Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Transition states”

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

Rate coefficients for rotational state-to-state transitions in H 2 O + H 2 O collisions for cometary and planetary applications, as predicted by mixed quantum-classical theory

We present new calculations of collision cross sections for state-to-state transitions between the rotational states in an H 2 O + H 2 O system, which are used to generate a new database of collisional rate coefficients for cometary and planetary applications. Calculations were carried out using a mixed quantum-classical theory approach that is implemented in the code MQCT. The large basis set of rotational states used in these calculations permits us to predict thermally averaged cross sections for 441 transitions in para- and ortho-H 2 O in a broad range of temperatures. It is found that all state-to-state transitions in the H 2 O + H 2 O system split into two well-defined groups, one with higher cross-section values and lower energy transfer, which corresponds to the dipole-dipole driven processes. The other group has smaller cross sections and higher energy transfer, driven by higher-order interaction terms. We present a detailed analysis of the theoretical error bars, and we symmetrized the state-to-state transition matrixes to ensure that excitation and quenching processes for each transition satisfy the principle of microscopic reversibility. We also compare our results with other data available from the literature for H 2 O + H 2 O collisions.

79 ASTRONOMY AND ASTROPHYSICS↗

Interplay between LHCSR proteins and state transitions governs the NPQ response in Chlamydomonas during light fluctuations

Abstract Photosynthetic organisms use sunlight as the primary energy source to fix CO 2 . However, in nature, light energy is highly variable, reaching levels of saturation for periods ranging from milliseconds to hours. In the green microalga Chlamydomonas reinhardtii , safe dissipation of excess light energy by nonphotochemical quenching (NPQ) is mediated by light‐harvesting complex stress‐related (LHCSR) proteins and redistribution of light‐harvesting antennae between the photosystems (state transition). Although each component underlying NPQ has been documented, their relative contributions to NPQ under fluctuating light conditions remain unknown. Here, by monitoring NPQ in intact cells throughout high light/dark cycles of various illumination periods, we find that the dynamics of NPQ depend on the timescales of light fluctuations. We show that LHCSRs play a major role during the light phases of light fluctuations and describe their role in growth under rapid light fluctuations. We further reveal an activation of NPQ during the dark phases of all high light/dark cycles and show that this phenomenon arises from state transition. Finally, we show that LHCSRs and state transition synergistically cooperate to enable NPQ response during light fluctuations. These results highlight the dynamic functioning of photoprotection under light fluctuations and open a new way to systematically characterize the photosynthetic response to an ever‐changing light environment.

59 BASIC BIOLOGICAL SCIENCES↗

Machine learning for impurity charge-state transition levels in semiconductors from elemental properties using multi-fidelity datasets

Quantifying charge-state transition energy levels of impurities in semiconductors is critical to understanding and engineering their optoelectronic properties for applications ranging from solar photovoltaics to infrared lasers. While these transition levels can be measured and calculated accurately, such efforts are time-consuming and more rapid prediction methods would be beneficial. Here, we significantly reduce the time typically required to predict impurity transition levels using multi-fidelity datasets and a machine learning approach employing features based on elemental properties and impurity positions. We use transition levels obtained from low-fidelity (i.e., local-density approximation or generalized gradient approximation) density functional theory (DFT) calculations, corrected using a recently proposed modified band alignment scheme, which well-approximates transition levels from high-fidelity DFT (i.e., hybrid HSE06). Further, the model fit to the large multi-fidelity database shows improved accuracy compared to the models trained on the more limited high-fidelity values. Crucially, in our approach, when using the multi-fidelity data, high-fidelity values are not required for model training, significantly reducing the computational cost required for training the model. Our machine learning model of transition levels has a root mean squared (mean absolute) error of 0.36 (0.27) eV vs high-fidelity hybrid functional values when averaged over 14 semiconductor systems from the II–VI and III–V families. As a guide for use on other systems, we assessed the model on simulated data to show the expected accuracy level as a function of bandgap for new materials of interest. Finally, we use the model to predict a complete space of impurity charge-state transition levels in all zinc blende III–V and II–VI systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High salt-induced PSI-supercomplex is associated with high CEF and attenuation of state transitions

