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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Structural and Optical Response of Polymer-Stabilized Blue Phase Liquid Crystal Films to Volatile Organic Compounds

Engineering useful mechanical properties into stimuli-responsive soft materials without compromising their responsiveness is, in many cases, an unresolved challenge. For example, polymer networks formed within blue-phase liquid crystals (BPs) have been shown to form mechanically robust films, but the impact of polymer networks on the response of these soft materials to chemical stimuli has not been explored. In this work, we report on the response of polymer-stabilized BPs (PSBPs) to volatile organic compounds (VOCs, using toluene as a model compound) and compare the response to BPs without polymer stabilization and to polymerized nematic and cholesteric phases. We find that PSBPs generate an optical response to toluene vapor (change in reflection intensity under crossed polars) that is sixfold greater in sensitivity than the polymerized nematic or cholesteric phases and with a limit of detection (140 ± 10 ppm at 25 °C) that is relevant to the measurement of permissible exposure limits for humans. Additionally, when compared to BPs that have not been polymerized, PSBPs respond to a broader range of toluene vapor concentrations (5000 vs <1000 ppm) over a wider temperature interval (25–45 vs 45–53 °C). We place these experimental observations into the context of a simple thermodynamic model to explore how the PSBP response reflects the effect of toluene on competing contributions of double-twisted LC cylinders, disclinations, and polymer network to the free energy that controls the PSBP lattice spacing. Overall, we conclude that the mechanical and thermal stability of PSBPs, when combined with their optical responsiveness to toluene, make this class of self-supporting LCs a promising one as the basis of passive and compact (e.g., wearable) sensors for VOCs.

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

Artificial Neural Network Models for Octane Number and Octane Sensitivity: A Quantitative Structure Property Relationship Approach to Fuel Design

Octane sensitivity (OS), defined as the research octane number (RON) minus the motor octane number (MON) of a fuel, has gained interest among researchers due to its effect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially within advanced compression ignition engines. RON/MON must be experimentally tested to determine OS, requiring time, funding, and specialized equipment. Thus, predictive models trained with existing experimental data and molecular descriptors (via quantitative structure-property relationships (QSPRs)) would allow for the preemptive screening of compounds prior to performing these experiments. Here, the present work proposes two methods for predicting the OS of a given compound: using artificial neural networks (ANNs) trained with QSPR descriptors to predict RON and MON individually to compute OS (derived octane sensitivity (dOS)), and using ANNs trained with QSPR descriptors to directly predict OS. Twenty-five ANNs were trained for both RON and MON and their test sets achieved an overall 6.4% and 5.2% error, respectively. Twenty-five additional ANNs were trained for both dOS and OS; dOS calculations were found to have 15.3% error while predicting OS directly resulted in 9.9% error. A chemical analysis of the top QSPR descriptors for RON/MON and OS is conducted, highlighting desirable structural features for high-performing molecules and offering insight into the inner mathematical workings of ANNs; such chemical interpretations study the interconnections between structural features, descriptors, and fuel performance showing that connectivity, structural diversity, and atomic hybridization consistently drive fuel performance.

09 BIOMASS FUELS↗
DOE OSTI2020

Prediction of Research/Motor Octane Number and Octane Sensitivity Using Artificial Neural Networks

Octane sensitivity (OS), dfined as the research octane number (RON) minus the motor octane number (MON) of a given fuel, has gained interest among researchers due to its apparent ffect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially with respect to advanced compression ignition engines. RON/MON must be experimentally tested to determine OS; however, the experimental methods utilized require a substantial amount of time, a significant monetary investment, and specialized equipment. To this end, predictive computational models trained with existing experimental data and molecular properties would allow for the preemptive screening of compounds prior to performing these experiments. The present work proposes two methods for predicting the OS of a given compound: using artficial neural networks (ANNs) trained with quantitative structure-property relationship (QSPR) descriptors to predict RON and MON individually to compute OS from RON/MON predictions (derived octane sensitivity, dOS), and using an ANN trained with QSPR descriptors to directly predict OS. ANNs trained to predict RON and MON achieved test set root-mean-square errors (RMSEs) of 10.499 and 7.551 respectively. dOS calculations were found to have a test set RMSE of 6.432 while predicting OS directly resulted in a test set RMSE of 7.019, showing it is more bene cial to obtain OS from RON/MON predictions than predicting it directly. Furthermore, relationships between individual QSPR descriptors and RON/MON/OS are discussed, highlighting correlations between specfic molecular features and these properties.

