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Materials with high thermal conductivity are of great importance to the thermal management of modern electronic devices. Recently, it was found that cubic boron arsenide (c-BAs) is a high thermal conductivity (κ) material with a value of ∼1300 W/(m•K) at room temperature (RT), where four-phonon scattering plays a crucial role in limiting the κ. In this work, with four-phonon scattering included, we find that the κ of wurtzite BAs (w-BAs) reaches as high as 1036 W/(m•K) along the a−b plane at RT, decreasing by 43% compared to the calculation without considering four-phonon scattering. The similar phonon transport properties between c-BAs and w-BAs can be understood in terms of similar projected density of states and scattering rates, which have the origin in crystal structural resemblance. To accelerate the calculation, the moment tensor potential derived from machine learning is adopted and proven to be a reliable and efficient method to obtain high-order interatomic force constants.

The effect of graphene oxide (GO) on the crystallization of calcium carbonate (CaCO3) is explored in this paper. Precipitation of CaCO3 was carried out by bubbling carbon dioxide (CO2) through tricalcium silicate (C3S) hydration solution with different graphene oxide admixture contents (0.2%, 1% and 2% mass ratios based on C3S). The polymorph, morphology, crystal size and particle size of CaCO3 were evaluated using X-ray diffraction (XRD), an environmental scanning electronic microscope (ESEM), and laser particle size analysis. The results showed that addition of GO was able to promote the conversion of CaCO3 to a calcite crystal phase with higher thermal stability and crystallinity than the control. However, as the dosage of GO increased, the growth of the calcite crystal particles was somewhat suppressed, resulting in a decrease in the crystal particle size and a narrow particle size distribution. When the amount of GO was 0.2%, 1% and 2%, the crystal size of the calcite was 5.49%, 12.38%, and 24.61% lower than that of the sample without GO, respectively, while the particle size of the calcite also decreased by 17.21%, 39.26%, 58.03%, respectively.

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The study of density-dependent stochastic population processes is important from a historical perspective as well as from the perspective of a number of existing and emerging applications today. In more recent applications of these processes, it can be especially important to include time-varying parameters for the rates that impact the density-dependent population structures and behaviors. Under a mean-field scaling, we show that such density-dependent stochastic population processes with time-varying behavior converge to a corresponding dynamical system. We analogously establish that the optimal control of such density-dependent stochastic population processes converges to the optimal control of the limiting dynamical system. An analysis of both the dynamical system and its optimal control renders various important mathematical properties of interest.

This paper addresses the problem of the position/force tracking in teleoperation system and proposes a haptic proxy control scheme. Compared to previous works, communication delays are assumed to be both time-varying and asymmetric, and the response of the synchronization and the transparency are improved. The control design is performed using Linear Matrix Inequality (LMI) optimization based on Lyapunov-Krasovskii functionals (LKF) and H ∞ control theory. With the designed controllers, the simulations of different working conditions, such as abrupt motion and wall contact, are performed and show the effectiveness of the proposed solution.

During railway transportation, due to various factors such as road conditions and operating conditions and produced vibrations and shocks, this kind of vibration environment may cause fatigue damage to on-board equipment and transported goods. The authors propose a research on the numerical simulation method of the nonstationary random vibration signal sensor of railway transportation; first, they establish the mathematical model of the railway nonstationary random vibration signal sensor and then introduce the method of reconstructing the railway nonstationary random vibration signal sensor. For railway nonstationary non-Gaussian random vibration reconstruction signal, compare the time-domain characteristics of the sampled signal, and for railway nonstationary non-Gaussian random vibration reconstruction signal, compare the frequency domain characteristics of the sampled signal. The results show that the relative error of the RMSM function is within 6%, the relative error of the sliding bias function is within 10%, and the relative error of the sliding kurtosis function is within 8%. The energy distribution of the edge Hilbert amplitude spectrum is very similar, with absolute error less than 6%. The energy fluctuations are similar in each band, with absolute error rates less than 4% in most bands. The method proposed in this article, suitable for reconstruction of railway nonstationary Gaussian random vibration and nonstationary non-Gaussian vibration signal sensor, verifies the effectiveness and feasibility of the signal reconstruction method. The model and signal reconstruction method proposed in this paper are applied to the railway nonstationary Gaussian and nonstationary non-Gaussian random vibration sampling signals.

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