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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Enhancement in magnetocaloric properties of holmium chromite by gadolinium substitution

HoCrO{sub 3}, Ho{sub 0.67}Gd{sub 0.33}CrO{sub 3}, and GdCrO{sub 3} bulk powder samples were prepared by citrate route. The phase purity and the structural properties of the samples were examined by x-ray diffraction and Raman spectroscopic measurements. The dc magnetization data revealed that the Cr{sup 3+} ordering temperatures (Néel temperature) for the HoCrO{sub 3}, Ho{sub 0.67}Gd{sub 0.33}CrO{sub 3}, and GdCrO{sub 3} samples are 140 K, 148 K, and 167 K, respectively, while the ac magnetization data revealed that the rare-earth (Ho) ordering occurs at ∼8 K for HoCrO{sub 3} and Ho{sub 0.67}Gd{sub 0.33}CrO{sub 3} samples. Temperature-induced magnetization reversal and spin reorientation were observed in GdCrO{sub 3} bulk sample, which depends on applied magnetic field and disappears at ∼1500 Oe and 500 Oe, respectively. By fitting the dc magnetic data with Curie-Weiss law, the effective magnetic moments were calculated to be 11.66 μ{sub B}, 10.23 μ{sub B}, and 9.90 μ{sub B} for the HoCrO{sub 3}, Ho{sub 0.67}Gd{sub 0.33}CrO{sub 3}, and GdCrO{sub 3} samples, respectively. The isothermal magnetization data showed that the magnetic behavior changed from canted antiferromagnetic in low temperature region (below Néel temperature) to paramagnetic at high temperature. It was found that Gd substitution considerably improves the magnetocaloric effect of HoCrO{sub 3}. Pure GdCrO{sub 3} bulk sample showed giant magnetocaloric entropy change (31.6 J/kg K at temperature ∼5 K and at ∼70 kOe), which is higher than that for polycrystalline RMnO{sub 3}, RCrO{sub 3}, and RFeO{sub 3} bulk powder samples. This renders GdCrO{sub 3} useful for potential applications in low-temperature magnetic refrigeration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Influence of Zn on magnetocaloric effect in (0.95)La{sub 0.7}Sr{sub 0.3}MnO{sub 3}/Ni{sub 1−x}Zn{sub x}Fe{sub 2}O{sub 4} ceramic composites

Highlights: • Synthesis of magnetic ceramic composites. • Magnetization of dual phase ceramics. • Magnetic entropy change in (0.95)La{sub 0.7}Sr{sub 0.3}MnO{sub 3}/(0.05)Ni{sub 1−x}Zn{sub x}Fe{sub 2}O{sub 4} solid solution. - Abstract: We report the magnetic and magnetocaloric properties of (0.95)La{sub 0.7}Sr{sub 0.3}MnO{sub 3}/(0.05)Ni{sub 1−x}Zn{sub x}Fe{sub 2}O{sub 4} (x = 0.0, 0.1, 0.3, and 0.5) ceramic composites. The composite samples with nominal compositions were prepared using the conventional solid-state reaction method. The phase purity and structure were confirmed by using X-ray diffraction. Temperature dependent magnetization measurements and Arrott analysis reveal second order of magnetic phase transition in the composite samples. A maximum in magnetic entropy change of ∼0.75 J/kg K at 1 T has been observed in (0.95)La{sub 0.7}Sr{sub 0.3}MnO{sub 3}/(0.05)NiFe{sub 2}O{sub 4} sample. The values of magnetic entropy change of these composites make them attractive for potential applications. These composite samples may consider as potential material for magnetic refrigeration near room temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Structural, magnetic, magneto-caloric and Mössbauer spectral study of Tb{sub 2}Fe{sub 17} compound synthesized by arc melting