09 BIOMASS FUELS↗
DOE OSTI2025

Wide-ranging predictions of new stable compounds powered by recommendation engines

The computational search for new stable inorganic compounds is faster than ever, thanks to high-throughput density functional theory (DFT). However, stable compound searches remain highly expensive because of the enormous search space and the cost of DFT calculations. To aid these searches, recommendation engines have been developed. We conduct a systematic comparison of the performance of previously developed recommendation engines, specifically ones based on elemental substitution, data mining, and neural network prediction of formation enthalpy. After identifying ways to improve the recommendation engines, we find the neural network to be superior at recommending stable Heusler compounds. Armed with improved recommendation engines, we identify tens of thousands of compounds that are stable at zero temperature and pressure, now available in the Open Quantum Materials Database. We summarize this diverse pool of compounds, including the elusive mixed anion compounds, and two of their many applications: thermoelectricity and solar thermochemical fuel production.

Science & Technology - Other Topics↗
DOE OSTI2021

Advances in engineering microbial biosynthesis of aromatic compounds and related compounds

Abstract Aromatic compounds have broad applications and have been the target of biosynthetic processes for several decades. New biomolecular engineering strategies have been applied to improve production of aromatic compounds in recent years, some of which are expected to set the stage for the next wave of innovations. Here, we will briefly complement existing reviews on microbial production of aromatic compounds by focusing on a few recent trends where considerable work has been performed in the last 5 years. The trends we highlight are pathway modularization and compartmentalization, microbial co-culturing, non-traditional host engineering, aromatic polymer feedstock utilization, engineered ring cleavage, aldehyde stabilization, and biosynthesis of non-standard amino acids. Throughout this review article, we will also touch on unmet opportunities that future research could address.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Accelerating polyketide synthase engineering for high TRY production of biofuels and bioproducts (Final Technical Report)

Polyketide synthase (PKS) enzymes have a modular, deterministic logic that holds the potential to act as a flexible chemical factory for the biological production of a huge diversity of valuable small molecule compounds. However, engineering a custom PKS to produce a specific desired product currently requires years of trial and error, for reasons that remain poorly understood. In this project, we have developed a rapid, high throughput, Design-Build-Test-Learn (DBTL) cycle for polyketide synthases (PKSs) and demonstrate its utility for production of materials precursors. The objectives are 1) to develop a rapid, high-throughput (HT) DBTL cycle for PKSs that will enable production of a large number of unnatural, organic molecules on demand at high titer, rate, and yield (TRY); 2) to demonstrate the utility of the PKS DBTL cycle to produce three molecules: one commodity chemical (caprolactam or valerolactam) and two novel materials precursors (caprolactam or valerolactam derivatives); and 3) to demonstrate the utility of the PKS DBTL cycle to increase the TRY of one molecule (caprolactam or valerolactam). In this project, we have successfully demonstrated our high throughput PKS DBTL pipeline, and have biologically produced valerolactam and several other novel nylon monomers.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Accelerating polyketide synthase engineering for high TRY production of biofuels and bioproducts (CRADA Final Report)

Polyketide synthase (PKS) enzymes have a modular, deterministic logic that holds the potential to act as a flexible chemical factory for the biological production of a huge diversity of valuable small molecule compounds. However, engineering a custom PKS to produce a specific desired product currently requires years of trial and error, for reasons that remain poorly understood. In this project, we have developed a rapid, high throughput, Design-Build-Test-Learn (DBTL) cycle for polyketide synthases (PKSs) and demonstrate its utility for production of materials precursors. The objectives are 1) to develop a rapid, high-throughput (HT) DBTL cycle for PKSs that will enable production of a large number of unnatural, organic molecules on demand at high titer, rate, and yield (TRY); 2) to demonstrate the utility of the PKS DBTL cycle to produce three molecules: one commodity chemical (caprolactam or valerolactam) and two novel materials precursors (caprolactam or valerolactam derivatives); and 3) to demonstrate the utility of the PKS DBTL cycle to increase the TRY of one molecule (caprolactam or valerolactam). In this project, we have successfully demonstrated our high throughput PKS DBTL pipeline, and have biologically produced valerolactam and several other novel nylon monomers.

