy in real-time conditions and the two-dimensional gas chromatography (GC×GC). A variety of products reveal the crucial role of hydrogen, water, and acid sites for heterolytic cleavage of the β-O-4 bond in VGE. Decarbonylation, hydrogenolysis, hydrogenation, and dehydration reaction pathways are proposed and further validated using first-principles calculations.

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

Data for Renewable Linear Alpha-Olefins by Base-Catalyzed Dehydration of Biologically-Derived Fatty Alcohols

Base catalysts were studied for the dehydration of fatty alcohols to linear alpha olefins (LAOs). For the gas phase dehydration of 1-octanol to 1-octene, 15% Cs/SiO2 catalyst was 56% selective at 10% conversion. Diluting a feed of C8, C10, and C14 fatty alcohols to 50% in undecane increased the selectivity to alpha olefins to 77–99%. 15% Cs/SiO2 was further investigated for the gas phase dehydration of a 4.2 g L−1 mixed C8–C14 fatty alcohol in tridecane feed and showed linear alpha olefin selectivities of 78–100% at initial conversions of 51–91% with the conversion lowering to 32–77% over 30 h. Catalytic activity was totally regenerated through calcination. A feed of biologically derived alcohols was produced with E. coli strain CM24 transformed with three plasmids (pBTRCk–pVHb–maACR, pACYC–pVHb–seFadBA, pTRC99A–pVHb–tdTER–fdh) which yielded a 5.5 g L−1 of C8–C14 fatty alcohol in tridecane. This biologically-derived feed was successfully dehydrated to linear alpha olefins over 15% Cs/SiO2 at selectivities of 60–100% with initial conversions of 35–75% which decreased to 22–55% over 30 h. Techno-economic analysis (TEA) of the integrated process for fatty alcohol production and subsequent dehydration to alpha olefins was conducted across the potential fermentation TRY (titer, rate, yield) landscape. Baseline fermentation performance resulted in a minimum product selling price (MPSP) double the market price for LAOs due to low titers and high costs associated with managing water and tridecane solvent flows through the system. However, targeted improvements in fermentation performance (e.g., achieving 40 g L−1 titer, 0.5 g L−1 h−1 productivity, 80% theoretical yield) can enable financially viable production of biologically derived LAOs.

Catalysis↗
DOE OSTI2021

Renewable linear alpha-olefins by base-catalyzed dehydration of biologically-derived fatty alcohols

In this work, base catalysts were studied for the dehydration of fatty alcohols to linear alpha olefins (LAOs). For the dehydration of 1-octanol to 1-octene, 15%Cs/SiO 2 catalyst was 56% selective at 10% conversion. Diluting a feed of C 8 , C 10 , and C 14 fatty alcohols to 50% in undecane increased the selectivity to alpha olefins to 77-99%. 15%Cs/SiO 2 was further investigated for the dehydration of a 4.2 g/L mixed C 8 -C 14 fatty alcohol in tridecane feed and showed linear alpha olefin selectivities of 78-100% at initial conversions of 51-91% with the conversion lowering to 32-77% over 30 h. Catalytic activity was totally regenerated through calcination. A feed of biologically derived alcohols was produced with E. coli strain CM24 transformed with three plasmids (pBTRCk – pVHb – maACR, pACYC – pVHb – seFadBA, pTRC99A – pVHb – tdTER – fdh) which yielded a 5.5 g/L of C 8 -C 14 fatty alcohol in tridecane. This biologically-derived feed was successfully dehydrated to linear alpha olefins over 15%Cs/SiO 2 at selectivities of 60-100% with initial conversions of 35-75% which decreased to 22-55% over 30 h. Techno-economic analysis (TEA) of the integrated process for fatty alcohol production and subsequent dehydration to alpha olefins was conducted across the potential fermentation TRY (titer, rate, yield) landscape. Baseline fermentation performance resulted in a minimum product selling price (MPSP) double the market price for LAOs due to low titers and high costs associated with managing water and tridecane solvent flows through the system. However, targeted improvements in fermentation performance (e.g., achieving 40 g/L titer, 0.5 g/L/h productivity, 80% theoretical yield) can enable financially viable production of biologically derived LAOs.