Abstract While PSI-driven cyclic electron flow (CEF) and assembly of thylakoid supercomplexes have been described in model organisms like Chlamydomonas reinhardtii , open questions remain regarding their contributions to survival under long-term stress. The Antarctic halophyte, C. priscuii UWO241 (UWO241), possesses constitutive high CEF rates and a stable PSI-supercomplex as a consequence of adaptation to permanent low temperatures and high salinity. To understand whether CEF represents a broader acclimation strategy to short- and long-term stress, we compared high salt acclimation between the halotolerant UWO241, the salt-sensitive model, C. reinhardtii , and a moderately halotolerant Antarctic green alga, C. sp. ICE-MDV (ICE-MDV). CEF was activated under high salt and associated with increased non-photochemical quenching in all three Chlamydomonas species. Furthermore, high salt-acclimated cells of either strain formed a PSI-supercomplex, while state transition capacity was attenuated. How the CEF-associated PSI-supercomplex interferes with state transition response is not yet known. We present a model for interaction between PSI-supercomplex formation, state transitions, and the important role of CEF for survival during long-term exposure to high salt.

59 BASIC BIOLOGICAL SCIENCES↗

Photoisomerization transition state manipulation by entangled two-photon absorption

Significance Entangled two-photon absorption has attracted considerable interest due to its potential applications for low–photon flux spectroscopy and microscopy. The entanglement parameters in the twin-photon state can be exploited to control two-photon excitation processes. Here we demonstrate that photon entanglement provides a powerful novel control knob for the nuclear wave packets in an optically dark electronic state. We show that the transition states in the trans–cis photoisomerization of azobenzene, initiated by an entangled two-photon absorption process, can be manipulated significantly by entangled light. These effects can be monitored experimentally by coherent stimulated X-ray Raman signals which reveal electronic coherences during the passage through conical intersections.

54 ENVIRONMENTAL SCIENCES↗

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development. Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions. However, the internal mechanisms of batteries are sensitive to many factors, such as charging/discharging protocols, manufacturing/storage conditions, and usage patterns. These factors will induce state transitions, thereby decreasing the prediction accuracy of data-driven approaches. Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer learning methods, Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit, to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance. From our results, our transfer learning methods reduce root-mean-squared error by 41% through adapting to the target domain. Furthermore, the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining. These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

25 ENERGY STORAGE↗

Degree of rate control and De Donder relations – An interpretation based on transition state theory

We describe sensitivities of elementary steps as salient parameters in determining the rate determining character of elementary steps within a reaction network and develop a formalism wherein the overall composite reaction is described by an apparent rate-determining step that is a sensitivity-weighted average of the elementary steps that comprise the reaction. Reaction parameters—apparent reaction orders, apparent enthalpy and entropy of activation—of the composite reaction network are determined within the framework we develop by application of transition state theory to the apparent rate-determining step. From this formalism we develop methods for determination of surface coverages by measuring only reaction orders, novel methods for discrimination between proposed mechanisms, a proof that the kinetic degrees of rate control sum to unity, and a proof for the relationship between fractional coverages and thermodynamic degrees of rate control. Two complementary formalisms for identifying rate-limiting transition states are broadly employed in chemical kinetics—De Donder relations based on measuring the thermodynamic driving forces of elementary steps during reaction and degrees of rate control based on knowledge of the kinetics of elementary reaction steps. Here, the formalism developed herein unifies these two strategies to elucidate in the most general case a relationship between the thermodynamic driving forces of elementary steps captured by the reversibilities and the kinetic and thermodynamic degrees of rate control.

42 ENGINEERING↗

Cryogenic Vibrationally Resolved Photoelectron Spectroscopy of OH–(H2O): Confirmation of Multidimensional Franck-Condon Simulation Results for the Transition State of the OH + H2O Reaction

We present a transition state spectroscopic study of the OH + H2O reaction using the experimental technique of cryogenic Negative Ion Photoelectron Spectroscopy (NIPES). The recorded NIPE spectrum at 193 nm exhibits multiple vibrational progressions that include excitations to the shared H atom antisymmetric stretching mode with an interval of 0.32 eV as well as other progressions, mainly involving the H bending and O…O symmetric stretching modes. The Vertical Detachment Energy (VDE) was measured at 3.53 eV, whereas an upper limit for the Adiabatic Detachment Energy (ADE) was estimated at 2.90 eV. These values are in excellent agreement with the theoretically computed values of 3.51 eV and 2.83 eV respectively, obtained at the CCSD(T)/aug-cc-pV5Z level of theory. The recorded NIPE spectrum is in very good agreement when compared to the one recently reported from four-dimensional Franck-Condon simulations, in which a similar spectral profile was predicted. Besides observing the ground state, a charge-transfer excited state in the form of [OH–(H2O)+] is identified with a relative energy of 1.39 eV, well matching the previous prediction of 1.36 eV. This work was supported by U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences, and performed using EMSL, a national scientific user facility sponsored by DOE’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory, which is operated by Battelle Memorial Institute for the DOE. The theoretical calculations were conducted on EMSL’s “Cascade” Supercomputer. This research also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

