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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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DOE OSTI2024

Molecularly Imprinted Polymer Sensor Empowered by Bound States in the Continuum for Selective Trace-Detection of TGF-beta

The integration of advanced materials and photonic nanostructures can lead to enhanced biodetection capabilities, crucial in clinical scenarios and point-of-care diagnostics, where simplified strategies are essential. Herein, a molecularly imprinted polymer (MIP) photonic nanostructure is demonstrated, which selectively binding to transforming growth factor-beta (TGF-β), in which the sensing transduction is enhanced by bound states in the continuum (BICs). The MIP operating as a synthetic antibody matrix and coupled with BIC resonance, enhances the optical response to TGF-β at imprinted sites, leading to an augmented detection capability, thoroughly evaluated through spectral shift and optical lever analogue readout. The validation underscores the MIP-BIC sensor capability to detect TGF-β in spiked saliva, achieving a limit of detection of 10 fM and a resolution of 0.5 pM at physiological concentrations, with a precision of two orders of magnitude above discrimination threshold in patients. The MIP tailored selectivity is highlighted by an imprinting factor of 52, showcasing the sensor resistance to interference from other analytes. The MIP-BIC sensor architecture streamlines the detection process eliminating the need for complex sandwich immunoassays and demonstrates the potential for high-precision quantification. This positions the system as a robust tool for biomarker detection, especially in real-world diagnostic scenarios.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Photoionization and Photofragmentation Dynamics of I 2 in Intense Laser Fields: A Velocity-Map Imaging Study

The photoionization and photofragmentation dynamics of I 2 in intense femtosecond near-infrared laser fields were studied using velocity-map imaging of cations, electrons, and anions. A series of photofragmentation pathways originating from different cationic electronic states were observed following single ionization, leading to I + fragments with distinct kinetic energies, which could not be resolved in previous studies. Photoelectron spectra indicate that these high-lying dissociative states are primarily produced through nonresonant ionization from several molecular orbitals (MO) of the neutral. The photoelectron spectra also show clear signatures of resonant ionization pathways (Freeman resonances) to low-lying bound ionic states via Rydberg states of the neutral moiety. To investigate the role of these Rydberg states further, we imaged anionic products (I – ) formed through ion-pair dissociations of neutral molecules excited to these Rydberg states by the intense femtosecond laser pulse. Collectively, these results shed significant new light on the complex dynamics of I 2 molecules in intense laser fields and on the important role of neutral Rydberg states in a full description of strong-field phenomena in molecules.

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

Polarity-Tolerant Chloride Binding in Foldamer Capsules by Programmed Solvent-Exclusion

Persistent anion binding in a wide range of solution environments is a key challenge that continues to motivate and demand new strategies in synthetic receptor design. Though strong binding in low-polarity solvents has become routine, our ability to maintain high affinities in high-polarity solvents has not yet reached the standard set by nature. Anions are bound and transported regularly in aqueous environments by proteins that use secondary and tertiary structure to isolate anion binding sites from water. Inspired by this principle of solvent exclusion, we created a sequence-defined foldameric capsule whose global minimum conformation displays a helical folded state and is preorganized for 1:1 anion complexation. The high stability of the folded geometry and its ability to exclude solvent were supported by solid-state and solution phase studies. This capsule then withstood a 4-fold increase in solvent dielectric constant (εr) from dichloromethane (9) to acetonitrile (36) while maintaining a high and solvent-independent affinity of 10 5 M –1 ; ΔG ~ 28 kJ mol –1 . This behavior is unusual. More typical of solvent-dependent behavior, Cl – affinities were seen to plummet in control compounds, such as aryl-triazole macrocycles and pentads, with their solvent-exposed binding cavities susceptible to dielectric screening. Finally, dimethyl sulfoxide denatures the foldamer by putative solvent binding, which then lowers the foldamer’s Cl – affinity to normal levels. Furthermore, the design of this capsule demonstrates a new prototype for the development of potent receptors that can operate in polar solvents and has the potential to help manage hydrophilic anions present in the hydrosphere and biosphere.

