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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Comparison of machine learning techniques to optimize the analysis of plutonium surrogate material via a portable LIBS device

The utilization of machine learning techniques has become commonplace in the analysis of optical emission spectra. These methods are often limited to variants of principal components analysis (PCA), partial-least squares (PLS), and artificial neural networks (ANNs). A plethora of other techniques exist and are well established in the world of data science, yet are seldom investigated for their use in spectroscopic problems. In this study, machine learning techniques were used to analyze optical emission spectra of laser-induced plasma from ceria pellets doped with silicon in order to predict silicon content. Additionally, a boosted regression ensemble model was created, and its predictive accuracy was compared to that of traditional PCA, PLS, and ANN regression models. Boosted regression tree ensembles yielded fits with R-squared (R2) values as high as 0.964 and mean-squared errors of prediction (MSEPs) as low as 0.074, providing the most accurate predictive model. Neural networks performed with slightly lower R2 values and higher MSEPs compared to the ensemble methods, thus indicating susceptibility to overfitting.

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

Robustness of the Stochastic Parameterization of Subgrid-Scale Wind Variability in Sea Surface Fluxes

Abstract High-resolution numerical models have been used to develop statistical models of the enhancement of sea surface fluxes resulting from spatial variability of sea surface wind. In particular, studies have shown that flux enhancement is not a deterministic function of the resolved state. Previous studies focused on single geographical areas or used a single high-resolution numerical model. This study extends the development of such statistical models by considering six different high-resolution models, four different geographical regions, and three different 10-day periods, allowing for a systematic investigation of the robustness of both the deterministic and stochastic parts of the data-driven parameterization. Results indicate that the deterministic part, based on regressing the unresolved normalized flux onto resolved-scale normalized flux and precipitation, is broadly robust across different models, regions, and time periods. The statistical features of the stochastic part of the model (spatial and temporal autocorrelation and parameters of a Gaussian process fit to the regression residual) are also found to be robust and not strongly sensitive to the underlying model, modeled geographical region, or time period studied. Best-fit Gaussian process parameters display robust spatial heterogeneity across models, indicating potential for improvements to the statistical model. These results illustrate the potential for the development of a generic, explicitly stochastic parameterization of sea surface flux enhancements dependent on wind variability.

Endo, Kota↗
DOE OSTI2022

In Silico Prediction of the Toxicity of Nitroaromatic Compounds: Application of Ensemble Learning QSAR Approach

In this work, a dataset of more than 200 nitroaromatic compounds is used to develop Quantitative Structure–Activity Relationship (QSAR) models for the estimation of in vivo toxicity based on 50% lethal dose to rats (LD 50 ). An initial set of 4885 molecular descriptors was generated and applied to build Support Vector Regression (SVR) models. The best two SVR models, SVR_A and SVR_B, were selected to build an Ensemble Model by means of Multiple Linear Regression (MLR). The obtained Ensemble Model showed improved performance over the base SVR models in the training set (R 2 = 0.88), validation set (R 2 = 0.95), and true external test set (R 2 = 0.92). The models were also internally validated by 5-fold cross-validation and Y-scrambling experiments, showing that the models have high levels of goodness-of-fit, robustness and predictivity. The contribution of descriptors to the toxicity in the models was assessed using the Accumulated Local Effect (ALE) technique. The proposed approach provides an important tool to assess toxicity of nitroaromatic compounds, based on the ensemble QSAR model and the structural relationship to toxicity by analyzed contribution of the involved descriptors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Comparing Designed Training Sets to Optimize Multivariate Regression Models for Pr, Nd, and Nitric Acid Using Spectrophotometry