Cao, Wenjin↗

Improved accuracy and transferability of molecular-orbital-based machine learning: Organics, transition-metal complexes, non-covalent interactions, and transition states

We report molecular-orbital-based machine learning (MOB-ML) provides a general framework for the prediction of accurate correlation energies at the cost of obtaining molecular orbitals. The application of Nesbet’s theorem makes it possible to recast a typical extrapolation task, training on correlation energies for small molecules and predicting correlation energies for large molecules, into an interpolation task based on the properties of orbital pairs. We demonstrate the importance of preserving physical constraints, including invariance conditions and size consistency, when generating the input for the machine learning model. Numerical improvements are demonstrated for different datasets covering total and relative energies for thermally accessible organic and transition-metal containing molecules, non-covalent interactions, and transition-state energies. MOB-ML requires training data from only 1% of the QM7b-T dataset (i.e., only 70 organic molecules with seven and fewer heavy atoms) to predict the total energy of the remaining 99% of this dataset with sub-kcal/mol accuracy. This MOB-ML model is significantly more accurate than other methods when transferred to a dataset comprising of 13 heavy atom molecules, exhibiting no loss of accuracy on a size intensive (i.e., per-electron) basis. It is shown that MOB-ML also works well for extrapolating to transition-state structures, predicting the barrier region for malonaldehyde intramolecular proton-transfer to within 0.35 kcal/mol when only trained on reactant/product-like structures. Finally, the use of the Gaussian process variance enables an active learning strategy for extending the MOB-ML model to new regions of chemical space with minimal effort. We demonstrate this active learning strategy by extending a QM7b-T model to describe non-covalent interactions in the protein backbone–backbone interaction dataset to an accuracy of 0.28 kcal/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transition-state correlations for predicting thermochemistry of adsorbates and surface reactions

Estimating thermochemical properties from linear correlations may provide a pathway to circumvent expensive density functional theory (DFT) calculations for quantities such as pre-exponentials and temperature corrections to DFT energies. Here, in this work, we construct thermochemical scaling relations between C 1 –C 6 n-alkanes in the gas phase and adsorbed alkyl chains extending from several transition metal surfaces, and examine changes in the slope and fit between metals and adsorption sites. We subsequently add –OH, –NH 2 , C$=$O, and C$=$C functional groups to the C 1 –C 6 molecules and demonstrate strong linear correlations for thermochemistry across all species. We broaden the correlations to incorporate transition states of C 1 –C 6 n-alkane dehydrogenation reactions, where thermochemistry for computationally prohibitive transition-state calculations can be quickly assessed. Additionally, we rationalize the linearity of thermochemical correlations based on the composition of the homologous series and theoretical assessments. As an application of the correlations, we estimate pre-exponentials for elementary surface reactions of ethane and propane hydrogenolysis on Ru(0001), which is of relevance to plastic hydrogenolysis. Depending on kinetically important steps, entropic contributions may be necessary to include in certain reaction mechanisms; in contrasting examples, entropies are found to be relatively insignificant for ethane hydrogenolysis but pertinent for propane hydrogenolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ring-Opening Dynamics of the Cyclopropyl Radical and Cation: the Transition State Nature of the Cyclopropyl Cation

Here, we provide compelling experimental and theoretical evidence for the transition state nature of the cyclopropyl cation. Synchrotron photoionization spectroscopy employing coincidence techniques together with a novel simulation based on high-accuracy ab initio calculations reveal that the cation is unstable via its allowed disrotatory ring-opening path. The ring strains of the cation and the radical are similar, but both ring opening paths for the radical are forbidden when the full electronic symmetries are considered. These findings are discussed in light of the early predictions by Longuet-Higgins alongside Woodward and Hoffman; we also propose a simple phase space explanation for the appearance of the cyclopropyl photoionization spectrum. The results of this work allow the refinement of the cyclopropane C–H bond dissociation energy, in addition to the cyclopropyl radical and cation cyclization energies, via the Active Thermochemical Tables approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improved temperature dependence of rate coefficients for rotational state-to-state transitions in H 2 O + H 2 O collisions