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

NO Coupling at Copper to cis -Hyponitrite: N 2 O Formation via Protonation and H-Atom Transfer

Copper nitrite reductases (CuNIRs) convert NO 2 – to NO as well as NO to N 2 O under high NO flux at a mononuclear type 2 Cu center. While model complexes illustrate N–N coupling from NO that results in symmetric trans-hyponitrite [Cu II ]– ONNO–[Cu II ] complexes, in this work we report NO assembly at a single Cu site in the presence of an external reductant Cp* 2 M (M = Co, Fe) to give the first copper cis-hyponitrites [Cp* 2 M]{[Cu II ](κ 2 - O 2 N 2 )[Cu I ]}. Importantly, the κ 1 –N-bound [Cu I ] fragment may be easily removed by the addition of mild Lewis bases such as CNAr or pyridine to form the spectroscopically similar anion {[Cu II ](κ 2 -O 2 N 2 )} – . The addition of electrophiles such as H + to these anionic copper(II) cis-hyponitrites leads to N 2 O generation with the formation of the dicopper(II)-bis-μ-hydroxide [Cu II ] 2 (μ- OH) 2 . One-electron oxidation of the {[Cu II ](κ 2 -O 2 N 2 )} – core turns on H-atom transfer reactivity, enabling the oxidation of 9,10- dihydroanthracene to anthracene with concomitant formation of N 2 O and [Cu II ] 2 (μ-OH) 2 . These studies illustrate both the reductive coupling of NO at a single copper center and a way to harness the strong oxidizing power of nitric oxide via the neutral cis- hyponitrite [Cu](κ 2 -O 2 N 2 ).

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

Bayesian Framework for Multi-Timescale State Estimation in Low-Observable Distribution Systems

To support the smart grid paradigm, there has been a significant increase in sensor deployments and metering infrastructure in distribution systems. However, the measurements provided by these sensors and metering devices are typically sampled at different rates and could suffer from losses during the aggregation process. It is crucial to effectively reconcile the time-series measurements for a reliable state estimation. While weighted least squares has been the traditional approach for state estimation, sparsity-based approaches like matrix completion have become popular due to their superior performance in low-observability conditions. This paper proposes a Bayesian framework for both multi-timescale data aggregation and matrix completion based state estimation. Specifically, the multiscale time-series data aggregated from heterogenous sources are reconciled using a multitask Gaussian process that exploits the spatio-temporal correlations. Here, the resulting consistent timeseries alongwith the confidence bound on the imputations are fed into a Bayesian matrix completion method augmented with linearized power-flow constraints to accurately estimate the states in low-observability conditions. Results on three phase unbalanced IEEE 37 and IEEE 123 bus test systems reveal the superior performance of the proposed Bayesian framework. The computational complexity for the proposed Bayesian framework is also quantified.

42 ENGINEERING↗
DOE OSTI2020

Optimal polynomial based quantum eigenstate filtering with application to solving quantum linear systems

We present a quantum eigenstate filtering algorithm based on quantum signal processing (QSP) and minimax polynomials. The algorithm allows us to efficiently prepare a target eigenstate of a given Hamiltonian, if we have access to an initial state with non-trivial overlap with the target eigenstate and have a reasonable lower bound for the spectral gap. We apply this algorithm to the quantum linear system problem (QLSP), and present two algorithms based on quantum adiabatic computing (AQC) and quantum Zeno effect respectively. Both algorithms prepare the final solution as a pure state, and achieves the near optimal $\mathcal{\tilde{O}}$(dκlog(1/ϵ)) query complexity for a d -sparse matrix, where κ is the condition number, and ϵ is the desired precision. Neither algorithm uses phase estimation or amplitude amplification.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Chemical and structural investigation of the paroxetine-human serotonin transporter complex

