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DOE OSTI2022

Mechanistic Study of 1,2-Dichloroethane Hydrodechlorination on Cu-Rich Pt–Cu Alloys: Combining Reaction Kinetics Experiments with DFT Calculations and Microkinetic Modeling

Cu-rich Pt–Cu bimetallic catalysts are among the most promising candidates for actively catalyzing the hydrodechlorination of 1,2-dichloroethane (1,2-DCA) toward ethylene production. Combining reaction kinetics experiments with density functional theory (DFT) calculations and mean-field microkinetic modeling, we present a systematic mechanistic study for 1,2-DCA hydrodechlorination on Cu-rich Pt–Cu alloy catalysts. Our DFT (PBE+(TS+SCS)) results suggest that increasing Cu content in the Pt–Cu alloy destabilizes C 2 -species adsorption while stabilizing the binding of atomic chlorine. The reaction energetics of all the elementary steps in the 1,2-DCA reaction network were calculated on a Pt 1 Cu 3 (111) model surface. The DFT results were then used to construct a microkinetic model, and the model-predicted reaction rates were compared with our reaction kinetics experimental results on a Cu-rich SiO 2 -supported Pt–Cu alloy catalyst through a parameter estimation procedure. Both the reaction kinetics experiments and the microkinetic model after parameter adjustments yielded 100% selectivity to ethylene. The microkinetic model pointed to a reaction pathway involving two sequential chlorine-removal steps on the Pt–Cu alloy catalyst, a mechanism distinct from the one previously identified on pure Pt/SiO 2 catalysts, which involved an initial hydrogen-removal step. Adjustments to the DFT-derived parameters indicate the possible formation of chlorine-induced Cu-enriched surface sites during 1,2-DCA hydrodechlorination conditions, sites that are more active than those encountered in the bulk Pt 1 Cu 3 (111) alloy surface. Furthermore, our study offers valuable initial insights on the 1,2-DCA hydrodechlorination reaction mechanism and the nature of the active sites on PtCu bimetallic catalysts.

1,2-Dichloroethane↗

DOE OSTI2020

Programmable Dynamic Self-Assembly of DNA Nanostructures (Final Technical Report)

This technical report summarizes our research toward the synthesis of active biomolecular materials that take advantage of the biological properties of DNA and RNA, but can operate in non-biological contexts. Our approach takes inspiration from the dynamic assembly and disassembly of cytoskeletal filaments inside cells, and focuses on the generation of artificial filaments with comparable adaptation and responsiveness. We report the construction of DNA nanotube systems that assemble and disassemble reversibly in response to a variety of molecular stimuli including other nucleic acids (DNA and RNA), enzymes, and pH, as well as our progress on developing a reaction network framework to regulate self-assembly. Our DNA polymers are active in that they rely on the programmable energetics of hybridization and on the kinetics of enzymatic reactions to perform assembly and disassembly. Results include experiments and computational models. The research described here was performed between June 15, 2016 and June 15, 2019 at the University of California at Riverside with the support of the collaborative award DE-SC0010595 to PI Elisa Franco at UC Riverside and PI Rebecca Schulman at Johns Hopkins. The report focuses on the research performed by the team of PI Franco. The report also details work performed during a no-cost extension (June 15, 2019 - December 15, 2019) awarded to PI Guillermo Aguilar and PI Franco.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Modeling Combustion Reaction ODEs with Neural Networks

The chemistry of combustion reactions is complex as it involves many species and reactions. In practice, such a system is often modeled computationally using an empirically derived chemical mechanism. Given the large range of reaction rates, the system is then time evolved using a stiff ODE solver. However, even when reduced chemical mechanisms are employed, the system can become computationally expensive for two-dimensional or three-dimensional systems. Such systems can also face problems with instability. As such, it is desirable to find a cheaper, stable alternative to solving the reaction system. Neural networks offer the potential to learn these reaction ODEs and time evolve a combustion reaction in a more cost-efficient manner than stiff ODE solvers. In this study, a variety of neural networks are trained on zero-dimensional Cantera simulations of methane combustion with varying initial conditions. Several predictive approaches as well as several neural network architectures (artificial neural network with dropout, ResNet, and Neural ODE) are compared in their ability to predict combustion trajectories. Promising models are then identified.

