Related papers: Machine Learning Approach to Predict Curie Tempera…
Simulated annealing is an effective and general means of optimization. It is in fact inspired by metallurgy, where the temperature of a material determines its behavior in thermodynamics. Likewise, in simulated annealing, the actions that…
Magnetic and electric properties of the Hubbard model with binary alloy disorder are studied within the dynamical mean--field theory. A paramagnet--ferromagnet phase transition and a Mott--Hubbard metal--insulator transition are observed…
We develop machine learning techniques for estimating physical properties of laser-cooled potassium-39 atoms in a magneto-optical trap using only the scattered light -- i.e., fluorescence -- that is intrinsic to the cooling process. In-situ…
We study the interatomic exchange interactions and Curie temperatures in half-metallic semi Heusler compounds NiCrZ (Z=P, Se, Te) and NiVAs. The study is performed within the framework of density functional theory. The calculation of…
Temperature fluctuations significantly affect microorganism growth and pest activities in grain pile, precise monitoring and forecasting temperature of stored grain are essential for maintaining the quality and safety of grain storage. This…
Algorithms for simulating complex physical systems or solving difficult optimization problems often resort to an annealing process. Rather than simulating the system at the temperature of interest, an annealing algorithm starts at a…
There currently exist no quantitative methods to determine the appropriate conditions for solid-state synthesis. This not only hinders the experimental realization of novel materials but also complicates the interpretation and understanding…
The experimental determination of eutectic points is a long-established and widely used technique, but it is generally only practical for systems with relatively low melting points. Many modern, promising materials, however, are…
Developing fast and accurate methods to discover intermetallic compounds is relevant for alloy design. While density-functional-theory (DFT)-based methods have accelerated design of binary and ternary alloys by providing rapid access to the…
We investigate how a temperature reduction in z-direction influences the switching probability and the noise in heat-assisted magnetic recording (HAMR) for a bit in bit-patterned media with dimensions d=5nm and h=10nm. Pure hard magnetic…
Accurate and efficient temperature prediction is critical for optimizing the preheating process of PET preforms in industrial microwave systems prior to blow molding. We propose a novel deep learning framework for generalized temperature…
Motivated by applications to 3D printing, this paper presents two algorithms for calculating an ensemble of solutions to heat conduction problems. The ensemble average is the most likely temperature distribution and its variance gives an…
The thermodynamic properties of strongly correlated system with binary type of disorder are investigated using the combination of the coherent potential approximation and dynamical mean-field theory. The specific heat has a peak at small…
We use a random forest model to predict the critical cooling rate (RC) for glass formation of various alloys from features of their constituent elements. The random forest model was trained on a database that integrates multiple sources of…
We provide a systematic analysis of finite-temperature magnetic properties of random alloys Fe$_x$Ni$_{1-x}$ with the face-centered-cubic structure over a broad concentration range $x$. By means of the spin-polarized relativistic…
We demonstrate the manipulation of the Curie temperature of buried layers of the ferromagnetic semiconductor (Ga,Mn)As using nanolithography to enhance the effect of annealing. Patterning the GaAs-capped ferromagnetic layers into nanowires…
We detail the use of simple machine learning algorithms to determine the critical Bose-Einstein condensation (BEC) critical temperature $T_\text{c}$ from ensembles of paths created by path-integral Monte Carlo (PIMC) simulations. We quickly…
The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced…
Debye temperature, $\Theta_D$, of Fe-rich Fe$_{100-x}$Cr$_x$ disordered alloys with $0\le x \le 22.3$ was determined from the temperature dependence of the central shift of M\"ossbauer spectra recorded in the temperature range of 60 -- 300…
In the dynamic and rapidly advancing battery field, alloy anode materials are a focal point due to their superior electrochemical performance. Traditional screening methods are inefficient and time-consuming. Our research introduces a…