A universal potential energy function and precise calculations on the molecular spectra

By using a function with a phase factor,a universal analytic potential energy function applied to the interactions between diatoms or molecules is derived and six kinds of potential curves of common shapes are obtained by adjusting the phase factor.The spectroscopic parameters of ten diatomic molecules are calculated by using the potential energy function;as a consequence,all calculation results are in good agreement with experimental data.

A UNIVERSAL ANALYTIC POTENTIAL-ENERGY FUNCTION BASED ON A PHASE FACTOR

Using a field equation with a phase factor, a universal analytic potential-energy function applied to the interactions between diatoms or molecules is derived, and five kinds of potential curves of common shapes are obtained adjusting the phase factors. The linear thermal expansion coefficients and Young's moduli of eleven kinds of face-centered cubic (fcc) metals - Al, Cu, Ag, etc. are calculated using the potential-energy function; the computational results are quite consistent with experimental values. Moreover, an analytic relation between the linear thermal expansion coefficients and Young's moduli of fcc metals is given using the potential-energy function. Finally, the force constants of fifty-five kinds of diatomic moleculars with low excitation state are computed using this theory, and they are quite consistent with RKR (Rydberg-Klein-Rees) experimental values.

Systematic assessment of various universal machine-learning interatomic potentials

Machine-learning interatomic potentials have revolutionized materials modeling at the atomic scale.Thanks to these,it is now indeed possible to perform simulations of ab initio quality over very large time and length scales.More recently,various universal machine-learning models have been proposed as an out-of-box approach avoiding the need to train and validate specific potentials for each particular material of interest.In this paper,we review and evaluate four different universal machine-learning interatomic potentials(uMLIPs),all based on graph neural network architectures which have demonstrated transferability from one chemical system to another.The evaluation procedure relies on data both from a recent verification study of density-functional-theory implementations and from the Materials Project.Through this comprehensive evaluation,we aim to provide guidance to materials scientists in selecting suitable models for their specific research problems,offer recommendations for model selection and optimization,and stimulate discussion on potential areas for improvement in current machinelearning methodologies in materials science.

Application of Dijkstra Algorithm to Proposed Tramway of a Potential World Class University

Nowadays, the development of “smart cities” with a high level of quality of life is becoming a prior challenge to be addressed. In this paper, promoting the model shift in railway transportation using tram network towards more reliable, greener and in general more sustainable transportation modes in a potential world class university is proposed. “Smart mobility” in a smart city will significantly contribute to achieving the goal of a university becoming a world class university. In order to have a regular and reliable rail system on campus, we optimize the route among major stations on campus, using shortest path problem Dijkstra algorithm in conjunction with a computer software called LINDO to arrive at the optimal route. In particular, it is observed that the shortest path from the main entrance gate (Canaan land entrance gate) to the Electrical Engineering Department is of distance 0.805 km.

Homeostasis of Synapses:Expansion During Wakefulness,Contraction During Sleep

Sleep is a universal biological process occurring in almost every species of animal,and the loss of sleep has detrimental effects,especially impairments in cognition[1,2].Yet,the neuronal function of sleep is still one of the greatest mysteries.One prominent idea,known as the synaptic homeostasis hypothesis,