Antidepressants target the serotonin transporter (SERT) by inhibiting serotonin reuptake. Structural and biochemical studies aiming to understand binding of small-molecules to conformationally dynamic transporters like SERT often require thermostabilizing mutations and antibodies to stabilize a specific conformation, leading to questions about relationships of these structures to the bonafide conformation and inhibitor binding poses of wild-type transporter. To address these concerns, we determined the structures of ΔN72/ΔC13 and ts2-inactive SERT bound to paroxetine analogues using single-particle cryo-EM and x-ray crystallography, respectively. We synthesized enantiopure analogues of paroxetine containing either bromine or iodine instead of fluorine. We exploited the anomalous scattering of bromine and iodine to define the pose of these inhibitors and investigated inhibitor binding to Asn177 mutants of ts2-active SERT. These studies provide mutually consistent insights into how paroxetine and its analogues bind to the central substrate-binding site of SERT, stabilize the outward-open conformation, and inhibit serotonin transport.

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

Consistency-Enhanced Evolution for Variable Selection Can Identify Key Chemical Information from Spectroscopic Data

In the last few decades, spectroscopic techniques such as near-infrared (NIR) spectroscopy have gained wide applications in several industries, such as the pharmaceutical, agricultural, oil, and gas industries. As a result, various soft sensors have been developed to predict sample properties from spectroscopic readings. Because the spectroscopic readings at different wavelengths, especially at the adjacent wavelengths, are highly correlated, it has been shown that variable selection could significantly improve a soft sensor’s prediction performance while reducing the model complexity. To improve the prediction performance, most variable selection methods focus on identifying the variables (i.e., wavelengths or wavelength segments) that are strongly correlated with the dependent variable. Although many successful applications have been reported, these variable selection methods do have their limitations. Specifically, the selected wavelengths sometimes show little connection to the chemical bounds or functional groups presenting in the sample. In addition, the selected variables can be quite sensitive to the choice of the training samples. In this work, we address these limitations from a different perspective: if a variable selection algorithm can identify the truly relevant input variables, it should consistently identify the same subset of variables regardless of the choice of the training samples. Therefore, we propose a variable selection method that aims to improve the consistency of variable selection resulting from different training samples. Furthermore, the new algorithm is termed consistency-enhanced evolution for variable selection (CEEVS). To demonstrate the performance and robustness of CEEVS, we compare the proposed method with three representative variable selection methods using five published NIR data sets. These case studies clearly demonstrate that by improving the variable selection consistency, we can not only achieve improved prediction performance, but also identify key chemical information from spectroscopic data.

42 ENGINEERING↗
DOE OSTI2025

Heterobinuclear Molecular Precursors Direct the Formation of Supported Subnanometer Cu–M Clusters with Tunable Catalytic Behavior

Subnanometer bimetallic clusters hold great promise for catalytic applications due to their unique electronic properties and high surface-to-volume ratios. However, precise control over their composition and size remains a major challenge, particularly for immiscible metal pairs. Here, we report a surface-anchored molecular approach for synthesizing ∼0.7–0.8 nm Cu–M (M = Ru, Mo, W, Fe) bimetallic clusters on mesoporous silica supports, using heterobinuclear N-heterocyclic carbene (NHC)-based complexes as precursors. The NHC ligand functionalized with an alkoxysilane anchor enables robust grafting to the silica interface. Controlled calcination and reduction lead to subnanometer clusters with tunable composition, dictated by the metal–metal bond stability in the precursor. In situ transmission electron microscopy reveals cluster growth proceeds via sintering of adjacent surface-bound units, while elevated temperatures above 300 °C triggering diffusion and phase separation. Catalytic testing in ethylene hydrogenation demonstrates composition-dependent activity and kinetics, with CuRu and CuW clusters exhibiting lower apparent activation energy barriers compared with monometallic Cu nanoparticles. This study establishes a generalizable strategy for the interfacial synthesis of alloyed clusters from molecular precursors and provides mechanistic insight into how precursor design governs nanostructure formation and catalytic behavior.