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

Nitrogen acquisition and retention pathways in sustainable perennial bioenergy grass cropping systems

Abstract Perennial tall grasses show promise as bioenergy crops due to high productivity and efficient nutrient use. Ongoing research on bioenergy grasses seeks to reduce their reliance on synthetic nitrogen (N) fertilizer, the manufacture of which relies on fossil fuel combustion. Excessive use of fertilizers also causes adverse environmental consequences and leads to the evolutionary loss of plant traits beneficial to sustainable N cycle. Notably, perennial tall grasses have exhibited the potential to maintain high biomass yield without the need for N fertilizer or causing soil N depletion. Perennial grasses can be adept at interacting with their microbial partners to facilitate N acquisition and retention via mechanisms such as biological N fixation and nitrification inhibition. These inherent N management traits should be preserved and optimized at the this early stage of bioenergy grass breeding programs. This review examines the impact of external N on bioenergy grass production and explores the potential of leveraging advantageous N‐cycling attributes of perennial tall grasses, laying groundwork for future management and research efforts. With minimized dependency on external N input, the cultivation of perennial energy grasses will pave the way toward more resilient agricultural systems and play a significant role in addressing key global energy and environmental challenges.

Agriculture↗
DOE OSTI2021

Airborne hyperspectral imaging of nitrogen deficiency on crop traits and yield of maize by machine learning and radiative transfer modeling

Nitrogen is an essential nutrient that directly affects plant photosynthesis, crop yield, and biomass production for bioenergy crops, but excessive application of nitrogen fertilizers can cause environmental degradation. To achieve sustainable nitrogen fertilizer management for precision agriculture, there is an urgent need for nondestructive and high spatial resolution monitoring of crop nitrogen and its allocation to photosynthetic proteins as that changes over time. Here, we used visible to shortwave infrared (400–2400 nm) airborne hyperspectral imaging with high spatial (0.5 m) and spectral (3–5 nm) resolutions to accurately estimate critical crop traits, i.e., nitrogen, chlorophyll, and photosynthetic capacity (CO 2 -saturated photosynthesis rate, V max,27 ), at leaf and canopy scales, and to assess nitrogen deficiency on crop yield. We conducted three airborne campaigns over a maize (Zea mays L.) field during the growing season of 2019. Physically based soil-canopy Radiative Transfer Modeling (RTM) and data-driven approaches i.e. Partial-Least Squares Regression (PLSR) were used to retrieve crop traits from hyperspectral reflectance, with ground truth of leaf nitrogen, chlorophyll, V max,27 , Leaf Area Index (LAI), and harvested grain yield. To improve computational efficiency of RTMs, Random Forest (RF) was used to mimic RTM simulations to generate machine learning surrogate models RTM-RF. The results show that prior knowledge of soil background and leaf angle distribution can significantly reduce the ill-posed RTM retrieval. RTM-RF achieved a high accuracy to predict leaf chlorophyll content (R 2 = 0.73) and LAI (R 2 = 0.75). Meanwhile, PLSR exhibited better accuracy to predict leaf chlorophyll content (R 2 = 0.79), nitrogen concentration (R 2 = 0.83), nitrogen content (R 2 = 0.77), and V max,27 (R 2 = 0.69) but required measured traits for model training. We also found that canopy structure signals can enhance the use of spectral data to predict nitrogen related photosynthetic traits, as combining RTM-RF LAI and PLSR leaf traits well predicted canopy-level traits (leaf traits × LAI) including canopy chlorophyll (R 2 = 0.80), nitrogen (R 2 = 0.85) and V max,27 (R 2 = 0.82). Compared to leaf traits, we further found that canopy-level photosynthetic traits, particularly canopy V max,27 , have higher correlation with maize grain yield. This study highlights the potential for synergistic use of process-based and data-driven approaches of hyperspectral imaging to quantify crop traits that facilitate precision agricultural management to secure food and bioenergy production.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Disinfection byproducts formed during drinking water treatment reveal an export control point for dissolved organic matter in a subalpine headwater stream

