Search NASA⌕ Search

SEARCH · Search NASA

Results for “Inorganic green chemistry”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Improved Fast Randomized Iteration Approach to Full Configuration Interaction

In this work, we present three modifications to our recently introduced fast randomized iteration method for full configuration interaction (FCI-FRI) and investigate their effects on the method’s performance for Ne, H 2 O, and N 2 . The initiator approximation, originally developed for full configuration interaction quantum Monte Carlo, significantly reduces statistical error in FCI-FRI when few samples are used in compression operations, enabling its application to larger chemical systems. The semistochastic extension, which involves exactly preserving a fixed subset of elements in each compression, improves statistical efficiency in some cases but reduces it in others. We also developed a new approach to sampling excitations that yields consistent improvements in statistical efficiency and reductions in computational cost. We discuss possible strategies based on our findings for improving the performance of stochastic quantum chemistry methods more generally.

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

Reactants, products, and transition states of elementary chemical reactions based on quantum chemistry

Reaction times, activation energies, branching ratios, yields, and many other quantitative attributes are important for precise organic syntheses and generating detailed reaction mechanisms. Often, it would be useful to be able to classify proposed reactions as fast or slow. However, quantitative chemical reaction data, especially for atom-mapped reactions, are difficult to find in existing databases. Therefore, we used automated potential energy surface exploration to generate 12,000 organic reactions involving H, C, N, and O atoms calculated at the ω B97X-D3/def2-TZVP quantum chemistry level. We report the results of geometry optimizations and frequency calculations for reactants, products, and transition states of all reactions. Additionally, we extracted atom-mapped reaction SMILES, activation energies, and enthalpies of reaction. We believe that this data will accelerate progress in automated methods for organic synthesis and reaction mechanism generation—for example, by enabling the development of novel machine learning models for quantitative reaction prediction.

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

Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation

In chemical kinetics research, kinetic models containing hundreds of species and tens of thousands of elementary reactions are commonly used to understand and predict the behavior of reactive chemical systems. Reaction Mechanism Generator (RMG) is a software suite developed to automatically generate such models by incorporating and extrapolating from a database of known thermochemical and kinetic parameters. Here, we present the recent version 3 release of RMG and highlight improvements since the previously published description of RMG v1.0. Most notably, RMG can now generate heterogeneous catalysis models in addition to the previously available gas- and liquid-phase capabilities. For model analysis, new methods for local and global uncertainty analysis have been implemented to supplement first-order sensitivity analysis. The RMG database of thermochemical and kinetic parameters has been significantly expanded to cover more types of chemistry. The present release includes parallelization for faster model generation and a new molecule isomorphism approach to improve computational performance. RMG has also been updated to use Python 3, ensuring compatibility with the latest cheminformatics and machine learning packages. Overall, RMG v3.0 includes many changes which improve the accuracy of the generated chemical mechanisms and allow for exploration of a wider range of chemical systems.

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

Oxidation and pyrolysis of methyl propyl ether

The ignition, oxidation, and pyrolysis chemistry of methyl propyl ether (MPE) was probed experimentally at several different conditions, and a comprehensive chemical kinetic model was constructed to help understand the observations, with many of the key parameters computed using quantum chemistry and transition state theory. Experiments were carried out in a shock tube measuring time variation of CO concentrations, in a flow tube measuring product concentrations, and in a rapid compression machine (RCM) measuring ignition delay times. The detailed reaction mechanism was constructed using the Reaction Mechanism Generator software. Sensitivity and flux analyses were used to identify key rate and thermochemical parameters, which were then computed using quantum chemistry to improve the mechanism. Validation of the final model against the 1-20 bar 600-1500 K experimental data is presented with a discussion of the kinetics. The model is in excellent agreement with most of the shock tube and RCM data. Strong non-monotonic variation in conversion and product distribution is observed in the flow-tube experiments as the temperature is increased, and unusually strong pressure dependence and significant heat release during the compression stroke is observed in the RCM experiments. These observations are largely explained by a close competition between radical decomposition and addition to O2 at different sites in MPE; this causes small shifts in conditions to lead to big shifts in the dominant reaction pathways. The validated mechanism was used to study the chemistry occurring during ignition in a diesel engine, simulated using Ignition Quality Test (IQT) conditions. At the IQT conditions, where the MPE concentration is higher, bimolecular reactions of peroxy radicals are much more important than in the RCM.