We have synthesized the intermetallic Tb{sub 2}Fe{sub 17} compound in hexagonal crystal structure by arc-melting without annealing. X-ray diffraction pattern has been refined by Rietveld method. The crystal structure is hexagonal with P6{sub 3}/mmc space group (Th{sub 2}Ni{sub 17}-type). The Mössbauer spectrum of Tb{sub 2}Fe{sub 17} compound has been analyzed with seven magnetic sextets assigned to the inequivalent crystallographic sites. The temperature dependence of magnetization data revealed that Tb{sub 2}Fe{sub 17} exhibits a second-order ferromagnetic to paramagnetic phase transition in the vicinity of Curie temperature (T{sub C}=412 K). The relative cooling power around the magnetic transition and the Arrott plots are also reported. - Graphical abstract: A 3D surface showing the temperature and applied magnetic field dependencies of the magnetization for Tb{sub 2}Fe{sub 17} compound (left). Rietveld analysis of the XRD pattern (right). Crystal structure for the hexagonal P6{sub 3}/mmc Tb{sub 2}Fe{sub 17} (bottom). Display Omitted - Highlights: • Tb{sub 2}Fe{sub 17} single-phase synthesized by simple arc-melting without any heat treatment. • The crystal structure is hexagonal with P6{sub 3}/mmc space group. • The magnetic entropy change of the sample was determined by Maxwell relation. • Hyperfine parameters, magnetic and magnetocaloric properties were studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1980

A hill-sliding strategy for initialization of Gaussian clusters in the multidimensional space

A hill sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimate of sample data for the first step of iterative unsupervised classification. Each cluster was assumed to posses a unimodal normal distribution. A clustering function proposed distinguished elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with LANDSAT multispectral scanner data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill sliding clustering technique developed herein has the potential applicability to decomposition any multivariate mixture distribution into a number of unimodal distributions when an appropriate distribution function to the data set is employed.

Park, J. K.↗
DOE OSTI2025

Biased degenerate ground-state sampling of small Ising models with converged quantum approximate optimization algorithm

The quantum alternating operator ansatz, a generalization of the quantum approximate optimization algorithm (QAOA), is a quantum algorithm used for approximately solving combinatorial optimization problems. QAOA typically uses the transverse field mixer as the driving Hamiltonian. One of the interesting properties of the transverse field driving Hamiltonian is that it results in nonuniform sampling of degenerate ground states of optimization problems. In this study, we numerically examine the fair sampling properties of the transverse field mixer QAOA, and Grover mixer QAOA (GM-QAOA), which provides theoretical guarantees of fair sampling of degenerate optimal solutions, up to a large enough p such that the mean expectation value converges to an optimal approximation ratio of 1. This comparison is performed with high-quality heuristically computed, but not necessarily optimal, QAOA angles, which give strictly monotonically improving solution quality as p increases. These angles are computed using the Julia based numerical simulation software JuliQAOA. Fair sampling of degenerate ground states is quantified using the Shannon entropy of the ground-state amplitudes distribution. The fair sampling properties are reported on several quantum signature Hamiltonians from previous quantum annealing fair sampling studies. Small random fully connected spin glasses are shown, which exhibit exponential suppression of some degenerate ground states with transverse field mixer QAOA. The transverse field mixer QAOA simulations show that some problem instances clearly saturate the Shannon entropy of 0 with a maximally biased distribution that occurs when the learning converges to an approximation ratio of 1 while other problem instances never deviate from a maximum Shannon entropy (uniform distribution) at any p step. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Bayesian Regression of Thermodynamic Models of Redox Active Materials

Finding a suitable functional redox material is a critical challenge to achieving scalable, economically viable technologies for storing concentrated solar energy in the form of a defected oxide. Demonstrating e ectiveness for thermal storage or solar fuel is largely accomplished by using a thermodynamic model derived from experimental data. The purpose of this project is to test the accuracy of our regression model on representative data sets. Determining the accuracy of the model includes parameter tting the model to the data, comparing the model using di erent numbers of param- eters, and analyzing the entropy and enthalpy calculated from the model. Three data sets were considered in this project: two demonstrating materials for solar fuels by wa- ter splitting and the other of a material for thermal storage. Using Bayesian Inference and Markov Chain Monte Carlo (MCMC), parameter estimation was preformed on the three data sets. Good results were achieved, except some there was some deviations on the edges of the data input ranges. The evidence values were then calculated in a variety of ways and used to compare models with di erent number of parameters. It was believed that at least one of the parameters was unnecessary and comparing evidence values demonstrated that the parameter was need on one data set and not signi cantly helpful on another. The entropy was calculated by taking the derivative in one variable and integrating over another. and its uncertainty was also calculated by evaluating the entropy over multiple MCMC samples. Afterwards, all the parts were written up as a tutorial for the Uncertainty Quanti cation Toolkit (UQTk).