Aims. We present an improved database of temperature-dependent rate coefficients for rotational state-to-state transitions in H 2 O + H 2 O collisions. The database includes 231 transitions between the lower para-states of H 2 O and 210 transitions between its lower ortho-states (up toj= 7) and can be employed in cometary and planetary applications up to the temperature of 1000 K. Methods. We developed and applied a new general method that allows the generation of rate coefficients for excitation and quenching processes that automatically satisfy the principle of microscopic reversibility and also helps to cover the range of low collision energies by interpolation of cross sections between the process threshold and the computed data points. Results. We find that in the range of intermediate temperatures, 150

Astronomy & Astrophysics↗

Force-Free Identification of Minimum-Energy Pathways and Transition States for Stochastic Electronic Structure Theories

Here, the accurate mapping of potential energy surfaces (PESs) is crucial to our understanding of the numerous physical and chemical processes mediated by atomic rearrangements, such as conformational changes and chemical reactions, and the thermodynamic and kinetic feasibility of these processes. Stochastic electronic structure theories, e.g., Quantum Monte Carlo (QMC) methods, enable highly accurate total energy calculations that in principle can be used to construct the PES. However, their stochastic nature poses a challenge to the computation and use of forces and Hessians, which are typically required in algorithms for minimum-energy pathway (MEP) and transition state (TS) identification, such as the nudged elastic band (NEB) algorithm and its climbing image formulation. Here, we present strategies that utilize the surrogate Hessian line-search method, previously developed for QMC structural optimization, to efficiently identify MEP and TS structures without requiring force calculations at the level of the stochastic electronic structure theory. By modifying the surrogate Hessian algorithm to operate in path-orthogonal subspaces and at saddle points, we show that it is possible to identify MEPs and TSs by using a force-free QMC approach. We demonstrate these strategies via two examples, the inversion of the ammonia (NH 3 ) molecule and the nucleophilic substitution (S N 2) reaction F – + CH 3 F → FCH 3 + F – . We validate our results using Density Functional Theory (DFT)- and Coupled Cluster (CCSD, CCSD(T))-based NEB calculations. We then introduce a hybrid DFT-QMC approach to compute thermodynamic and kinetic quantities, free energy differences, rate constants, and equilibrium constants that incorporates stochastically optimized structures and their energies, and show that this scheme improves upon DFT accuracy. Our methods generalize straightforwardly to other systems and other high-accuracy theories that similarly face challenges computing energy gradients, paving the way for highly accurate PES mapping, transition state determination, and thermodynamic and kinetic calculations at significantly reduced computational expense.

Iyer, Gopal R.↗

Modeling State Transition and Head-Dependent Efficiency Curve for Pumped Storage Hydro in Look-Ahead Dispatch

As one of the most widely installed utility-scale storage facilities, pumped storage hydro (PSH) plays an essential role in providing flexibility for power systems worldwide. Thus, to accurately quantify the flexibility of PSH units in operational optimization problems is important. The conventional PSH models in the literature rarely consider detailed state transitions due to their hourly-based settings. However, it becomes imperative for operational optimization on short-term intervals, especially with increasing shares of renewable energy in power systems. To this end, this paper presents a novel deterministic PSH model that considers the transition time and trajectory between three states of PSH units in look-ahead dispatch. Moreover, to better characterize the varying efficiency of PSH units with water head and flow rate, this paper proposes to model detailed headdependent efficiency curves (hereafter called input-output curves) in look-ahead dispatch, which encounters heavy computational burdens when short time intervals are applied. In this work, a zig-zag piece-wise linear approximation method is used for input-output curve modeling. This can enable an accurate quantification for variable efficiency and head dependence in a computationally effective manner. Here, numerical results are presented to show performances of the proposed PSH model in both flexibility quantification and computation time.

