Comparative studies on thermoelectric properties of p-type Mg2Sn0.75Ge0.25 doped with lithium, sodium, and gallium
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This work presents a computational study of charge hopping dynamics along a one-dimensional chain with Gaussian site energy disorder and linearly coupled quantum bath. Time dependent square displacements are calculated directly from numerical solutions of Pauli master equations, for five different rate kernels: exact Fermi golden rule (FGR) rate expression, stationary phase interpolation (SPI) approximation, semiclassical (SC) approximation, classical Marcus rate expression, and Miller-Abrahams expression. All results demonstrate diffusive behavior in the steady state limit. The results based on the FGR rate expression show that the charge transport in the quantum bath can be much more sensitive to the disorder than the prediction from the classical Marcus expression. While the SPI approximation captures this general trend reasonably well, the SC approximation tends to be unreliable at both quantitative and qualitative levels and becomes even worse than the classical Marcus expression under certain conditions. Furthermore, these results offer useful guidance in the choice of approximate rate kernels for larger-scale simulations and also demonstrate significant but fragile positive effects of quantum environments on the charge hopping dynamics.
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In alkali aluminosilicate glasses, additions of 4+ cations like Zr and Ti are often added to promote crystallization. In this study, Zr, Ti, or Sn are progressively substituted for Si in nepheline (NaAlSiO4) glass to determine their impact on the crystallization behavior. For glasses homogeneous on quenching, up to NaAlZr0.075Si0.925O4, NaAlSn0.100Si0.900O4, and NaAlTi0.300Si0.700O4, respectively, crystallization temperatures were investigated by thermal analysis. A subset of compositions was subjected to additional thermal analysis, varying heating rate and particle size, to investigate the subtleties of crystallization behavior. Subsequent heat treatment of glass powders was performed to maximize crystallization, and glass-ceramic microstructure was assessed by optical microscopy and electron microprobe, while crystalline phases were determined by X-ray diffraction. In all cases the major crystalline phase was orthorhombic carnegieite, which accommodated Ti in its structure but not Zr or Sn, and excess 4+ cations formed MO2, i.e., brookite, baddeleyite, and cassiterite, respectively.
A high-packing density pomegranate Sb@C yolk–shell structure has been developed as high-performance anodes for lithium-ion and sodium-ion batteries.
Computation of adsorption and transition state energies for a large number of surface intermediates for numerous active site models pose significant computational overhead in computational screening of catalysts. Machine learning (ML) techniques can be used to predict part of these energies. To predict the energies, ML models need to be fed appropriate metal and species descriptors. For complex surface chemistries, the structures of the intermediate species can vary greatly. In this paper, working with the hydrodeoxygenation of succinic acid on six different metal surfaces, we have studied the effect of linear and non-linear ML models used along with pen-and-paper based species descriptors and two categories of metal descriptors on two different categories of intermediate species: chain and ring. More specifically, our computations include the prediction of chain species when trained on only chain species and also when trained on both chain and ring species. Similar computations were performed for predictions of ring species. In each case, results of linear ML models were compared with kernel based non-linear models. Our results indicate that ring species data does not improve the prediction of chain species. Similarly, chain species data does not improve the prediction of ring species. The use of non-linear ML models, however, did help to minimize the prediction errors compared to the linear models. Furthermore, the study also shows that electronic or adsorption energy based metal descriptors along with bond count based species fingerprints can achieve a mean absolute error (MAE) of less than 0.2 eV for complex chain molecules when used with an appropriate machine learning model.