36 MATERIALS SCIENCE↗
DOE OSTI2025

The Poisson tensor completion non-parametric differential entropy estimator

We introduce the Poisson tensor completion (PTC) estimator, a non-parametric differential entropy estimator. The PTC estimator leverages inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial Poisson process. The Poisson tensor decomposition leads to a completion of the intensity measure over all bins—including those containing few to no samples—and leads to our proposed PTC differential entropy estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values and so can be safely used directly in entropy estimation. Our estimator is the first tensor-based estimator that exploits the underlying spatial Poisson process related to the histogram explicitly when estimating the probability density with low-rank tensor decompositions for the purpose of tensor completion. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

42 ENGINEERING↗
NASA NTRS1981

Pulsations in total columnar electron content

Radio signals from the ATS 6 beacon received at Boulder reveal small-amplitude, quasi-sinusoidal fluctuations with periods in the range of 10 to 50 s. Visual comparisons of these data (116 events for October 1974 to April 1975) shows a good correspondence with simultaneous geomagnetic pulsations at Boulder in two thirds of the cases for which Boulder magnetograms were available, but they do not necessarily correspond with magnetic pulsations on ATS 6. Spectral analyses, by the method of maximum entropy, were made on sample records. The principal results are the following: (1) The occurrence of the pulsations is higher on magnetically disturbed days. (2) The maximum likelihood of occurrence is around 2100 UT (1400 LT). (3) The dominant spectrum peaks of the radio fluctuations and geomagnetic field on the ground generally coincide. Cases are found also in which temporal characteristics of the spectra are similar. These results indicate a close association of the radio fluctuations with the Pc 3-4 type pulsations of the geomagnetic field on the ground. It is suggested that the radio fluctuations originate mainly in the F region of the ionosphere, while some of them could be due to plasmapause effects.

Okuzawa, T.↗
DOE OSTI2024

MENT-Flow: maximum-entropy phase space tomography using normalizing flows

Generative models can be trained to reproduce low-dimensional projections of high-dimensional phase space distributions. Normalizing flows are generative models that parameterize invertible transformations, allowing exact probability density evaluation and sampling. Consequently, flows are unbiased entropy estimators and could be used to solve the high-dimensional maximum-entropy tomography (MENT) problem. In this work, we evaluate a flow-based MENT solver (MENT-Flow) against exact maximum-entropy solutions and Minerbo's iterative MENT algorithm in two dimensions.

Hoover, Austin↗
NASA NTRS1973

Suitability of the rare-earth compounds Dy2Ti2O7 and Gd3Al5O12 for low temperature (4K-20K) magnetic refrigeration cycle

Measurements were made of the magnetic entropy and magnetization of powered samples of the compounds Dy2Ti2O7 and Gd3Al5O12. The magnetization was measured for temperatures at and below 4.2 K, in applied fields ranging to 7.0 tesla. Isothermal changes in magnetic entropy were measured for temperatures from 1.2 to 20 K, in applied fields up to 10 tesla. The results of the measurements are consistent with a doublet ground state for Dy2Ti2O7, and an eight-fold degenerate ground state for Gd3Al5O12. Absolute values of magnetic entropy have been obtained at the lower temperatures, permitting the isotherms to be properly located in the S-H plane with the use of adiabatic magnetization data. The iso-field lines in the S-T plane were determined. The results indicate that Dy2Ti2O7 can absorb a maximum of 71 + or - 4 joules/kg of heat at 4.2 K, while Gd3Al5O12 can absorb 233 + or - joules/kg at the same temperature. The large difference between the two is most likely a result of crystal field interactions in the dysoprosium compound. Both materials can be cycled adiabatically between 4.2 and 20 K.