Chemometric regression models were developed for the quantification of praseodymium (Pr, 0–1000 µg/mL), neodymium (Nd, 0–1000 µg/mL), and nitric acid (HNO 3 , 0.1–5 M) using spectrophotometry. Designed calibration sets were composed of 20 samples each: 10 model points and 10 lack-of-fit (LOF) points. The D-optimal designs effectively minimized the number of samples required to build models, and each design resulted in similar prediction performance, suggesting that statistical design of experiments can provide a reliable framework for selecting training set samples in three-variable systems. Partial least squares regression (PLSR) models were validated against a one-factor-at-a-time validation set composed of 125 samples (three variables, five levels). The top PLS-1 models resulted in average percent root mean square error of prediction error values of 3.5%, 1.7%, and 1.2% for Pr(III), Nd(III), and HNO 3 , respectively. Power set augmentations of the model and LOF samples were investigated to optimize the number of training set samples. PLSR models built using just required model points (10) had similar predictive capabilities as models including the LOF points (20) but with fewer samples. The number of validation samples was also varied systematically to learn how many samples are needed to validate regression models. This work addresses long-standing questions in the field of chemometrics to help make this approach amenable to the near-real-time quantification of hazardous species in remote settings.

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

The Radius of PSR J0740+6620 from NICER with NICER Background Estimates

We report a revised analysis for the radius, mass, and hot surface regions of the massive millisecond pulsar PSR J0740+6620, studied previously with joint fits to NICER and XMM-Newton data by Riley et al. (2021) and Miller et al. (2021). We perform a similar Bayesian estimation for the pulse-profile model parameters, except that instead of fitting simultaneously the XMM-Newton data, we use the best available NICER background estimates to constrain the number of photons detected from the source. This approach eliminates any potential issues in the cross-calibration between these two instruments, providing thus an independent check of the robustness of the analysis. The obtained neutron star parameter constraints are compatible with the already published results, with a slight dependence on how conservative the imposed background limits are. A tighter lower limit causes the inferred radius to increase, and a tighter upper limit causes it to decrease. We also extend the study of the inferred emission geometry to examine the degree of deviation from antipodality of the hot regions. We show that there is a significant offset to an antipodal spot configuration, mainly due to the non-half-cycle azimuthal separation of the two emitting spots. The offset angle from the antipode is inferred to be above 25° with 84% probability. This seems to exclude a centered-dipolar magnetic field in PSR J0740+6620.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Multiwavelength Observation Campaign of the TeV Gamma-Ray Binary HESS J0632 + 057 with NuSTAR, VERITAS, MDM, and Swift

HESS J0632+057 belongs to a rare subclass of binary systems that emit gamma rays above 100 GeV. It stands out for its distinctive high-energy light curve, which features a sharp "primary" peak and broader "secondary" peak. We present the results of contemporaneous observations by NuSTAR and VERITAS during the secondary peak between 2019 December and 2020 February, when the orbital phase (Φ) is between 0.55 and 0.75. NuSTAR detected X-ray spectral evolution, while VERITAS detected TeV emission. We fit a leptonic wind-collision model to the multiwavelength spectra data obtained over the four NuSTAR and VERITAS observations, constraining the pulsar spin-down luminosity and the magnetization parameter at the shock. Despite long-term monitoring of the source from 2019 October to 2020 March, the MDM observatory did not detect significant variation in Hα and Hβ line equivalent widths, an expected signature of Be-disk interaction with the pulsar. Furthermore, fitting folded Swift-XRT light-curve data with an intrabinary shock model constrained the orbital parameters, suggesting two orbital phases (at Φ D = 0.13 and 0.37), where the pulsar crosses the Be-disk, as well as phases for the periastron (Φ 0 = 0.30) and inferior conjunction (Φ IFC = 0.75). The broadband X-ray spectra with Swift-XRT and NuSTAR allowed us to measure a higher neutral hydrogen column density at one of the predicted disk-passing phases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Skyrmion‐Excited Spin‐Wave Fractal Networks