combustion kinetics↗

DOE OSTI2021

Hydrodechlorination of 1,2-Dichloroethane on Platinum Catalysts: Insights from Reaction Kinetics Experiments, Density Functional Theory, and Microkinetic Modeling

Catalytic hydrodechlorination is a promising strategy for treating industrial 1,2-dichloroethane wastes, for which Pt and Pt-based alloy catalysts are widely used. Here, we performed a detailed mechanistic study for 1,2-dichloroethane hydrodechlorination on Pt using a synergistic approach combining density functional theory (DFT) calculations, reaction kinetics experiments, and microkinetic modeling. Using planewave DFT calculations, we evaluated the reaction energy and activation energy barrier of each elementary step involved in the reaction network on Pt(111). The calculated energetics were then incorporated into a comprehensive mean-field microkinetic model accounting for a total of 65 elementary steps. The model-predicted reaction rates were compared with the results from our reaction kinetics experiments on SiO2-supported Pt catalysts. Our results indicated that the hydrodechlorination of 1,2-dichloroethane on Pt(111) starts with a H-removal step; then, it proceeds through a sequence of alternating dechlorination and dehydrogenation steps until vinylidene (CH 2 C*) is formed; finally, CH 2 C* is hydrogenated to the final product, ethane, sequentially via vinyl (CH 2 CH*), ethylene, and ethyl (CH 3 CH 2 *) intermediates. After model parameter adjustments, we achieved good agreement between our theoretical model and experimental results; the adjustments to the calculated parameters are consistent with the typically anticipated coverage effects. Furthermore, our study offers valuable mechanistic insights, which are useful for improving catalysts for this chemistry.

1,2-dichloroethane↗

DOE OSTI2025

Opportunities for isomer studies for astrophysics at FRIB

The role of nuclear isomers in astrophysical nucleosynthesis is gaining increased attention, as reactions on ground and isomeric states are both potentially important for determining the reaction rates and flow within the reaction network. A particular case is the odd-odd N=Z nuclides in the sd -shell, which play an important role in breakout from the CNO cycle in nova nucleosynthesis, affecting reaction flow, the nucleosynthesis end-point, and final abundances, impacting potential astronomical observables. Because many of these nuclides have low-lying isomers, it is important to constrain reactions on both ground and isomeric states. Developments in radioactive-beam facilities are opening such opportunities, via direct and indirect techniques. The first measurement using a new technique for manipulating ground/isomer content in reaccelerated beams without affecting ion optics, has been employed to study 38 K, which will be applicable to measurements on 34 Cl and others at the nascent Facility for Rare Isotope Beams.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

MEMOTE for standardized genome-scale metabolic model testing

Reconstructing metabolic reaction networks enables the development of testable hypotheses of an organism’s metabolism under different conditions. State-of-the-art genome-scale metabolic models (GEMs) can include thousands of metabolites and reactions that are assigned to subcellular locations. Gene–protein–reaction (GPR) rules and annotations using database information can add meta-information to GEMs. GEMs with metadata can be built using standard reconstruction protocols, and guidelines have been put in place for tracking provenance and enabling interoperability, but a standardized means of quality control for GEMs is lacking. Here we report a community effort to develop a test suite named MEMOTE (for metabolic model tests) to assess GEM quality.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2021

Neutral–neutral synthesis of organic molecules in cometary comae

Remote and in situ observations of cometary gases have revealed the presence of a wealth of complex organic molecules, including carbon chains, alcohols, imines, and the amino acid glycine. Such chemical complexity in cometary material implies that impacts by comets could have supplied reagents for prebiotic chemistry to young planetary surfaces. However, the assumption that some of the molecules observed in cometary comae at millimetre wavelengths originate from ices stored inside the nucleus has not yet been proven. In fact, the comae of moderately-active comets reach sufficient densities within a few thousand kilometres of the nucleus for an active (solar radiation-driven) photochemistry to ensue. Here, we present results from our latest chemical-hydrodynamic models incorporating an updated reaction network, and show that the commonly-observed HC3N (cyanoacetylene) and NH2CHO (formamide) molecules can be efficiently produced in cometary comae as a result of two-body, neutral–neutral, gas-phase reactions involving well-known coma species. In the presence of a near-nucleus distributed source of CN (similar to that observed by the Rosetta spacecraft at comet 67P), we find that sufficient HC3N and NH2CHO can be synthesized to match the abundances of these molecules observed previously in Oort cloud comets. The precise coma origins of these (and other) complex organic molecules can be verified through radio interferometric mapping observations, for example using the Atacama Large Millimeter/submillimeter Array.