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

Automated reaction kinetics and network exploration (Arkane): A statistical mechanics, thermodynamics, transition state theory, and master equation software

The open-source statistical mechanics software described here, Arkane–Automated Reaction Kinetics and Network Exploration–facilitates computations of thermodynamic properties of chemical species, high-pressure limit reaction rate coefficients, and pressure-dependent rate coefficient over multi-well molecular potential energy surfaces (PES) including the effects of collisional energy transfer on phenomenological kinetics. Arkane can use estimates to fill in information for molecules or reactions where quantum chemistry information is missing. The software solves the internal energy master equation for complex unimolecular reaction systems. Inputs to the software include converged electronic structure computations performed by the user using a variety of supported software packages (Gaussian, Molpro, Orca, TeraChem, Q-Chem, Psi4). The software outputs high-pressure limit rate coefficients and pressure-dependent phenomenological rate coefficients, as well as computed thermodynamic properties (enthalpy, entropy, and constant pressure heat capacity) with added energy corrections. Some of the key features of Arkane include treatment of 1D, 2D or ND hindered internal rotation modes, treatment of free internal rotation modes, quantum tunneling effect consideration, transition state theory (TST) and Rice-Ramsperger-Kassel-Marcus (RRKM) rate coefficient computations, master equation solution with four implemented methods, inverse-Laplace transform of high-pressure limit rate coefficients into the energy domain, energy corrections based on bond-additivity or isodesmic reactions, automated and efficient PES exploration, and PES sensitivity analysis. The present work describes the design of Arkane, how it should be used, and refers to the theory that it employs. Arkane is distributed via the RMG-Py software suite (https://github.com/ReactionMechanismGenerator/RMG-Py).

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

Engineering Enzymes for Environmental Sustainability

The development and implementation of more efficient and sustainable technologies is key to delivering our net–zero targets. Here we review how engineered enzymes, with a focus on those developed using directed evolution, can be deployed to improve the sustainability of numerous processes and help to conserve our environment. Efficient and robust biocatalysts have been engineered to capture carbon dioxide (CO2) and have been embedded into new efficient metabolic CO2 fixation pathways. Enzymes have been refined for bioremediation, enhancing their ability to degrade toxic and harmful pollutants. Biocatalytic recycling is gaining momentum, with engineered cutinases and PETases developed for the depolymerization of the abundant plastic, PET. Finally, biocatalytic approaches for accessing petroleum–based feedstocks and chemicals are expanding, using optimized enzymes to convert plant biomass into biofuels or other high value products. Finally, through these examples, we hope to illustrate how enzyme engineering and biocatalysis can contribute to the development of more environmentally sustainable approaches, in order to protect our planet.

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

Probing the potential of type V Deep eutectic solvents as sustainable electrolytes

The increasing interest within the scientific community in environmentally friendly solvents has led to a focus on Deep Eutectic Solvents (DES), which have natural components. DES are viewed as alternatives to traditional organic solvents and have the potential to be used as electrolytes. For the first time, transport properties of four Type V Deep Eutectic Salt Solutions (DESS) were accessed to investigate the potential of this technology, selecting precursors ranked as excellent in Eco-Scale metrics. The DESS were composed of terpene and trioctylphosphine oxide (TOPO), and varying concentrations of lithium bis(trifluoromethane)sulfonimide (LiTFSI), and their properties were assessed through self-diffusion, viscosity, density, and conductivity measurements. While Type V DESS are capable of dissolving significant amounts of LiTFSI (up to 30 % molar), their ionic conductivity is low, with values ranging from 3.6·10 –3 to 9.3·10 –2 mS·cm –1 at 25 °C, thus limiting their suitability as electrolytes, for instance, for lithium-ions batteries applications. Similar diffusion coefficients for Li + and TFSI – ions suggest the formation of long-lived ion pairs moving as a neutral species. As a result, future research aims to introduce additives to disrupt contact ion pairs and enhance transport properties, leveraging the sustainable appeal of DES and their use in advanced energy storage technologies.