The oxidation of two-dimensional Ti 3 C 2 MXene structures has been recognized as a promising method for the formation of hybrid structures of carbon supported nanotitania. Here, we studied the oxidation of Ti 3 C 2 MXene structures using reactive force field (ReaxFF) based molecular dynamics simulations. To investigate the effect of oxidizing agent, we used three different environments including dry air (oxygen molecules), wet air (oxygen and water molecules) and hydrogen peroxide (H 2 O 2 molecules). Oxidation simulations were performed at different temperatures of 1000, 1500, 2000, 2500 and 3000 K. We found that by controlling the temperature, carbon supported titania can be formed by diffusion of Ti atoms to the surface of MXene structures during the oxidation. These results were confirmed by the increase in the average bond orders of C–C and Ti–O and decrease in the average bond orders of Ti–C. Moreover, it was revealed that by increasing the temperature, the oxidation rate increases, and the rate depends on the oxidant according to the following order: H 2 O 2 > wet air > dry air. This was validated by heating the MXene in wet air and dry air followed by examining the products using X-ray diffraction and Raman spectroscopy. To investigate the effect of the presence of the oxidant, the MXene structure was also heated under vacuum, and it was found that in this case the MXene structure was converted to cubic TiC. Furthermore, it was indicated that during the heating process of the MXene structure in a vacuum, the average bond orders for C–C, Ti–C and Ti–O do not change significantly due to the lack of oxidants in the environment, leaving room for only topotactic transformation of atoms during the heating. In conclusion, the formation of the TiC structure by heating the MXene in an inert environment was confirmed experimentally as well.
We construct effective coarse-grained (CG) models for polymeric fluids by employing two coarse-graining strategies. The first one is a forward-coarse-graining procedure by the Mori-Zwanzig (MZ) projection while the other one applies a reverse-coarse-graining procedure, such as the iterative Boltzmann inversion (IBI) and the stochastic parametric optimization (SPO). More specifically, we perform molecular dynamics (MD) simulations of star polymer melts to provide the atomistic fields to be coarse-grained. Each molecule of a star polymer with internal degrees of freedom is coarsened into a single CG particle and the effective interactions between CG particles can be either evaluated directly from microscopic dynamics based on the MZ formalism, or obtained by the reverse methods, i.e., IBI and SPO. The forward procedure has no free parameters to tune and recovers the MD system faithfully. For the reverse procedure, we find that the parameters in CG models cannot be selected arbitrarily. If the free parameters are properly defined, the reverse CG procedure also yields an accurate effective potential. Moreover, we explain how an aggressive coarse-graining procedure introduces the many-body effect, which makes the pairwise potential invalid for the same system at densities away from the training point. From this work, general guidelines for coarse-graining of polymeric fluids can be drawn.
We present detailed benchmark ground-state calculations of the one- and two-dimensional Hubbard model utilizing the cluster extensions of the rotationally invariant slave-boson mean-field theory and the density matrix embedding theory. Our analysis shows that the overall accuracy and the performance of these two methods are very similar. Furthermore, we propose a unified computational framework that allows us to implement both of these techniques on the same footing. In conclusion, this provides us with a different line of interpretation and paves the ways for developing systematically distinct generalizations of these complementary approaches.
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The energy difference between the oxide and bulk peaks in X-ray photoelectron spectroscopy (XPS) spectra was investigated for both GeO{sub 2}/Ge and SiO{sub 2}/Si structures with thickness-controlled water films. This was achieved by obtaining XPS spectra at various values of relative humidity (RH) of up to ∼15%. The increase in the energy shift is more significant for thermal GeO{sub 2} on Ge than for thermal SiO{sub 2} on Si above ∼10{sup −4}% RH, which is due to the larger amount of water molecules that infiltrate into the GeO{sub 2} film to form hydroxyls. Analyzing the origins of this energy shift, we propose that the positive charging of a partially hydroxylated GeO{sub 2} film, which is unrelated to X-ray irradiation, causes the larger energy shift for GeO{sub 2}/Ge than for SiO{sub 2}/Si. A possible microscopic mechanism of this intrinsic positive charging is the emission of electrons from adsorbed water species in the suboxide layer of the GeO{sub 2} film to the Ge bulk, leaving immobile cations or positively charged states in the oxide. This may be related to the reported negative shift of flat band voltages in metal-oxide-semiconductor diodes with an air-exposed GeO{sub 2} layer.