Comets↗

DOE OSTI2021

The Transient Covalent Bond in Abiotic Nonequilibrium Systems

Abstract Biochemical systems accomplish many critical functions with by operating out‐of‐equilibrium using the energy of chemical fuels. The formation of a transient covalent bond is a simple but very effective tool in designing analogous reaction networks. This Minireview focuses on the fuel chemistries that have been used to generate transient bonds in recent demonstrations of abiotic nonequilibrium systems (i.e., systems that do not make use of biological components). Fuel reactions are divided into two fundamental classifications depending on whether the fuel contributes structural elements to the activated state, a distinction that dictates how they can be used. Reported systems are further categorized by overall fuel reaction (e.g., hydrolysis of alkylating agents, carbodiimide hydration) and illustrate how similar chemistry can be used to effect a wide range of nonequilibrium behavior, ranging from self‐assembly to the operation of molecular machines.

Kariyawasam, Lasith S.↗

DOE OSTI2022

Modified Energy Span Analysis of Catalytic Parallel Pathways and Selectivity

Mechanistic modeling provides vital insights into catalytic reactions. To analyze complex reaction networks with parallel pathways, we leverage the graph theory approach of the Energy Span Model (ESM) to develop a modified energy span analysis (MESA). A new method of cycle plots is proposed to perform reaction pathways analysis visually. We demonstrate this method on two published models: one describing carbon monoxide oxidation and the other simulating ethylene conversion to propanal via hydroformylation or ethane via hydrogenation. Fundamental insights explain kinetic observables, such as a reactant’s negative reaction order. General principles are revealed, such as rate-determining surface species being outside the primary reaction flux cycle and pathway selectivity being a purely kinetic property when reaction conditions are not near equilibrium. Lastly, we demonstrate MESA’s consistency with published microkinetic modeling results, highlighting this technique’s extension of the ESM to heterogeneous catalysts using collision theory to describe adsorption steps and concentration effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Impact of in situ nuclear networks and atomic opacities on neutron star merger ejecta dynamics, nucleosynthesis, and kilonovae

Context. Binary neutron star merger (BNSM) ejecta are key sites of rapid neutron capture (r-process) nucleosynthesis and they produce kilonovae powered by the radioactive decay of freshly synthesized nuclei. Modeling their evolution requires multi-physics simulations involving hydrodynamics, nuclear reactions, and radiative processes. The impact of nuclear burning and atomic opacity is poorly understood and often treated with simplified prescriptions. Aims. We systematically investigate different treatments of nuclear heating, particle thermalization, and atomic opacities in radiation-hydrodynamics simulations of BNSM ejecta and kilonova light curves. Methods. Ejecta profiles from long-term numerical-relativity simulations of asymmetric neutron star binaries with a massive neutron star remnant were evolved to ∼30 days using a 2D ray-by-ray approach. We compared simplified heating-rate and thermalization prescriptions with in situ Nuclear reaction Network (NN) calculations that track nuclear energy deposition and include a composition-dependent thermalization scheme. We also contrasted various gray opacity models with a frequency-dependent treatment based on atomic calculations. Results. Coupling NN and hydrodynamics significantly affects nucleosynthesis and kilonova emission. Assuming homologous expansion alters abundance evolution and produces a narrower, less populated second r-process peak and a third peak shifted to higher mass numbers. The back-reaction of nuclear heating affects the temperature evolution enough to delay and redden the early (t∼ hours) kilonova peaks. A constant thermalization efficiency underestimates and reddens the early emission while overestimating the late-time luminosity compared to the composition-dependent treatment. Analytical opacity prescriptions yield a more extended, colder photosphere, resulting in dimmer, redder kilonovae at early times (t≲ hour), while the delayed recession of the photosphere prolongs the red emission at t ≳ 5 days. Conclusions. Coupling hydrodynamics to an in situ NN is crucial for reliable nucleosynthesis and kilonova predictions. Resolving the first several hundred milliseconds of the hydrodynamics is essential for robust nucleosynthesis calculations. Composition-dependent thermalization and frequency-dependent, atomic-physics-based opacities are needed to accurately capture the temperature evolution of the ejecta and the brightness and color evolution of the kilonova. Calibrated analytic nuclear-power fits with simplified thermalization and opacity prescriptions can still reproduce the density and temperature evolution of the ejecta.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