Changes in climate, season, and vegetation can alter organic export from watersheds. While an accepted tradeoff to protect public health, disinfection processes during drinking water treatment can adversely react with organic compounds to form disinfection byproducts (DBPs). By extension, DBP monitoring can yield insights into hydrobiogeochemical dynamics within watersheds and their implications for water resource management. In this study, we analyzed temporal trends from a water treatment facility that sources water from Coal Creek in Crested Butte, Colorado. These trends revealed a long-term increase in haloacetic acid and trihalomethane formation over the period of 2005-2020. Additionally, disproportionate export of dissolved organic carbon and formation of DBPs that exceeded regulatory guidelines were consistently recorded in association with late spring freshet. Synoptic sampling of the creek in 2020 and 2021 identified a biogeochemical hotspot for organic carbon export in the upper domain of the watershed that contained a prominent fulvic acid-like fluorescent signature. DBP formation potential analyses from this domain yielded similar ratios of dominant DBP species to those formed at the drinking water facility. Spectrometric qualitative analyses of pre and post-reacted waters with hypochlorite indicated ligninlike and condensed hydrocarbon-like molecules were the major reactive chemical classes during chlorine-based disinfection. This study demonstrates how drinking water quality archives can be coupled with synoptic sampling to identify and understand export control points for dissolved organic matter. Resultant understanding can be applied in water treatment and watershed management plans to improve drinking water quality sourced from analogous watersheds.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Early season prediction of within-field crop yield variability by assimilating CubeSat data into a crop model

Accurate early season predictions of crop yield at the within-field scale can be used to address a range of crop production, management, and precision agricultural challenges. While the remote sensing of within-field insights has been a research goal for many years, it is only recently that observations with the required spatio-temporal resolutions, together with efficient assimilation methods to integrate these into modeling frameworks, have become available to advance yield prediction efforts. Here we explore a yield prediction approach that combines daily high-resolution CubeSat imagery with the APSIM crop model. The approach employs APSIM to train a linear regression that relates simulated yield to simulated leaf area index (LAI). That relationship is then used to identify the optimal regression date at which the LAI provides the best prediction of yield: in this case, approximately 14 weeks prior to harvest. Instead of applying the regression on satellite imagery that is coincident, or closest to, the regression date, our method implements a particle filter that integrates CubeSat-based LAI into APSIM to provide end-of-season high-resolution (3 m) yield maps weeks before the optimal regression date. The approach is demonstrated on a rainfed maize field located in Nebraska, USA, where suitable collections of both imagery and in-situ data were available for assessment. The procedure does not require in-field data to calibrate the regression model, with results showing that even with a single assimilation step, it is possible to provide yield estimates with good accuracy up to 21 days before the optimal regression date. Yield spatial variability was reproduced reasonably well, with a strong correlation to independently collected measurements (R 2 = 0.73 and rRMSE = 12%). When the field averaged yield was compared, our approach reduced yield prediction error from 1 Mg/ha (control case based on a calibrated APSIM model), to 0.5 Mg/ha (using satellite imagery alone), and then to 0.2 Mg/ha (results with assimilation up to three weeks prior to the optimal regression date). Such a capacity to provide spatially explicit yield predictions early in the season has considerable potential to enhance digital agricultural goals and improve end-of-season yield predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Conceptual Design of a Thermal–to-14-MeV Neutron Conversion Device for Use in the Advanced Test Reactor