N-heterocyclic carbene↗
DOE OSTI2023

Generating Synthetic Time Series Photovoltaic Data with Real-World Physical Challenges and Noise for Use in Algorithm Test and Validation

The PV Fleet Data Initiative and other projects seek the develop algorithms for automated analysis of PV time series data for extraction of statistical information and other parameters of the data such as degradation rates, soiling loss information, tracker performance, clipping or curtailment, system availability and other valuable information. While there is a vast body of PV data available for application of said extraction algorithms it is difficult to validate these algorithms because the true parameters to be extracted are not known. There has been a wide use of synthetic data in the literature for algorithm validation but this synthetic data is typically very bounded by the problem or topic at hand. The PV Fleet Data Initiative project has demonstrated that real time series PV data almost always includes a host of data quality and physical problems that, in reality, any automated PV abstraction algorithm must handle appropriately. For this reason, this work describes the development of a complex synthetic PV times series data set that includes data quality and physical problems that have been experienced in real world PV data. The various quality and physical problems are documented in the synthetic data so that users can test the validity of various PV extraction algorithms as well as develop new algorithms to solve problems this data set can support.

14 SOLAR ENERGY↗
DOE OSTI2021

Ca2+ Effects on Fe(II) Interactions with Mn-Binding Sites in Mn-Depleted Oxygen-Evolving Complexes of Photosystem II and on Fe Replacement of Mn in Mn-Containing, Ca-Depleted Complexes

Fe(II) cations bind with high efficiency and specificity at the high-affinity (HA), Mn-binding site (termed the “blocking effect” since Fe blocks further electron donation to the site) of the oxygen-evolving complex (OEC) in Mn-depleted, photosystem II (PSII) membrane fragments (Semin et al. in Biochemistry 41:5854, 2002). Furthermore, Fe(II) cations can substitute for 1 or 2Mn cations (pH dependent) in Ca-depleted PSII membranes (Semin et al. in Journal of Bioenergetics and Biomembranes 48:227, 2016; Semin et al. in Journal of Photochemistry and Photobiology B 178:192, 2018). In the current study, we examined the effect of Ca2+ cations on the interaction of Fe(II) ions with Mn-depleted [PSII(-Mn)] and Ca-depleted [PSII(-Ca)] photosystem II membranes. We found that Ca2+ cations (about 50 mM) inhibit the light-dependent oxidation of Fe(II) (5 µM) by about 25% in PSII(-Mn) membranes, whereas inhibition of the blocking process is greater at about 40%. Blocking of the HA site by Fe cations also decreases the rate of charge recombination between QA- and YZ•+ from t1/2?=?30 ms to 46 ms. However, Ca2+ does not affect the rate during the blocking process. An Fe(II) cation (20 µM) replaces 1Mn cation in the Mn4CaO5 catalytic cluster of PSII(-Ca) membranes at pH 5.7 but 2 Mn cations at pH 6.5. In the presence of Ca2+ (10 mM) during the substitution process, Fe(II) is not able to extract Mn at pH 5.7 and extracts only 1Mn at pH 6.5 (instead of two without Ca2+). Measurements of fluorescence induction kinetics support these observations. Inhibition of Mn substitution with Fe(II) cations in the OEC only occurs with Ca2+ and Sr2+ cations, which are also able to restore oxygen evolution in PSII(-Ca) samples. Nonactive cations like La3+, Ni2+, Cd2+, and Mg2+ have no influence on the replacement of Mn with Fe. These results show that the location and/or ligand composition of one Mn cation in the Mn4CaO5 cluster is strongly affected by calcium depletion or rebinding and that bound calcium affects the redox potential of the extractable Mn4 cation in the OEC, making it resistant to reduction.

calcium↗
DOE OSTI2022

Model-based predictive control of multi-zone commercial building with a lumped building modelling approach

Here this study investigates the applicability of a lumped building modeling approach to model-based predictive control (MPC) to alleviate the complex modeling process of the grey-box multi-zone building model. Based on experimental data, two building models were estimated in this study. The detailed model as a reference case and a lumped model were estimated with decentralized and conventional approaches, respectively. Then, simulations were performed with two boundary conditions, including the comfort bound and electricity cost structure. The performances of the MPC with the detailed and lumped models were analyzed compared to the feedback control. More savings was achieved with a larger comfort bound and more aggressive electricity cost structure. The savings potential of the proposed lumped model approach was not as high as that of the detailed model. However, the proposed method yields good control performance, whose savings was approximately 8.6% over that of feedback control. These results suggest that the proposed method can be used to facilitate MPC implementation in multi-zone building applications.