Magnetic skyrmions exhibit unique, technologically relevant pseudo-particle behaviors which arise from their topological protection, including well-defined, 3D dynamic modes that occur at microwave frequencies. During dynamic excitation, spin waves are ejected into the interstitial regions between skyrmions, creating the magnetic equivalent of a turbulent sea. However, since the spin waves in these systems have a well-defined length scale, and the skyrmions are on an ordered lattice, ordered structures from spin-wave interference can precipitate from the chaos. This work uses small-angle neutron scattering (SANS) to capture the dynamics in hybrid skyrmions and investigate the spin-wave structure. Performing simultaneous ferromagnetic resonance and SANS, the diffraction pattern shows a large increase in low-angle scattering intensity, which is present only in the resonance condition. This scattering pattern is best fit using a mass fractal model, which suggests the spin waves form a long-range fractal network. The fractal structure is constructed of fundamental units with a size that encodes the spin-wave emissions and are constrained by the skyrmion lattice. Furthermore, these results offer critical insights into the nanoscale dynamics of skyrmions, identify a new dynamic spin-wave fractal structure, and demonstrate SANS as a unique tool to probe high-speed dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Carbon‐13 Hyperpolarization of α‐Ketocarboxylates with Parahydrogen in Reversible Exchange

Abstract Signal Amplification by Reversible Exchange (SABRE) is a relatively simple and fast hyperpolarization technique that has been used to hyperpolarize the α‐ketocarboxylate pyruvate, a central metabolite and the leading hyperpolarized MRI contrast agent. In this work, we show that SABRE can readily be extended to hyperpolarize 13 C nuclei at natural abundance on many other α‐ketocarboxylates. Hyperpolarization is observed and optimized on pyruvate (P 13C =17 %) and 2‐oxobutyrate (P 13C =25 %) with alkyl chains in the R‐group, oxaloacetate (P 13C =11 %) and alpha‐ketoglutarate (P 13C =13 %) with carboxylate moieties in the R group, and phenylpyruvate (P 13C =2 %) and phenylglyoxylate (P 13C =2 %) with phenyl rings in the R‐group. New catalytically active SABRE binding motifs of the substrates to the hyperpolarization transfer catalyst – particularly for oxaloacetate – are observed. We experimentally explore the connection between temperature and exchange rates for all of these SABRE systems and develop a theoretical kinetic model, which is used to fit the hyperpolarization build‐up and decay during SABRE activity.

McBride, Stephen J. [Department of Chemistry North↗
DOE OSTI2021

Characterizing Topological Order with Matrix Product Operators

One of the most striking features of gapped quantum phases that exhibit topological order is the presence of long-range entanglement that cannot be detected by any local order parameter. The formalism of projected entangled-pair states is a natural framework for the parameterization of gapped ground state wavefunctions which allows one to characterize topological order in terms of the virtual symmetries of the local tensors that encode the wavefunction. In their most general form, these symmetries are represented by matrix product operators acting on the virtual level, which leads to a set of algebraic rules characterizing states with topological quantum order. This construction generalizes the concepts of $\mathsf G$- and twisted injectivity; the corresponding matrix product operators encode all topological features of the theory and provide a complete picture of the ground state manifold on the torus. We show how the string-net models of Levin and Wen fit within this formalism and in doing so provide a particularly intuitive interpretation of the pentagon equation for F-symbols as the pulling of matrix product operators through the string-net tensor network. Our approach paves the way to finding novel topological phases beyond string nets and elucidates the description of topological phases in terms of entanglement Hamiltonians and edge theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Time dependent chlorination of CeO 2 , La 2 O 3 and Nd 2 O 3 by ZrCl 4 dissolved in eutectic LiCl–KCl

Partial chlorination of CeO 2 , La 2 O 3 , and Nd 2 O 3 was achieved using ZrCl 4 dissolved in molten LiCl-KCl at 450°C over a period of 4-5 hr. ZrCl 4 was pre-volatilized into an argon stream to maintain a constant vapor pressure for equilibration with the salt. This approach was effective at maintaining the ZrCl 4 concentration at the solubility limit of 1.3 mol% in the molten salt throughout the duration of two of the chlorination experiments and within about 60% of the solubility limit in the third experiment. Based on the analysis of salt samples, fractional conversion after four hours of reaction for CeO 2 , and five hours for La 2 O 3 , and Nd 2 O 3 were calculated to be 0.97, 0.28, and 0.65 respectively. Assuming a shrinking core diffusion-limited model, the diffusivity of ZrCl 4 through the hypothesized ZrO 2 layer was calculated for the chlorination of CeO 2 , La 2 O 3 , and Nd 2 O 3 were 1.76 x 10 -10 cm 2 /sec, 7.85 x 10 -12 cm 2 /sec, and 7.42 x 10 -12 cm 2 /sec, respectively. Given the extremely low values calculated for diffusivity, it was concluded that the process is chemical reaction rate limited and that a complete reaction of each rare earth oxide could be achieved. Furthermore, a chemically controlled shrinking core model was shown to also fit the experimental data closely.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