Here, this paper details the conceptual design of a thermal-to-14-MeV neutron converter consisting of a mixture of lithium and deuterium in a blanket material. Such a device operates a two-step reaction, first generating tritons via thermal neutron absorption in the tritium breeding material, and in the second step, high-energy neutrons are produced either via deuterium-tritium fusion reaction or with tritium reacting with lithium. A thermal-to-14-MeV neutron converter significantly hardens the neutron spectrum by virtually removing thermal neutrons and adding a high-energy 14 MeV component to the neutron spectrum. While similar concepts have been previously proposed and tested in other reactors, the unique characteristics of the Advanced Test Reactor (ATR), namely its important thermal flux (up to $10^{15}$ n.cm$^{-2}$.s$^{-1}$) makes it markedly attractive for obtaining a very large fast neutron flux, usable for irradiation studies under neutron flux conditions prototypical of fusion reactors. The paper provides a description of a new computational scheme developed for handling the coupled neutron-triton transport mechanism using the Geant4 toolkit. Resulting neutron spectra and high-energy neutron yields are summarized for different irradiation positions and potential neutron breeder materials. Maximum predicted thermal-to-14-MeV neutron yields are on the order of $2.10^{-4}$, which is consistent with previous studies found in the literature. Thus, when placed inside the ATR, such a neutron converter will be providing the largest high-energy neutron source available for activation and irradiation studies of materials foreseen for use in fusion reactors. Future steps will involve qualifying the computational scheme using the ATR critical facility using activation foil measurements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Uncertainty-quantified phenomenological optical potentials for single-nucleon scattering

Optical-model potentials (OMPs) continue to play a key role in nuclear reaction calculations. However, the uncertainty of phenomenological OMPs in widespread use—inherent to any parametric model trained on data—has not been fully characterized, and its impact on downstream users of OMPs remains unclear. Here we assign well-calibrated uncertainties for two representative global OMPs, those of Koning-Delaroche and Chapel Hill '89, using Markov-chain Monte Carlo for parameter inference. By comparing the canonical versions of these OMPs against the experimental data originally used to constrain them, we show how a lack of outlier rejection and a systematic underestimation of experimental uncertainties contributes to bias of, and overconfidence in, best-fit parameter values. Our updated, uncertainty-quantified versions of these OMPs address these issues and yield complete covariance information for potential parameters. Scattering predictions generated from our ensembles show improved performance both against the original training corpora of experimental data and against a new “test” corpus comprising many of the experimental single-nucleon scattering data collected over the last twenty years. Finally, we apply our uncertainty-quantified OMPs to two case studies of application-relevant cross sections. We conclude that, for many common applications of OMPs, including OMP uncertainty should become standard practice. Furthermore, to facilitate their immediate use, digital versions of our updated OMPs and related tools for forward uncertainty propagation are included as Supplemental Material.

150 ≤ A ≤ 189↗
DOE OSTI2024

Optimizing Selection Pressures and Pest Management to Maximize Cultivation Yield (OSPREY) (Final Technical Report)

This project was proposed in response to AOI 1, Cultivation Intensification Processes for Algae, within the FY19 Bioenergy Technologies Office Multi-Topic Funding Opportunity Announcement (FOA Number: DE-FOA-0002029). The work was designed to address a critical industry need to improve annualized productivity, stability, and quality of algal production strains for biofuels and bioproducts. The overall project goals were to generate process innovations rooted in established outdoor systems for strain selection, improvement, maintenance, and cultivation as well as pest detection and tracking. Planned advances included a 50% improvement in harvest yield based on AFDW (g m 2 d -1 ), 50% improvement in robustness based on stability metrics (e.g., high-productivity cultivation days, pond uptime), and 20% improvement in conversion yield. Individually, each of our planned process improvements (e.g., pest tracking) had the potential to increase productivity. However, to realize increases in yield at the system level, improvements to one unit’s process must be balanced against potential effects on other processes. For example, changes to strains, cultivation, and pest management developed in isolation may hurt other unit operations. Therefore, a critical success factor of the project was the integration of the pipeline components, achieved through iterative field-to- (short term) lab testing. In addition, through sustainability models, we evaluated how improvements would alter industry scenarios.