42 ENGINEERING↗
DOE OSTI2021

DFT Mechanism Studies: Biomimetic 1,4-NADH Chemoselective, Co-factor Regeneration with [Cp*Rh(bpy)H] + , in Tandem with the Biocatalysis Pathways of a Core Model of the (HLADH)-Zn(II) Mediated Enzyme, in the Enantioselective Reduction of Achiral Ketones to Chiral S-Alcohols

In this study, Quantum Chemical (QC) calculations, utilizing Density Functional Theory (DFT), were performed to investigate the mechanistic aspects of the chemoselective catalyzed reaction of [Cp*Rh(bpy)H] + with the biomimetic NAD + analogues, N-benzylnicotinamide triflate, 1, and β-nicotinamide ribose-5'-methyl phosphate, 2, in the conversion to their 1,4-NADH analogues, 1,4-dihydro-N-benzylnicotinamide, 4, and β-1,4-dihydronicotinamide-5'-ribose methyl phosphate, 5. This reaction was in tandem with the 1,4-NADH dependent HLADH-Zn(II)- catalyzed reduction of achiral ketones to chiral S-alcohols. The [Cp*Rh(bpy)H] + complex, and not its equilibrium tautomer, [η 4 -Cp*HRh(bpy)] + , was found to control the hydride transfer during the biomimetic NAD + /1,4-NADH conversion, through the non-covalent interactions of the biomimetic co-factors with [Cp*Rh(bpy)H] + . The thermodynamics and kinetics for the chiral reduction of the Zn(II) bound ketones, 2-pentanone and 4-phenyl-2-butanone, with co-factor, 4, catalyzed by Zn(SCH 3 ) 2 (Imidazole), a core model of the Zn(II)-based catalytic center of HLADH, was also investigated by the evaluation of two possible reaction pathways: (1) formation of a ZnH from the C4-H hydride transfer of co-factor, 4, followed by reaction of the postulated ZnH with the bound 2-pentanone or 4-phenyl-2-butanone substrate, and (2), the direct C4-H transfer to the bound achiral ketone substrates, to provide the dominant chiral alcohols, S-2-pentanol or S-4-phenyl-2-butanol. The latter pathway was found most viable, and DFT calculations also revealed an essential η 2 -coordination of the 5,6 double bond of co-factor, 4, to the HLADH-Zn(II) metal ion center, upon imidazole decomplexation, providing an asymmetric differentiation of S-η 2 -5,6-1,4-NADH-Zn(II) binding. A proposed new paradigm for the Zn(II)'s non-innocent role in the HLADH-Zn(II) biocatalysis reduction mechanism, for enantioselective hydride transfer to a Zn(II) bound ketone, providing S-alcohols.

1,4 NADH co-factors↗
DOE OSTI2020

Low-energy magnons in the chiral ferrimagnet Cu 2 OSeO 3 : A coarse-grained approach

We report a comprehensive neutron scattering study of low energy magnetic excitations in the breathing pyrochlore helimagnetic Cu2OSeO3. Fully documenting the four lowest energy magnetic modes that leave the ferrimagnetic configuration of the “strong tetrahedra” intact (| ℏ ω| < 13 meV), we find gapless quadratic dispersion at the Γ point for energies above 0.2 meV, two doublets separated by 1.6(2) meV at the R point, and a bounded continuum at the X point. Our constrained rigid spin cluster model relates these features to Dzyaloshinskii-Moriya (DM) interactions and the incommensurate helical ground state. Combining conventional spin wave theory with a spin cluster form factor accurately reproduces the measured equal time structure factor through multiple Brillouin zones. An effective spin Hamiltonian describing complex anisotropic intercluster interactions is obtained.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Photoelectron spectroscopy and computational investigations of the electronic structures and noncovalent interactions of cyclodextrin-closo-dodecaborate anion complexes x-CD·B12X122- (x = a, ß, y; X = H, F)