Flood, D. J.↗
DOE OSTI2023

Comparison of quantum advantage experiments using random circuit sampling

Random circuit sampling, the task of sampling bit strings from a random unitary operator, has been implemented to demonstrate quantum advantage on the Sycamore quantum processor with 53 qubits and on the Zuchongzhi quantum processor with 56 and 61 qubits. Recently, it was claimed that classical computers using tensor network simulation could catch on to current noisy quantum processors for random circuit sampling. While the linear cross-entropy benchmark fidelity was used to certify all these claims, it may not capture statistical properties of outputs in detail. Here, we compare the bit strings sampled from classical computers using tensor network simulation by Pan et al. [F. Pan, K. Chen, and P. Zhang, Phys. Rev. Lett. 129, 090502 (2022)] and by Kalachev et al. [G. Kalachev, P. Panteleev, P. Zhou, and M.-H. Yung, arXiv:2112.15083] with the bit strings from the Sycamore quantum processor. It is shown that all of Kalachev et al.'s samples passed the NIST random number tests. The heat maps of bit strings show that Pan et al.'s and Kalachev et al.'s samples are quite different from the Sycamore or Zuchongzhi samples. The analysis with the Marchenko-Pastur distribution and the Wasssertein distances demonstrates that Kalachev et al.'s samples are statistically closer to the Sycamore samples than Pan et al.'s while the three datasets have similar values for the linear cross-entropy fidelity. In conclusion, our finding implies that further study is needed to certify or beat the claims of quantum advantage using random circuit sampling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Bayesian Entropy Neural Networks for physics-aware prediction

This article addresses the need for deep learning models to integrate well-defined constraints into their outputs, driven by their application in surrogate models, learning with limited data and partial information, and scenarios requiring flexible model behavior to incorporate non-data sample information. We introduce Bayesian Entropy Neural Networks (BENN), a framework grounded in Maximum Entropy (MaxEnt) principles, designed to impose constraints on Bayesian Neural Network (BNN) predictions. BENN is capable of constraining not only the predicted values but also their derivatives and variances, ensuring a more robust and reliable model output. To achieve simultaneous uncertainty quantification and constraint satisfaction, we employ the method of multipliers approach. This allows for the concurrent estimation of neural network parameters and the Lagrangian multipliers associated with the constraints. Our experiments, spanning diverse applications such as beam deflection modeling and microstructure generation, demonstrate the effectiveness of BENN. The results highlight significant improvements over traditional BNNs and showcase competitive performance relative to contemporary constrained deep learning methods.

14 SOLAR ENERGY↗
DOE OSTI2022

Investigation of Molecular Diffusion at Block Copolymer Thin Films Using Maximum Entropy Method-Based Fluorescence Correlation Spectroscopy and Single Molecule Tracking

Fluorescence correlation spectroscopy (FCS) has been widely used to investigate molecular diffusion behavior in various samples. The use of the maximum entropy method (MEM) for FCS data analysis provides a unique means to determine multiple distinct diffusion coefficients without a priori assumption of their number. Comparison of the MEM-based FCS method (MEM-FCS) with another method will reveal its utility and advantage as an analytical tool to investigate diffusion dynamics. Herein, we measured diffusion of fluorescent probes doped into nanostructured thin films using MEM-FCS, and validated the results with single molecule tracking (SMT) data. The efficacy of the MEM code employed was first demonstrated by analyzing simulated FCS data for systems incorporating one and two diffusion modes with broadly distributed diffusion coefficients. The MEM analysis accurately afforded the number of distinct diffusion modes and their mean diffusion coefficients. These results contrasted with those obtained by fitting the simulated data to conventional two-component and anomalous diffusion models, which yielded inaccurate estimates of the diffusion coefficients. Subsequently, the MEM analysis was applied to FCS data acquired from hydrophilic dye molecules incorporated into microphase-separated polystyrene-block-poly(ethylene oxide) (PS-b-PEO) thin films characterized under a water-saturated nitrogen atmosphere. The MEM analysis revealed distinct fast and slow diffusion components attributable to molecules diffusing on the film surface and inside the film, respectively. SMT studies of the same materials yielded trajectories for mobile molecules that appear to follow the curved PEO microdomains. Diffusion coefficients obtained from the SMT data were consistent with those obtained for the slow diffusion component detected by MEM-FCS. Furthermore, these results highlight the utility of MEM-FCS and SMT for gaining complementary information on molecular diffusion processes in heterogeneous material systems.