13 HYDRO ENERGY↗

Restricted Partition Function Semiclassical Transition State Theory (RPF-SCTST): Applications to Reactions Involving Hydrogen Cyanide, Hydrogen Peroxide, and Formaldehyde Oxide

We demonstrate the efficiency of the numerical calculation of thermal semiclassical transition state theory (SCTST) rates across several representative chemical reactions using the restricted partition function (RPF)─viz a function that depends only on the imaginary action associated with a reaction. Here, we treat the potential energy surfaces (PESs) through fourth order expansions around the saddle point and integrate the Hamiltonian up to second order in employing vibrational perturbation theory. We apply this formalism to uni- and bimolecular reactions with different─though relatively high─barrier heights to uncover the influence of the barrier properties, minimal energies, and separability of the rotational motion on rate constants and tunneling corrections. Although all modes are coupled within the RPF, we found in our numerical examples that the rotational component in the absence of significant rotational distortions can be separated from the vibrational contributions. Moreover, a classical treatment of the rotational contribution is adequate over the temperature range from approximately 100 to 1000 K. We also found that the choice of DFT basis set can lead to variations in rate constants of up to an order of magnitude. Lastly, different schemes for counting eligible energy levels result in rate constants that differ by no more than a factor of 2, with the remaining discrepancies attributed to the treatment of near-convergent levels in perturbation theory.

74 ATOMIC AND MOLECULAR PHYSICS↗

Survival of itinerant excitations and quantum spin state transitions in YbMgGaO 4 with chemical disorder

A recent focus of quantum spin liquid (QSL) studies is how disorder/randomness in a QSL candidate affects its true magnetic ground state. The ultimate question is whether the QSL survives disorder or the disorder leads to a “spin-liquid-like” state, such as the proposed random-singlet (RS) state. Since disorder is a standard feature of most QSL candidates, this question represents a major challenge for QSL candidates. YbMgGaO 4 , a triangular lattice antiferromagnet with effective spin-1/2 Yb 3+ ions, is an ideal system to address this question, since it shows no long-range magnetic ordering with Mg/Ga site disorder. Despite the intensive study, it remains unresolved as to whether YbMgGaO 4 is a QSL or in the RS state. Here, through ultralow-temperature thermal conductivity and magnetic torque measurements, plus specific heat and DC magnetization data, we observed a residual κ 0 /T term and series of quantum spin state transitions in the zero temperature limit for YbMgGaO 4 . These observations strongly suggest that a QSL state with itinerant excitations and quantum spin fluctuations survives disorder in YbMgGaO 4 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Generator coordinate method for transition-state dynamics in nuclear fission

Since its beginnings, fission theory has assumed that low-energy induced fission takes place through transition-state channels at the barrier tops. Nevertheless, up to now there is no microscopic theory applicable to those conditions. We suggest that modern reaction theory is suitable for this purpose, and propose a methodology based on a configuration-interaction framework using the generator coordinate method (GCM). Simple reaction-theoretic models are constructed with the Gaussian overlap approximation to parametrize both the dynamics within the channels and their incoherent couplings to states outside the barrier. The physical characteristics of the channels examined here are their effective bandwidths and the quality of the coupling to compound-nucleus states as measured by the transmission factor T. We also investigate the spacing of GCM states with respect to their degree of overlap. We find that a rather coarse mesh provides an acceptable accuracy for estimating the bandwidths and transmission factors. The common numerical stability problem in using the GCM is avoided due to the choice of meshes and the finite bandwidths of the channels. Here, the bandwidths of the channels are largely controlled by the zero-point energy with respect to the collective coordinate in the GCM configurations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Rotational state-to-state transition rate coefficients for H 2 O + H 2 O collisions at nonequilibrium conditions

Aims.The goal is to develop a database of rate coefficients for rotational state-to-state transitions in H 2 O + H 2 O collisions that is suitable for the modeling of energy transfer in nonequilibrium conditions, in which the distribution of rotational states of H 2 O deviates from local thermodynamic equilibrium. Methods.A two-temperature model was employed that assumed that although there is no equilibrium between all possible degrees of freedom in the system, the translational and rotational degrees of freedom can be expected to achieve their own equilibria independently, and that they can be approximately characterized by Boltzmann distributions at two different temperatures,T kin andT rot . Results.Upon introducing our new parameterization of the collisional rates, taking into account their dependence on bothT kin andT rot , we find a change of up to 20% in the H 2 O rotational level populations for both ortho and para-H 2 O for the part of the cometary coma where the nonequilibrium regime occurs.

Astronomy & Astrophysics↗