This report presents a comparative study on Enhanced Feher's Quadrature Phase Shift Keying (EFQPSK) and Constrained Envelope Root Nyquist (CERN) techniques. These two techniques have been developed in recent times to provide high spectral and power efficiencies under nonlinear amplifier environment. The purpose of this study is to gain insights into these techniques and to help system planners and designers with an appropriate set of guidelines for using these techniques. The comparative study presented in this report relies on effective simulation models and procedures. Therefore, a significant part of this report is devoted to understanding the mathematical and simulation models of the techniques and their set-up procedures. In particular, mathematical models of EFQPSK and CERN, effects of the sampling rate in discrete time signal representation, and modeling of nonlinear amplifiers and predistorters have been considered in detail. The results of this study show that both EFQPSK and CERN signals provide spectrally efficient communications compared to filtered conventional linear modulation techniques when a nonlinear power amplifier is used. However, there are important differences. The spectral efficiency of CERN signals, with a small amount of input backoff, is significantly better than that of EFQPSK signals if the nonlinear amplifier is an ideal clipper. However, to achieve such spectral efficiencies with a practical nonlinear amplifier, CERN processing requires a predistorter which effectively translates the amplifier's characteristics close to those of an ideal clipper. Thus, the spectral performance of CERN signals strongly depends on the predistorter. EFQPSK signals, on the other hand, do not need such predistorters since their spectra are almost unaffected by the nonlinear amplifier, Ibis report discusses several receiver structures for EFQPSK signals. It is observed that optimal receiver structures can be realized for both coded and uncoded EFQPSK signals with not too much increase in computational complexity. When a nonlinear amplifier is used, the bit error rate (BER) performance of the CERN signals with a matched filter receiver is found to be more than one decibel (dB) worse compared to the bit error performance of EFQPSK signals. Although channel coding is found to provide BER performance improvement for both EFQPSK and CERN signals, the performance of EFQPSK signals remains better than that of CERN. Optimal receiver structures for CERN signals with nonlinear equalization is left as a possible future work. Based on the numerical results, it is concluded that, in nonlinear channels, CERN processing leads towards better bandwidth efficiency with a compromise in power efficiency. Hence for bandwidth efficient communications needs, CERN is a good solution provided effective adaptive predistorters can be realized. On the other hand, EFQPSK signals provide a good power efficient solution with a compromise in band width efficiency.
We have made comparative studies of ion anisotropy and high-energy variability of solar energetic particle (SEP) events previously examined by the Solar, Heliospheric, and Interplanetary Environment (SHINE) Workshop campaign. We have found distinctly different characteristics of SEPs between two large "gradual" events having very similar solar progenitors (the 2002 April 21 and August 24 events). Since the scattering centers of SEPs are approximately frozen in the solar wind, we emphasize work in the solar-wind frame where SEPs tend to be isotropized, and small anisotropies are easier to detect. While in the August event no streaming reversal occurred, in the April event the field-aligned anisotropy of all heavy ions showed sign of streaming reversal. The difference in streaming reversal was consistent with the difference in the presence of the outer reflecting boundary. In the April event the magnetic mirror, which was located behind the interplanetary shock driven by the preceding coronal mass ejection (CME), could block the stream of SEPs, while in the August event SEPs escaped freely because of the absence of nearby boundary. The magnetic mirror was formed at the bottleneck of magnetic field lines draped around a flank of the preceding CME. In the previous SHINE event analysis the contrasting event durations and Fe/O ratios of the both events were explained as the interplay between shock geometry and seed population. Our new findings, however, indicate that event duration and time as well as spectral variation are also affected by the presence of a nearby reflecting boundary.
This paper reports the results of a comparative study of the various libraries making up the COG thermal database and is a follow up to an earlier study, “A Comparative Study of the COG Thermal Libraries”.
The motorized momentum exchange tether (MMET) is capable of generating useful velocity increments through spin–orbit coupling. This study presents a comparative study of the velocity increments between the rigid body and flexible models of MMET. The equations of motions of both models in the time domain are transformed into a function of true anomaly. The equations of motion are integrated, and the responses in terms of the velocity increment of the rigid body and flexible models are compared and analysed. Results show that the initial conditions, eccentricity, and flexibility of the tether have significant effects on the velocity increments of the tether.