09 BIOMASS FUELS↗
DOE OSTI2021

A Hybrid Heavy-Duty Diesel Power System for Off-Road Applications - Concept Definition

A multi-year Power System R&D project was initiated with the objective of developing an off-road hybrid heavy-duty concept diesel engine with front end accessory drive-integrated energy storage. This off-road hybrid engine system is expected to deliver 15-20% reduction in fuel consumption over current Tier 4 Final-based diesel engines and consists of a downsized heavy-duty diesel engine containing advanced combustion technologies, capable of elevated peak cylinder pressures and thermal efficiencies, exhaust waste heat recovery via SuperTurbo™ turbocompounding, and hybrid energy recovery through both mechanical (high speed flywheel) and electrical systems. The first year of this project focused on the definition of the hybrid elements using extensive dynamic system simulation over transient work cycles, with hybrid supervisory controls development focusing on energy recovery and transient load assist, in Caterpillar’s DYNASTY™ software environment. Three key off-road applications were the focus of the hybrid concept definition with an aim of understanding the system’s modular capability for the diverse off-road heavy-duty market. Core engine performance 1D and 3D simulations isolated the efficiency contributions from the downsized engine, turbocompounding, and in-cylinder thermal barrier coatings. A fuel consumption improvement range of 14 to 24% was predicted, resulting in successful project progression to the design and experimental validation phase. Furthermore, an overview of the experimental engine and hybrid system status concludes the discussion along with the multi-year project’s next steps.

33 ADVANCED PROPULSION SYSTEMS↗
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 OSTI2022

Engineered microbes for conversion of organic compounds to medium chain length alcohols and methods of use

This disclosure provides a genetically-modified bacterium from the genus Pseudomonas that comprises an exogenous nucleic acid encoding an enoyl-CoA reductase and an exogenous nucleic acid encoding an acyl-CoA reductase that produces medium chain length alcohols. The disclosure further provides methods for producing medium chain alcohols using such genetically-modified bacterium. This disclosure provides a renewable, bio-based production platform for valuable mcl-alcohols that have a wide range of industrial applications. Current production of mcl-alcohols typically occurs through the hydrogenation of plant oils and waxes. This process leads to issues of deforestation and is largely unsustainable. Utilizing waste lignin streams as the carbon source provides a more sustainable feedstock that can be generated from plant waste like corn stover. Along with this, the use of lignin avoids competition with food resources as traditional starch and sugar feedstocks.

Guss, Adam M.↗
DOE OSTI2023

Advances in S. cerevisiae Engineering for Xylose Fermentation and Biofuel Production: Balancing Growth, Metabolism, and Defense

Genetically engineering microorganisms to produce chemicals has changed the industrialized world. The budding yeast Saccharomyces cerevisiae is frequently used in industry due to its genetic tractability and unique metabolic capabilities. S. cerevisiae has been engineered to produce novel compounds from diverse sugars found in lignocellulosic biomass, including pentose sugars, like xylose, not recognized by the organism. Engineering high flux toward novel compounds has proved to be more challenging than anticipated since simply introducing pathway components is often not enough. Several studies show that the rewiring of upstream signaling is required to direct products toward pathways of interest, but doing so can diminish stress tolerance, which is important in industrial conditions. As an example of these challenges, we reviewed S. cerevisiae engineering efforts, enabling anaerobic xylose fermentation as a model system and showcasing the regulatory interplay’s controlling growth, metabolism, and stress defense. Enabling xylose fermentation in S. cerevisiae requires the introduction of several key metabolic enzymes but also regulatory rewiring of three signaling pathways at the intersection of the growth and stress defense responses: the RAS/PKA, Snf1, and high osmolarity glycerol (HOG) pathways. The current studies reviewed here suggest the modulation of global signaling pathways should be adopted into biorefinery microbial engineering pipelines to increase efficient product yields.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Fuel and fuel blend for internal combustion engine

A fuel or fuel blending agent for an internal combustion engine includes a ketone compound that is a C 4 to C 10 branched acyclic ketone, cyclopentanone, or a derivative of cyclopentanone. The ketone compound may be blended with a majority portion of a fuel selected from the group consisting of: gasoline, diesel, alcohol fuel, biofuel, renewable fuel, Fischer-Tropsch fuel, or combinations thereof. The ketone compound may be derived from biological sources. A method for powering an internal combustion engine with a fuel comprising the ketone compound is also provided.

Dec, John E.↗
DOE OSTI2023

Fuel and fuel blend for internal combustion engine

A fuel or fuel blending agent for an internal combustion engine includes a ketone compound that is a C 4 to C 10 branched acyclic ketone, cyclopentanone, or a derivative of cyclopentanone. The ketone compound may be blended with a majority portion of a fuel selected from the group consisting of: gasoline, diesel, alcohol fuel, biofuel, renewable fuel, Fischer-Tropsch fuel, or combinations thereof. The ketone compound may be derived from biological sources. A method for powering an internal combustion engine with a fuel comprising the ketone compound is also provided.