09 BIOMASS FUELS↗
DOE OSTI2022

An overview of magneto-inertial fusion on the Z Machine at Sandia National Laboratories

We present an overview of the magneto-inertial fusion (MIF) concept MagLIF (Magnetized Liner Inertial Fusion) pursued at Sandia National Laboratories and review some of the most prominent results since the initial experiments in 2013. In MagLIF, a centimeter-scale beryllium tube or "liner" is filled with a fusion fuel, axially pre-magnetized, laser pre-heated, and finally imploded using up to 20 MA from the Z machine. All of these elements are necessary to generate a thermonuclear plasma: laser preheating raises the initial temperature of the fuel, the electrical current implodes the liner and quasi-adiabatically compresses the fuel via the Lorentz force, and the axial magnetic field limits thermal conduction from the hot plasma to the cold liner walls during the implosion. MagLIF is the first MIF concept to demonstrate fusion relevant temperatures, significant fusion production (>10^13 primary DD neutron yield), and magnetic trapping of charged fusion particles. On a 60 MA next-generation pulsed-power machine, two-dimensional simulations suggest that MagLIF has the potential to generate multi-MJ yields with significant self-heating, a long-term goal of the US Stockpile Stewardship Program. At currents exceeding 65 MA, the high gains required for fusion energy could be achievable.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Distinct Bimetallic Cooperativity Among Water Reduction Catalysts Containing [Co III Co III ], [Ni II Ni II ], and [Zn II Zn II ] Cores

We report three binuclear species [LCo III 2 (μ-Pz) 2 ](ClO 4 ) 3 (1), [LNi II 2 (CH 3 OH) 2 Cl 2 ]ClO 4 (2), and [LZn II 2 Cl 2 ]PF 6 (3) supported by the deprotonated form of the ligand 2,6-bis[bis(2-pyridylmethyl) amino-methyl]-4-methylphenol were synthesized, structurally characterized as solids and in solution, and had their electrochemical and spectroscopic behavior established. Species 1–3 had their water reduction ability studied aiming to interrogate the possible cooperative catalytic activity between two neighboring metal centers. Species 1 and 2 reduced H 2 O to H 2 effectively at an applied potential of -1.6 V Ag/AgCl , yielding turnover numbers of 2,820 and 2,290, respectively, after 30 minutes. Species 3 lacked activity and was used as a negative control to eliminate the possibility of ligand-based catalysis. Pre- and post-catalytic data gave evidence of the molecular nature of the process within the timeframe of the experiments. Species 1 showed structural, rather than electronic cooperativity, while species 2 displayed no obvious cooperativity. DFT methods complemented the experimental results determining plausible mechanisms.

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

Enabling bifacial thin film devices by developing a back surface field using Cu x AlO y

Bifacial solar cells have the potential to increase the energy yield per unit area over traditional monofacial devices without significant added cost, driving $/kWh costs lower and accelerating the adoption of solar photovoltaics. However, the performance of bifacial thin film solar cells significantly lags that achieved by crystalline silicon cells. Here we incorporate wide bandgap Cu x AlO y as a back buffer layer for CdTe devices and achieve a backside illuminated device with high current density and high fill factor. Moreover, these values remain nearly constant even as the absorber layer thickness changes, indicating that a fully-depleted device is not required for efficient charge collection. We show that this response is indicative of a back surface field, albeit with a persistent high back surface recombination velocity. By managing electron reflection, we achieved a backside illumination conversion efficiency of 7.1% and bifaciality of 0.55 for a 3.3 µm CdTe device and 8.0% and 0.62 for a 2 µm device. Future improvements can be made by identifying and incorporating a passivation material that reduces the back surface recombination velocity.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Cumulative fission yields of short-lived fission products from 235 U and 239 Pu measured by HPGe gamma-ray spectroscopy