First-principles and cluster expansion study of the effect of magnetism on short-range order in Fe–Ni–Cr austenitic stainless steels

Short-range order (SRO), the regular and predictable arrangement of atoms over short distances, alters the mechanical properties of technologically relevant structural materials such as medium/high entropy alloys and austenitic stainless steels. In this study, we present a generalized spin cluster expansion (CE) model and show that magnetism is a primary factor influencing the level of SRO present in austenitic Fe-Ni-Cr alloys. The spin CE consists of a chemical cluster expansion combined with an Ising model for Fe-Ni-Cr austenitic alloys. It explicitly accounts for local magnetic exchange interactions, thereby capturing the effects of finite temperature magnetism on SRO. Model parameters are obtained by fitting to a first-principles data set comprising both chemically and magnetically diverse FCC configurations. The magnitude of the magnetic exchange interactions are found to be comparable to the chemical interactions. Compared to a conventional implicit magnetism CE built from only magnetic ground state configurations, the spin CE shows improved performance on several experimental benchmarks over a broad spectrum of compositions, particularly at higher temperatures due to the explicit treatment of magnetic disorder. We find that SRO is strongly influenced by alloy Cr content, since Cr atoms prefer to align antiferromagnetically with nearest neighbors but become magnetically frustrated with increasing Cr concentration. Using the spin CE, we predict that increasing the Cr concentration in typical austenitic stainless steels promotes the formation of SRO and increases order-disorder transition temperatures. Furthermore, this study underscores the significance of considering magnetic interactions explicitly when exploring the thermodynamic properties of complex transition metal alloys. It also highlights guidelines for customizing SRO through adjustments of alloy composition.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A mathematical approach to using the forgetting curve to evaluate experience and training factors in human reliability analysis

Traditional human reliability analysis (HRA) methods have difficulty dealing with the dynamic nature of factors such as time and rely on static and expert-judgment-based assessments of performance-shaping factors (PSFs) across limited levels. In this study, we introduce a mathematical approach for dynamically evaluating the experience and training PSF. Our proposed method integrates the psychological concept of the “forgetting curve” to evaluate how PSFs are impacted by the number of trainings and the time elapsed since training. To confirm the validity of the model, we provide experimental data fitted by identifying the quantitative relationship between training and human performance. This research enables dynamic and objective assessments, thus reducing reliance on subjective expert judgment and improving the accuracy of HRA.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Energetics of hydroxylbastnäsite solid solutions, La 1-$\chi$ Nd $\chi$ CO 3 OH

Bastnäsites (LnCO 3 (F,OH)) are a group of common rare earth elements (REE)-bearing minerals and are one of the primary global sources of REE. Due to the chemical similarities among REE, bastnӓsites tend to occur as solid solutions instead of end members in REE containing ores. To better understand the processes and the mechanisms of formation of such deposits, it is essential to determine the thermodynamic properties of bastnӓsites, including hydroxylbastnӓsite (LnCO 3 OH) solid solutions. In this work, we performed detailed structural and calorimetric investigations on synthetic hexagonal La–Nd hydroxylbastnӓsite (La 1-$\chi$ NdCO 3 OH, $\chi$ = 0, 0.25, 0.5, 0.75, 1) solid solutions. X-ray diffraction confirms the crystal structure of the solid solution series in the $\ P$6 space group, and pair distribution function (PDF) analysis reveals local bonding environments characterized by three different types of 9-coordinated metal-oxygen polyhedra. Unit cell parameters of La1–xNdxCO3OH exhibit a nearly linear relation with the Nd content x, suggesting a random distribution of La and Nd in the structure. Their standard enthalpies of formation (Δ$\ H$° f ) were determined by high temperature oxide melt drop solution calorimetry, from which the enthalpies of mixing (Δ$\ H$ mix ) were derived. The Δ$\ H$ mix can be fitted by a regular solution model with an interaction parameter of 12.58 ± 0.16 kJ/mol, suggesting enthalpic metastability of La1–xNdxCO3OH relative to the two endmembers. Combining entropy and enthalpy, we further estimated the Gibbs free energies of mixing (Δ$\ G$ mix ) at relevant temperatures, revealing favorable temperatures under which the intermediate La 1-$\chi$ NdCO 3 OH phases can be stabilized. Such entropy-driven stabilization, as is consistent with our geochemical modeling results, may explain the enhancement of thermal stability of the solid solutions in nature. Additionally, the temperature range constrained from this study may be used to estimate the thermal history of REE bastnӓsite deposit.