The Transient Covalent Bond in Abiotic Nonequilibrium Systems

Biochemical systems accomplish many critical functions with by operating out-of-equilibrium using the energy of chemical fuels. The formation of a transient covalent bond is a simple but very effective tool in designing analogous reaction networks. This Minireview focuses on the fuel chemistries that have been used to generate transient bonds in recent demonstrations of abiotic nonequilibrium systems (i.e., systems that do not make use of biological components). Here, fuel reactions are divided into two fundamental classifications depending on whether the fuel contributes structural elements to the activated state, a distinction that dictates how they can be used. Reported systems are further categorized by overall fuel reaction (e.g., hydrolysis of alkylating agents, carbodiimide hydration) and illustrate how similar chemistry can be used to effect a wide range of nonequilibrium behavior, ranging from self-assembly to the operation of molecular machines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Solvent oligomerization pathways facilitated by electrolyte additives during solid-electrolyte interphase formation

The solid–electrolyte interphase (SEI) layer formation is known to play an important role in determining the lifetime of lithium-ion batteries. A thin, stable SEI layer is linked to overall improved battery performance and longevity, however, the factors and mechanisms that lead to optimal SEI morphology and composition are not well understood. Inclusion of electrolyte additives (fluoroethylene carbonate, FEC; and vinylene carbonate, VC) is often necessary for improving SEI characteristics. To understand how these electrolyte additives impact SEI formation, we employed molecular dynamics (MD) and density functional theory (DFT) simulations to study the reaction networks and oligomerization pathways, respectively, for three systems containing ethylene carbonate (EC), a lithium ion, and FEC or VC. MD simulations suggest radical oligomerization pathways analogous to traditional oligomerization with nucleophilic alkoxide species via SN1 reaction mechanisms. Both S N 1 and S N 2 mechanisms were studied for all three systems using DFT. Oligomerization reactions were studied with both a standard alkoxide species and a ring-opened EC radical as the nucleophiles and EC, FEC, and VC as the electrophiles. For all cases, FEC and VC exhibited lower free energy barriers and more stable adducts when compared with EC. We conclude that one of the role of additives is to modify the oligomerization process of EC by introducing branching points (FEC) or termination points (VC).

25 ENERGY STORAGE↗

DOE OSTI2020

Reaction Mechanism of Vapor-Phase Formic Acid Decomposition over Platinum Catalysts: DFT, Reaction Kinetics Experiments, and Microkinetic Modeling

A combination of periodic density functional theory (DFT, PW91-GGA) calculations, reaction kinetics experiments, and mean-field microkinetic modeling is used to derive insights on the reaction mechanism and determine the nature of the active site under reaction conditions for the vapor-phase decomposition of formic acid (FA, HCOOH) over Pt/C catalysts. Microkinetic models formulated using DFT energetics derived on the clean Pt(100) and Pt(111) required large parameter adjustments to reproduce the experimentally measured apparent activation energies and reaction orders. Further, these models predicted high surface coverage of adsorbed carbon monoxide (CO*), inconsistent with the environment of the active site in the DFT calculations on the clean surfaces. Consequently, we reperformed DFT calculations for the entire reaction network on partially CO*-covered (4/9 monolayer, ML) Pt(111) and Pt(100). The resultant microkinetic models, with thermochemistry and kinetics explicitly dependent on CO* coverage, were able to reproduce the experimentally determined activation energies and reaction orders, in addition to being self-consistent in CO* coverage. Our results suggest that Pt(100) is likely poisoned by CO* under typical reaction conditions and does not contribute significantly to the experimentally observed reactivity. Instead, we find that Pt(111) better represents the active site for FA decomposition reaction on Pt/C catalysts. The optimized model on 4/9 ML CO*-covered Pt(111) suggests that the reaction occurs via the carboxyl (COOH*) intermediate and that the spectator CO*-assisted pathways play a significant role under reaction conditions. Lastly, this study underscores the importance of spectator species on the energetics and the mechanism of a catalytic reaction and their key role in developing a model that better addresses the nature of the active site under realistic catalytic reaction conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Direct reactions for astrophysical p-capture rates with ORRUBA and GODDESS