We report a joint negative ion photoelectron spectroscopy (NIPES) and computational study on the electronic structures and noncovalent interactions of a series of cyclodextrin-closo-dodecaborate dianion complexes, ?-CD·B12X122- (? = a, ß, ?; X = H, F). The measured vertical / adiabatic detachment energies (VDEs / ADEs) are 1.15/0.93, 3.55/3.20, 3.90/3.60, and 3.85/3.60 eV for B12H122- and its a-, ß-, ?-CD complexes, respectively; while the corresponding values are 1.90/1.70, 4.00/3.60, 4.33/3.95, and 4.30/3.85 eV for the X = F case. These results show that the inclusion of B12X122- into the CD cavities greatly increase the electronic stability of the dianions. The effect of electronic stabilization for ß-CD is roughly the same as for ?-CD, both being considerably stronger than that for a-CD. Density functional theory (DFT) based geometry optimization reveals that B12X122- are inserted into CDs increasingly deeper from a-CD to ?-CD. The calculated VDEs and ADEs agree with the experiments well, particularly, reproducing the electron binding energy (EBE) trends. The molecular orbital analyses indicate that the most loosely bound photodetached electrons origin from the guest B12X122- moieties. In addition to a shift of all signals to larger EBE, significant changes in the signal patterns are observed. At low EBE, this is due to the splitting of highly degenerate B12X122- orbitals, while at high EBE, photodetachment from CD oxygens contributes to the new bands. The guest B12X122- and host CD nocovalent, size-specific interaction based on the independent gradient model (IGM) and energy decomposition analysis (EDA), is dominated by electrostatic interactions. The analysis further unravels unambiguiously the existence of dihydrogen bonding and how it affects the total energy that stabilizes the host-guest complexes of CDs·B12H122- compared to the general hydrogen bonding interaction in CDs·B12F122-. This work clearly exhibits strong influences on the electronic structures of dodecaborates upon clustering with CDs, with both size (a-, ß-, ?-) and molecular (X = H or F) specificities, thus providing critical molecular-level information on the cyclodextrin-closo-dodecaborate interactions of interest to medical applications, e.g. Boron neutron capature therapy. The NIPES experiments done at PNNL were supported by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Bioscience (X.-B.W.) and was performed at the EMSL, a national scientific user facility sponsored by DOE’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory. H.S. and Z.S. acknowledge the funding support of National Natural Science Foundation of China (Nos.11727810, 61720106009 and 21603074), the Science and Technology Commission of Shanghai Municipality (Nos. 19JC1412200), and the Program of Introducing Talents of Discipline to Universities 111 project (B12024). Z. L. thanks the China Scholarship Council (CSC) for financial support. We acknowledge the ECNU Multifunctional Platform for Innovation (001) and HPC Research Computing Team for providing computational and storage resources. J.W. acknowledges support from the Alexander von Humboldt foundation (Feodor Lynen Fellowship and Rückkehrerstipendium), a Freigeist fellowship of the Volkswagenfoundation and Prof. Vladimir A. Azov for helpful discussions.