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

Statistical analysis on random quantum circuit sampling by Sycamore and Zuchongzhi quantum processors

Random quantum circuit sampling, a task to sample bit strings from a random quantum circuit, is considered a suitable benchmark task to demonstrate the outperformance of quantum computers even with noisy qubits. Recently, random quantum circuit sampling was performed on the Sycamore quantum processor with 53 qubits [Nature (London) 574, 505 (2019)] and on the Zuchongzhi quantum processor with 56 qubits [Phys. Rev. Lett. 127, 180501 (2021)]. Here, we analyze and compare the statistical properties of the outputs of the random quantum circuit sampling by the Sycamore and Zuchongzhi processors. Using the Marchenko-Pastur law of random matrices of bit strings and the Wasssertein distances between bit strings, we find that the statistical properties of Sycamore bit strings are quite different from those of Zuchongzhi bit strings, while both processors score similar values of linear cross-entropy fidelity for random circuit sampling. Some bit strings sampled by the Zuchongzhi processor pass the NIST random number tests while both Sycamore and Zuchongzhi processors show similar patterns in the heat maps of bit strings. Zuchongzhi bit strings are much closer to classical uniform random bits than those of Sycamore. It is shown that the statistical properties of bit strings of both random quantum circuits change little as the depth of the random quantum circuits increases. Our findings raise a question about the computational reliability of noisy quantum processors because two quantum processors with similar noise levels and similar qubit structures produced statistically different outputs for the same random quantum circuit sampling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Effects of transient thermal shock on the microstructures and corrosion properties of a reduced activation high-entropy alloy

The devices would subject transient thermal shocks (TTS) during operation under extremely harsh conditions of nuclear fusion reactors, which inevitably exert significant impact on the microstructure and performance of structural materials. Here, a reduced activation VCrFeTa 0.2 W 0.2 high-entropy alloy (HEA) was developed by vacuum arc melting. The effects of electron beam induced TTS on its microstructure, microhardness, and corrosion properties were investigated. The results indicate that the weight fraction of each phase changes after TTS, showing a significant decrease in the content of BCC1 phase and an increase in the content of BCC2 and Laves phases. The content of BCC1 phase continues to decrease slightly with increasing the power of TTS. Besides, the microhardness of the alloy increases from ~673 HV to ~714 HV after TTS treatments. In the reduced activation HEA, TTS results in a relatively low corrosion current density of ~0.472 μA/cm 2 in 3.5 wt% NaCl solution, around one-third of the current density observed in the as-cast sample. Furthermore, the VCrFeTa 0.2 W 0.2 HEA after TTS exhibits a pitting potential of ~1.165 V SCE , which is much higher than that of the as-cast sample. The refined composite multiscale entropy method is employed to analyze the influence of TTS on current fluctuation behavior during the corrosion process. The reduced activation VCrFeTa 0.2 W 0.2 HEA exhibits excellent properties in harsh environments after TTS, thereby showing advantageous property in the field of nuclear structural materials. Furthermore, TTS is an efficient and controllable strategy for the improvement of the HEAs’ microstructures and performances.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Sensitivity Gains, Linearity, and Spectral Reproducibility in Nonuniformly Sampled Multidimensional MAS NMR Spectra of High Dynamic Range.