Understanding the nucleosynthesis and energy generation in quiescent and explosive stellar burning requires a detailed understanding of reaction rates on many unstable nuclides. Such reaction rates are often governed by the properties of low-lying, isolated proton resonances. Though direct measurements of resonance strengths are ultimately desired, and are a focus of rare isotope beam facilities worldwide, such tour-de-force experiments must be guided by indirect techniques, in order to know resonance energies, J π assignments, and estimated widths, to inform targeted measurements. Furthermore, some important low-lying resonances may be too weak for direct measurements with radioactive beams, and indirect techniques provide the only practical constraints. Additionally, there has been growing interest in the astrophysical role of isomeric states, which can influence the reaction flow in nucleosynthetic reaction networks, and hence impact the quantitative interpretation of astronomical observables, such as γ-ray signatures, and elemental and isotopic ratios. Properties of single-proton resonances can be obtained by exploiting the selectivity of direct reactions, such as single-nucleon transfer and charge-exchange reactions. Constraining proton-capture rates via direct reactions has been a focus of the astrophysics program at ORNL for over two decades, spurring the development of the ORRUBA and GODDESS detector systems. Herein, a review of recent developments in instrumentation and radioactive beam delivery (including isomeric beam experiments) is presented, along with some specific examples of astrophysically interesting sd-shell nuclides, which have been a target of recent ORRUBA and GODDESS experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Probing O 2 -dependence of cyclopentyl reactions via isomer-resolved speciation

Modeling chemical kinetics relevant to low-temperature combustion requires complete description of reactions involving critical species such as hydroperoxyalkyl radicals, Q̇OOH, which undergo competing unimolecular reactions and bimolecular reactions with O 2 . The balance of flux across the two pathways affects rates of chain-branching and depends on temperature, pressure, and oxygen concentration. Accordingly, the influence of [O 2 ] on product formation from alkyl + O 2 reactions and the subsequent fate of Q̇OOH and related products is central to the development of an accurate chemical kinetics mechanism. Furthermore, chemical reactions consuming Q̇OOH-mediated species are often simplified to such a degree that mechanism truncation error (uncertainty derived from incomplete reaction networks) becomes significant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

International Network of Nuclear Reaction Data Centres

This report summarizes the IAEA Technical Meeting on the International Network of Nuclear Reaction Data Centres held as a video meeting from 4 to 7 May 2021. The meeting was attended by 29 participants representing 13 cooperative Centres from eight Member States (China, Hungary, India, Japan, Korea, Russia, Ukraine and USA) and two International Organisations (NEA, IAEA) as well as a participant from Kazakhstan. A summary of the meeting is given in this report along with the conclusions and actions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1987

Chemical network problems solved on NASA/Goddard's massively parallel processor computer

The single instruction stream, multiple data stream Massively Parallel Processor (MPP) unit consists of 16,384 bit serial arithmetic processors configured as a 128 x 128 array whose speed can exceed that of current supercomputers (Cyber 205). The applicability of the MPP for solving reaction network problems is presented and discussed, including the mapping of the calculation to the architecture, and CPU timing comparisons.

Cho, Seog Y.↗

DOE OSTI2020

DNA Reaction–Diffusion Attractor Patterns

Abstract Living systems can form and recover complex chemical patterns with precisely sized features in the ranges of tens or hundreds of microns. We show how designed reaction–diffusion processes can likewise produce precise patterns, termed attractor patterns, that reform their precise shape after being perturbed. We use oligonucleotide reaction networks, photolithography, and microfluidic delivery to form precisely controlled attractor patterns and study the responses of these patterns to different localized perturbations. Linear and “hill”‐shaped patterns formed and stabilized into shapes and at time scales consistent with reaction–diffusion models. When patterns were perturbed in particular locations with UV light, they reliably reformed their steady‐state profiles. Recovery also occurred after repeated perturbations. By designing the far‐from‐equilibrium dynamics of a chemical system, this study shows how it is possible to design spatial patterns of molecules that are sustained and regenerated by continually evolving towards a specific steady state configuration.

Dorsey, Phillip James↗