In this study, we present a preliminary investigation focused on determining cumulative fission yields for short-lived fission products. Our analysis involves examining gamma spectra from the irradiated samples of 235 U and 239 Pu using the High Flux Isotope Reactor. The motivation stems from the observed discrepancy in the antineutrino energy spectrum within the range of 5 to 7 MeV. While several hypotheses have been proposed, a thorough analysis of fission yields provides an additional way of gaining insight into this unexplained phenomenon. Our study suggests that the measured gamma rays from 100 Nb, 140 Cs and 95 Sr are consistent with the expected values. However, 93 Rb, 96 Y, 97 Y and 142 Cs cannot be quantified due to insufficient statistics, interference from other gamma rays and the Compton scattering background. Additionally, the calculated cumulative fission yields based on the measured 140 Cs and 95 Sr are found to be consistent with the JEFF3.3 fission yield library. In conclusion, the present work shows that the potential of improving gamma-ray spectroscopy in the fission yields as a means to improve our understanding of the antineutrino spectrum.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Prenol production in a microbial host via the “Repass” Pathways

Prenol and isoprenol are promising advanced biofuels and serve as biosynthetic precursors for pharmaceuticals, fragrances, and other industrially relevant compounds. Despite engineering improvements that circumvent intermediate cytotoxicity and lower energy barriers, achieving high titer ‘mevalonate (MVA)-derived’ prenol has remained elusive. Difficulty in selective prenol production stems from the necessary isomerization of isopentenyl diphosphate (IPP) to dimethylallyl diphosphate (DMAPP) as well as the intrinsic toxicity of these diphosphate precursors. Here, the expression of specific isopentenyl monophosphate kinases with model-guided enzyme substitution of diphosphate isomerases and phosphatases enabled selective cycling of monophosphates and diphosphates, dramatically improving prenol titers and selectivity in Escherichia coli. Pairing this approach with the canonical MVA pathway resulted in 300 mg/L prenol at a 30:1 ratio with isoprenol. Further pairing with the “IPP-Bypass” pathway resulted in 526 mg/L prenol at a 72:1 ratio with isoprenol, the highest and purest MVA-derived prenol titer to date. Additionally, modifying this “IPP-Repass” for DMAPP production and coexpressing the prenyltransferase acPT1 yielded 48.3 mg/L of the potential therapeutic precursor drupanin from p-coumarate. These novel repass pathways establish a unique strategy for tuning diphosphate precursors to drive isoprenoid biosynthesis and prenylation reactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Predictive Model of Charge Mobilities in Organic Semiconductor Small Molecules with Force-Matched Potentials

Charge mobility of crystalline organic semiconductors (OSC) is limited by local dynamic disorder. Recently, the charge mobility for several high mobility OSCs, including TIPS-pentacene, were accurately predicted from a density functional theory (DFT) simulation constrained by the crystal structure and the inelastic neutron scattering spectrum, which provide direct measures of the structure and the dynamic disorder in the length scale and energy range of interest. However, the computational expense required for calculating all of the atomic and molecular forces is prohibitive. In this work, we demonstrate the use of density functional tight binding (DFTB), a semiempirical quantum mechanical method that is 2 to 3 orders of magnitude more efficient than DFT. We show that force matching a many-body interaction potential to DFT derived forces yields highly accurate DFTB models capable of reproducing the low-frequency intricacies of experimental inelastic neutron scattering (INS) spectra and accurately predicting charge mobility. We subsequently predicted charge mobilities from our DFTB model of a number of previously unstudied structural analogues to TIPS-pentacene using dynamic disorder from DFTB and transient localization theory. The approach we establish here could provide a truly rapid simulation pathway for accurate materials properties prediction, in our vision applied to new OSCs with tailored properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