Recently, we have demonstrated that considerable inherent sensitivity gains are attained in MAS NMR spectra acquired by nonuniform sampling (NUS) and introduced maximum entropy interpolation (MINT) processing that assures the linearity of transformation between the time and frequency domains. In this report, we examine the utility of the NUS/MINT approach in multidimensional datasets possessing high dynamic range, such as homonuclear 13C–13C correlation spectra. We demonstrate on model compounds and on 1–73-(U-13C,15N)/74–108-(U-15N) E. coli thioredoxin reassembly, that with appropriately constructed 50 % NUS schedules inherent sensitivity gains of 1.7–2.1-fold are readily reached in such datasets. We show that both linearity and line width are retained under these experimental conditions throughout the entire dynamic range of the signals. Furthermore, we demonstrate that the reproducibility of the peak intensities is excellent in the NUS/MINT approach when experiments are repeated multiple times and identical experimental and processing conditions are employed. Finally, we discuss the principles for design and implementation of random exponentially biased NUS sampling schedules for homonuclear 13C–13C MAS correlation experiments that yield high quality artifact-free datasets.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2019

Stability of magnetocaloric La(Fe x Co y Si 1-x-y ) 13 in water and air

Stability of cobalt-doped lanthanum iron silicide, La(Fe x Co y Si 1-x-y ) have been investigated under conditions required for magnetocaloric refrigeration. The XRD analysis revealed that both milled and non-milled samples stored in water loose a few Bragg peaks corresponding to the NaZn13 phase of La(Fe x Co y Si 1-x-y ) . Samples stored in air show well-defined Bragg peaks similar to that of pristine material. The SEM-EDS of the milled and non-milled samples stored in water and air show an increased concentration of oxygen in the samples, particularly those treated with water. The course non-milled powders kept in air and water show sharp transitions at the Curie temperature T C = 300K without large magnetization above the T C . The milled, fine-particulate sample stored in air shows a slightly broadened transition at T C , and that stored in deionized water for 14 days shows significantly broadened transition from 300K and retains large magnetizations above 400 K. This is indicative of relatively fast hydrolysis and removal of some or all of La, likely as hydroxide, from fine powders, leaving behind La-poor or, potentially, La-free Fe-Co-Si containing ferromagnetic residue with much higher Curie temperature. The non-milled course sample stored in water exhibits sharper magnetic transition and higher magnetization hence it shows the highest entropy change among all 4 type of samples.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Molybdenum carbide nanoparticles as catalysts for oil sands upgrading: Dynamics and free-energy profiles

There is no doubt that a huge gap exists in understanding heterogeneous catalysis between a cluster model of a few atoms and a bulk model of periodic slabs. Nanoparticles, which are crucial in heterogeneous catalysis in industry, lie in the middle of the gap. We present here our work on the computational modelling of molybdenum carbide nanoparticles (MCNPs) as the catalysts for the upgrading of oil sands in the in-situ environment, using benzene hydrogenation as a model reaction. With a cluster model, efforts were first made to understand the mechanism of the reaction with a density functional theory (DFT) study on the adsorption of benzene and its hydrogenation product – cyclohexane, as well as the cyclic hydrogenation reaction intermediates on the Mo{sub 2}C(0001) surface. From the thermodynamic data, along with literature information, it was found that the benzene hydrogenation reaction on molybdenum carbide happens most likely through a Langmuir-Hinshelwood mechanism with the gradual lifting up of the benzene molecule. The electron localization function (ELF) was then used to help understand the nature of the interactions between the MCNPs, identifying strong multi-center interactions between the adsorbates and the MCNPs. To enable the treatment of larger nanoparticles, a fast semi-empirical density functional tight-binding (DFTB) method was parameterized. With this method, the potential energy profiles of benzene hydrogenation reactions on different sizes of MCNPs are calculated. The study was then extended to consider a MCNP embedded in solvent (benzene), using a quantum mechanical (DFTB) / molecular mechanical approach. Calculations on the free energies profiles with the umbrella sampling method show that the entropy of the MCNPs and the solvent are essential in understanding the catalytic activity of the transition metal related nanoparticles for solid/liquid heterogeneous catalysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