Li, Zhipeng↗
DOE OSTI2021

Analysis and prediction of reaction kinetics using the degree of rate control

“Degree of rate control” (DRC) analysis provides a quantitative approach for analysing the kinetics of multi-step reaction mechanisms that has been widely applied to both heterogeneous and homogeneous catalysis research, as well as electrocatalysis. The DRC of any given transition state or intermediate is defined as a partial derivative such that it approximately equals the fractional increase in net rate to the product of interest per differential decrease in its standard-state free energy for that species (÷RT), holding constant the standard-state free energies of all other transition states and intermediates. Even very complex mechanisms usually have only a few species with non-zero DRCs and are thus the species whose interactions with the catalyst most strongly affect the net rate. These key DRC values thus offer a simple and intuitive route to optimize catalyst materials, especially with the assistance of computational methods like density functional theory (DFT). These high-DRC species are also the species whose energetics must be most accurately measured or calculated to achieve an accurate kinetic model for any reaction mechanism. In simple cases with a single “rate-determining step”, the DRC for its transition state (TS) is + 1. Catalyst-bound intermediates, on the other hand, often have negative DRCs equal to a small integer times their fractional occupancy of catalyst sites. The apparent activation energy equals a weighted average of the standard-state enthalpies (relative to reactants) of all the species (intermediates, transition states and products) in the reaction mechanism, each weighted by its DRC (+RT). It has been shown that the apparent transfer coefficient in electrocatalysis, an inverted form of the Tafel slope, is a weighted average of the number of electrons transferred to generate each intermediate or product species in the mechanism, weighted again by the DRC. Quantitative analysis of kinetic isotope effects (KIEs, or the ratio of net rates for different reactant isotopes) in complex mechanisms has shown that the logarithm of the KIE equals the weighted average over all species in the mechanism of the difference between the two isotopes in their standard-state free energies (÷RT), again weighted by the DRC. The reaction orders with respect to fluid-phase concentrations of reactants, products and intermediates have also been proven to be directly related to DRCs. Thus, there are numerous experimental observables which equate to short linear combinations of DRCs, so that combinations of experimental measurements might provide access to DRC values. Since its invention for transition states in 1994 and its generalization to include intermediates in 2009, the DRC has thus far mainly been calculated for microkinetic models based either entirely on DFT or on DFT with the key energies (i.e., those for high-DRC species) being fine-tuned to match experiments. The relationships summarized in this work provide new opportunities for using experiments earlier in the development and optimization of microkinetic models that require input from computational catalysis.

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

Quantum computational phase transition in combinatorial problems

Quantum Approximate Optimization algorithm (QAOA) aims to search for approximate solutions to discrete optimization problems with near-term quantum computers. As there are no algorithmic guarantee possible for QAOA to outperform classical computers, without a proof that bounded-error quantum polynomial time (BQP) ≠ nondeterministic polynomial time (NP), it is necessary to investigate the empirical advantages of QAOA. We identify a computational phase transition of QAOA when solving hard problems such as SAT—random instances are most difficult to train at a critical problem density. We connect the transition to the controllability and the complexity of QAOA circuits. Moreover, we find that the critical problem density in general deviates from the SAT-UNSAT phase transition, where the hardest instances for classical algorithms lies. Then, we show that the high problem density region, which limits QAOA’s performance in hard optimization problems (reachability deficits), is actually a good place to utilize QAOA: its approximation ratio has a much slower decay with the problem density, compared to classical approximate algorithms. Indeed, it is exactly in this region that quantum advantages of QAOA over classical approximate algorithms can be identified.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

GHB analogs confer neuroprotection through specific interaction with the CaMKIIα hub domain

Ca 2+ /calmodulin-dependent protein kinase II alpha subunit (CaMKIIα) is a key neuronal signaling protein and an emerging drug target. The central hub domain regulates the activity of CaMKIIα by organizing the holoenzyme complex into functional oligomers, yet pharmacological modulation of the hub domain has never been demonstrated. Here, using a combination of photoaffinity labeling and chemical proteomics, we show that compounds related to the natural substance γ-hydroxybutyrate (GHB) bind selectively to CaMKIIα. By means of a 2.2-Å x-ray crystal structure of ligand-bound CaMKIIα hub, we reveal the molecular details of the binding site deep within the hub. Furthermore, we show that binding of GHB and related analogs to this site promotes concentration-dependent increases in hub thermal stability believed to alter holoenzyme functionality. Selectively under states of pathological CaMKIIα activation, hub ligands provide a significant and sustained neuroprotection, which is both time and dose dependent. This is demonstrated in neurons exposed to excitotoxicity and in a mouse model of cerebral ischemia with the selective GHB analog, HOCPCA (3-hydroxycyclopent-1-enecarboxylic acid). Together, our results indicate a hitherto unknown mechanism for neuroprotection by a highly specific and unforeseen interaction between the CaMKIIα hub domain and small molecule brain-penetrant GHB analogs. This establishes GHB analogs as powerful tools for investigating CaMKII neuropharmacology in general and as potential therapeutic compounds for cerebral ischemia in particular.

59 BASIC BIOLOGICAL SCIENCES↗