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

A time-varying vulnerability index for COVID-19 in New Mexico, USA using generalized propensity scores

The coronavirus disease (COVID-19) pandemic has highlighted systemic inequities in the United States and resulted in a larger burden of negative social outcomes for marginalized communities. New Mexico, a state in the southwestern US, has a unique population with a large racial minority population and a high rate of poverty that may make communities more vulnerable to negative social outcomes from COVID-19. To identify which communities may be at the highest relative risk, we created a county-level vulnerability index. After the first COVID-19 case was reported in New Mexico on March 11, 2020, we fit a generalized propensity score model that incorporates sociodemographic factors to predict county-level viral exposure and thus, the generic risk to negative social outcomes such as unemployment or mental health impacts. We used four static sociodemographic covariates important for the state of New Mexico—population, poverty, household size, and minority population—and weekly cumulative case counts to iteratively run our model each week and normalize the exposure score to create a time-varying vulnerability index. We found the relative vulnerability between counties varied in the first eight weeks from the initial COVID-19 case before stabilizing. This framework for creating a location-specific vulnerability index in response to an ongoing disaster may be used as a quick, deployable metric to inform health policy decisions such as allocating state resources to the county level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Production of polyacrylonitrile/ionic covalent organic framework hybrid nanofibers for effective removal of chromium(VI) from water

Hexavalent Cr(VI) found in industrial wastewater is a proven carcinogen which causes serious health issues in humans around the world. This study presents a novel method to enhance the Cr(VI) oxyanion removal from wastewater by polyacrylonitrile (PAN) nanofibers through incorporation of a guanidinium-based ionic covalent organic framework (BT-DG) in the nanofibers structure. In this work, simple electrospinning technique was employed to produce PAN nanofibers and BT-DG was synthesized through condensation between benzene-1,3,5-tricarbaldehyde and N,N'-diaminoguanidine monohydrochloride. In-situ polymerization of BT-DG onto PAN nanofibers resulted in generation of hybrid PAN-BT-DG nanofibers. This modified PAN-BT-DG was characterized by obtaining its point of zero charge (PZC), differential scanning calorimeter (DSC), scanning electron microscopy (SEM) morphology and surface elements and oxidation states by X-ray photoelectron spectroscopy (XPS). PAN-BT-DG exhibited positive surface charge below pH 4, making it an outstanding adsorbent, for Cr(VI) removal. Cr(VI) adsorption onto PAN-BT-DG followed pseudo second order kinetics and adsorption data fitted well to Freundlich isotherm model. Highest Cr(VI) removal was obtained at 55 °C with a maximum Langmuir adsorption capacity of 173 mg/g at pH 3. Kinetic studies revealed that Cr(VI) adsorption onto PAN-BT-DG is endothermic and thermodynamically feasible. Desorption studies were conducted on PAN-BT-DG using 1 M NaOH as the stripping solvent and PAN-BT-DG exhibited excellent regeneration after five consecutive cycles.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Behavior of astatine and bismuth in non-conventional solvents: Extraction into imidazolium-based ionic liquid and methyl anthranilate with active pharmaceuticals binary mixtures from nitric acid media