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

Synthesis and thermomechanical characteristics of zwitterionic poly(arylene ether sulfone) copolymers

Charge-containing polymeric materials have been widely studied for a range of applications. The fundamental relationships between the charge species, charge density, and the microscale morphology of charge-containing polymers are critical for defining the application in which they may be used. In this work, a series of thermoplastic poly(arylene ether sulfone) (PAES) copolymers with controllable sulfobetaine charge contents (0~100 mol%) and high molecular weights (Mw ~ 65 kDa) were prepared. All the zwitterionic PAESs synthesized showed thermal stability up to 250 °C. DSC and tensile tests showed a decreased T g and mechanical strength with the incorporation of increasing charge density, which suggests a plasticization effect by the charged group. Electron microscopy and X-ray scattering data confirmed the absence of microphase separation in the ion-containing random copolymer system, which corroborated with the observation of a single T g for all zwitterionic copolymers studied. Furthermore, the relative hydrophilicity of the samples was evaluated by water uptake measurements, which revealed that the water uptake of the zwitterionic PAESs can reach up to 64% for the 72 mol% zwitterion copolymer while the free-standing film in the wet state still maintains a Young's modulus of 185 MPa. Here, the thermoplastic charge-containing copolymers in this work demonstrated potential for applications such as coatings or water purification membranes, in which balancing hydrophilicity, processibility, and thermomechanical performance are important.

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

Harnessing biological applications of quantum materials: opportunities and precautions

Since the discovery of graphene, research on two-dimensional (2D) quantum materials has generated a plethora of novel materials with the potential to significantly change our lives. Owing to their unique quantum, electronic, and excitonic properties, biosensing and bio-imaging are two specific areas where these quantum materials have started to make a large impact. This article provides a holistic overview into the properties, synthesis methods, biological applications, and toxicology studies of commonly studied quantum materials. Recent research into the biological applications of graphene and transition metal dichalcogenides is highlighted and their unique electronic properties are explored. Though tremendous research is generated in discovering new 2D materials, toxicology studies in the area are lacking. Historically, toxicology studies have lagged significantly behind new material discovery often with dire consequences. The product development cycle of polymeric materials is a testament to the negative consequences of having a reactionary approach to toxicology. With 2D materials set to become a widespread part of everyday life in the near future, we comment on the need for a proactive approach to examining and understanding their toxicology.

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

Covalently integrated silica nanoparticles in poly(ethylene glycol)-based acrylate resins: thermomechanical, swelling, and morphological behavior

Nanocomposites integrate functional nanofillers into viscoelastic matrices for electronics, lightweight structural materials, and tissue engineering. Herein, the effect of methacrylate-functionalized (MA-SiO 2 ) and vinyl-functionalized (V-SiO 2 ) silica nanoparticles on the thermal, mechanical, physical, and morphological characteristics of poly(ethylene glycol) (PEG) nanocomposites was investigated. The gel fraction of V-SiO 2 composites decreases upon addition of 3.8 wt% but increases with further addition (>7.4 wt%) until it reaches a plateau at 10.7 wt%. The MA-SiO 2 induced no significant changes in gel fraction and both V-SiO 2 and MA-SiO 2 nanoparticles had a negligible impact on the nanocomposite glass transition temperature and water absorption. The Young's modulus and ultimate compressive stress increased with increasing nanoparticle concentration for both nanoparticles. Due to the higher crosslink density, MA-SiO 2 composites reached a maximum mechanical stress at a concentration of 7.4 wt%, while V-SiO 2 composites reached a maximum at a concentration of 10.7 wt%. Scanning electron microscopy, transmission electron microscopy, and small-angle X-ray scattering revealed a bimodal size distribution for V-SiO 2 and a monomodal size distribution for MA-SiO 2 . Although aggregates were observed for both nanoparticle surface treatments, V-SiO 2 dispersion was poor while MA-SiO 2 were generally well-dispersed. Finally, these findings lay the framework for silica nanofillers in PEG-based nanocomposites for advanced manufacturing applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Thermodynamically leveraged solventless aerobic deconstruction of polyethylene-terephthalate plastics over a single-site molybdenum-dioxo catalyst