Dec, John E.↗
DOE OSTI2023

Engineering Nannochloropsis oceanica for the production of diterpenoid compounds

Abstract Photosynthetic microalgae like Nannochloropsis hold enormous potential as sustainable, light‐driven biofactories for the production of high‐value natural products such as terpenoids. Nannochloropsis oceanica is distinguished as a particularly robust host with extensive genomic and transgenic resources available. Its capacity to grow in wastewater, brackish, and sea waters, coupled with advances in microalgal metabolic engineering, genome editing, and synthetic biology, provides an excellent opportunity. In the present work, we demonstrate how N. oceanica can be engineered to produce the diterpene casbene—an important intermediate in the biosynthesis of pharmacologically relevant macrocyclic diterpenoids. Casbene accumulated after stably expressing and targeting the casbene synthase from Daphne genkwa (DgTPS1) to the algal chloroplast. The engineered strains yielded production titers of up to 0.12 mg g −1 total dry cell weight (DCW) casbene. Heterologous overexpression and chloroplast targeting of two upstream rate‐limiting enzymes in the 2‐C‐methyl‐ d ‐erythritol 4‐phosphate pathway, Coleus forskohlii 1‐deoxy‐ d ‐xylulose‐5‐phosphate synthase and geranylgeranyl diphosphate synthase genes, further enhanced the yield of casbene to a titer up to 1.80 mg g −1 DCW. The results presented here form a basis for further development and production of complex plant diterpenoids in microalgae.

Du, Zhi‐Yan↗
DOE OSTI2021

Multitude Characterization and Prediction of DOE Advanced Biofuels Properties

Advanced multitude of experiments ranging from the liquid fuel to combustion are conducted on Co-OPTIMA fuels to aid the characterization of the fuels. The series of targeted experiments characterized Co-OPTIMA fuel spray atomization, flame topology, flame speed, autoignition, volatility, viscosity, soot/coking, and compatibility. The fuels are selected and prioritized based on input from national lab members. The research characterized and predicted biomass-based, low greenhouse gas fuels and blends combustion, autoignition, and physical properties of mixtures of identified compounds at engine-relevant conditions, in particular those properties that blend non-linearly. The main challenge of Co-OPTIMA is the evaluation of a variety of biofuels and blends in all the reaction conditions that might be encountered in new high-efficiency engines. Despite the improved high-throughput experimental techniques, it seems unlikely that all of the performance metrics could be measured for all relevant petroleum derived, bio-derived molecules and mixtures, and reaction conditions. A series of targeted experiments ranging from the liquid fuel to the combustion process is required, and to extract the maximum information from each experiment. These targeted experiments evaluated how a specific fuel will perform in an engine. The series of targeted experiments are as follows: (a) Spray Atomization, Vaporization and Droplet Formation (b) Combustion Flame and Local Fuel/Air Image-Based Measurements (c) Laminar Flame Speed Measurements (d) Autoignition and Soot Measurements (e) Synchrotron Coupled Fundamental Autoignition Experiments (f) Fuel Coking and Hot Surface Deposit g) Fuel Volatility Measurements (h) Viscosity Measurements (i) Seal Flexible Fuel Compatibility These experimental processes provide an essential pathway for the prediction of fuel behaviors in engines and systematic process for fuel down select.

09 BIOMASS FUELS↗
DOE OSTI2025

Oxidative Funneling of PVDC (CRADA Final Report)

Poly(vinylidene chloride) (PVDC) is a major polymer product from the Participant. PVDC-containing plastics are not commonly recycled. To overcome the challenges associated with recycling PVDC and multi-layer materials, we propose a tandem catalytic-biological process to convert PVDC containing waste to upcycled, tunable products such as polyhydroxyalkanoates (PHAs). PHAs are commercially relevant, biodegradable polymers that are useful in packaging, biomedical, and personal care applications. This technology, which the Contractor has named oxidative funneling (OxFun), uses a metal-promoted autoxidation step to depolymerize co-mingled polymers to a mixture of oxygenated compounds, which an engineered bacterium can funnel to a single bioproduct: here, medium chain length polyhydroxyalkanoates (mcl-PHAs). The proposed oxidation chemistry is amenable to inclusion of additional polymers, and the biocatalyst can be engineered to convert the deconstruction products to a variety of valuable chemicals, thus presenting a tunable system for both feedstock variability and target product. Pseudomonas putida KT2440 – a metabolically robust microbe that has been engineered and proven viable for upcycling deconstructed polystyrene (PS), high density polyethlene (HDPE), and polyethylene terephthalate (PET) – can be engineered with enzymes capable of de-chlorinating PVDC deconstruction products (e.g., 2,2-dichloroacetate) in addition to PE-derived substrates into mcl-PHAs.

36 MATERIALS SCIENCE↗