Astatine is one of the least chemically studied elements and its behavior in the presence of non- conventional solvents has not been investigated before. This work considers both hydrophobic ionic liquids and binary mixtures as alternatives to conventional solvents. The study is based on the extraction of astatine and bismuth (target material required to produce astatine) into imidazolium-based ionic liquid, and binary mixtures formed by active pharmaceuticals (ibuprofen, lidocaine) and a food grade ingredient (methyl anthranilate). It is shown that both the ionic liquid and binary mixtures can successfully extract At from nitric acid media, but extraction of Bi into the ionic liquid is very inefficient, resulting in a good separation factor for these two elements in the entire studied acidity range. Extraction of At into binary mixtures is very efficient, having distribution ratio values as high as 1000, while the behavior of Bi under these conditions depends on the composition of the mixture. Furthermore, a mathematical model has been developed to fit both At and Bi experimental data and applied to determine corresponding thermodynamic extraction constants.

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

LiMo 8 O 10 : Polar Crystal Structure with Infinite Edge-Sharing Molybdenum Octahedra

Here, polycrystalline LiMo 8 O 10 was prepared in a sealed Mo crucible at 1380 °C for 48 h using the conventional high-temperature solid-state method. The polar tetragonal crystal structure (space group I4 1 md) is confirmed based on the Rietveld refinement of powder neutron diffraction and 7 Li/ 6 Li solid-state NMR. The crystal structure features infinite chains of Mo 4 O 5 (i.e., Mo 2 Mo 4/2 O 6/2 O 6/3 ) as a repeat unit containing edge-sharing Mo 6 octahedra with strong Mo–Mo metal bonding along the chain. X-ray absorption near-edge spectroscopy of the Mo-L 3 edge is consistent with the formal Mo valence/configuration. Magnetic measurements reveal that LiMo 8 O 10 is paramagnetic down to 1.8 K. Temperature-dependent resistivity [ρ(T)] measurement indicates a semiconducting behavior that can be fitted with Mott’s variable range hopping conduction mechanism in the temperature range of 215 and 45 K. The ρ(T) curve exhibits an exponential increase below 5 K with a large ratio of ρ 1.8 /ρ 300 = 435. LiMo 8 O 10 shows a negative field-dependent magnetoresistance between 2 and 25 K. Heat capacity measurement fitted with the modified Debye model yields the Debye temperature of 365 K.

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

Elucidation of Marcus Relationships for Hydride Transfer Reactions Involving Transition Metal Hydrides

The rate of hydride transfer from three Ir hydride complexes of the type Cp*Ir( R bpy)H + (Cp* = C 5 Me 5 ; R bpy = 4,4′-R-2,2′-bipyridine, R = OMe, H, CO 2 Me) to six N-methylacridinium ( R Acr + ) acceptors with electronically different substituents in the 2- or 2,7-positions were measured. Using the thermodynamic hydricity of the donors and the hydride affinity of the acceptors the thermodynamic driving forces for hydride transfer were determined. Brønsted plots, which correlate kinetic and thermodynamic hydricity, demonstrate distinct linear free energy relationships for each complex, with different Brønsted α values. Thus, at the same driving force hydride transfer from Cp*Ir( OMe bpy)H + is faster than for Cp*Ir(bpy)H + or Cp*Ir( CO2Me bpy)H + . Experimental and computational analyses are consistent with a concerted hydride transfer mechanism for all Ir complexes. As the thermodynamic driving force increases an earlier transition state is observed and all transition states also include π-stacking interactions between the donor and acceptor, which likely contribute to the different α values. The experimental data fits well to the Marcus model, enabling the determination of reorganization energies (λ) that range from 58 to 69 kcal mol -1 . These are lower than λ values for hydride transfer reactions involving organic donors and acceptors. This work provides a rare example of the correlation of kinetic and thermodynamic hydricity using only experimental data and shows that hydride transfer reactions involving metal hydrides can follow Marcus theory. Furthermore, the findings offer insight into controlling metal-catalyzed hydride transfer reactions, which is valuable for designing improved systems for a range of transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