Here, we describe the solventless catalytic deconstruction of polyethylene-terephthalate (PET) under an aerobic atmosphere, mediated by an earth-abundant, low-cost activated carbon (AC)-supported single-site molybdenum-dioxo catalyst (AC/MoO 2 ). Catalytic amounts of AC/MoO 2 selectively convert waste PET into its monomer, terephthalic acid (TPA), within 4 h at 265 °C with yields as high as 94% under 1 atm air. Pure crystalline TPA product sublimes from the reaction hot zone, crystallizing on the reactor cold zone, thus avoiding the need for separation and purification steps. This process does not employ any hazardous/toxic reducing agents or solvents, and the catalyst can be recycled multiple times without loss of activity, rendering this process highly atom-efficient. According to computational and experimental mechanistic studies, the AC/MoO 2 catalyst mediates a thermoneutral metal-catalyzed β-scission step, followed by an exothermic step that converts the vinyl benzoate intermediate to TPA and acetaldehyde using trace amounts of moisture in the air. The formation of gaseous acetaldehyde makes the isolation of TPA from the reaction mixture facile and industrially favorable, especially since solvents are unnecessary. The present methodology is also extended to the deconstruction of other frequently used polyester plastics, polybutylene terephthalate (PBT), polyethylene naphthalate (PEN), and polyethylene furanoate (PEF), and operates equally well with post-consumer waste products. Notably, this process is also compatible with plastic mixtures of polyesters with polyolefins, polyamides, and polycarbonates, leading to the selective conversion of each polyester to the corresponding monomer, leaving the residual polymer unchanged and polyester-free.

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

Rapid Construction of Validated Chemistry Models for Advanced Biofuels (Co-Optima Final Report)

Computer methods were developed and demonstrated that make it possible to predict the combustion and pyrolysis chemistry of proposed biofuels, even before the biofuels are ever manufactured or experimentally tested. The methods are based on first-principles calculations of reaction rates and equilibria. A large number of complicated calculations are required, so we developed a computer workflow that automates many of the steps. With the chemical structure of the biofuel and the system conditions (temperature, pressure, compositions, etc.) as the input, the computer methods can construct a detailed kinetic model with refined parameters without intense human intervention. The automation of model construction makes it practical for a single engineer to make the predictions in a reasonable time period. The accuracy of the computer predictions was tested by measuring the time-profiles of various reaction intermediates (carbon monoxide, carbon dioxide, water, formaldehyde, methane, and ethylene) formed as the biofuels pyrolyze or ignite using sophisticated laser shock tube methods. Several biofuels, including methyl propyl ether, cyclopentanone, butyl acetate isomers, etc., were carefully studied to demonstrate the validity of the proposed computational and experimental methodology. This research project opens up the possibility for assessing some proposed biofuels on the computer without expensive experimental campaigns. The new computer methods are open source and well-documented, allowing a knowledgeable modeler to easily access the developed methods and implement them in their work routine. Moreover, they are also convenient and powerful, promising for developing the fuel chemistry models needed for use in engine simulators, facilitating co-optimization of new engine designs with new fuels.

09 BIOMASS FUELS↗
DOE OSTI2023

Class-based separations of mixed solid–liquid systems with condensable solvent washing and extraction: The dilemma of pizza box recycling

As primary feedstocks deplete across the world, raw material extraction becomes increasingly expensive. Awareness of the environmental impact of primary extraction has motivated the development of energy- and reagent-efficient methods for material reuse. This work confronts an emblematic challenge of modern recycling: the soiled pizza box. While the fibers constituting corrugated cardboard are generally recyclable, pizza contaminants such as sauces and oils complicate their reuse, resulting in municipal prohibitions on the recycling of used pizza boxes in cardboard recycling streams and a representative of 275 kg/year per US household of food waste that is directed to landfill. This challenge is common to many materials, and engineering strategies must be developed to tackle complex/mixed feedstocks. To address the mixed composition of the pizza box (and similar materials), an environmentally benign, non-toxic organic solvent is applied to remove and fractionate components from mixed materials. The solvent employed in this process, dimethyl ether (DME), is a condensable hygroscopic gas, which facilitates its removal and recovery for reuse. Further, the results of this study indicate that 1) DME is capable of solubilizing and extracting components from soiled cardboard and other materials, (resulting in cardboard drier than new/unused cardboard) facilitating its recycling, and 2) the DME-soluble components of the system phase separate into aqueous and fatty acid/oil fractions (potentially ~27.5 kg/year per US household). Condensable solvent-driven washing and extraction enable the efficient separation of multiple intermediate product streams, suggesting a pathway to enable technology development necessary for achieving clean production in a circular economy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