月期刊平台服务过的文章录用时间为1-3个月，依据20年经验，经月期刊专家预审通过后的文章，投稿通过率100%以上！
工业过程的设计需要可靠的热力学数据。CALPHAD（相图和热化学的计算机耦合）旨在通过开发代表不同相的热力学性质的模型来促进计算热力学，该模型允许从二元和三元子系统的热力学性质预测多组分系统的性质，对数据及其内部结构进行临界评估。将rpo转换为自一致的数据库，开发优化和导出热力学参数的软件，开发和使用数据库进行计算，以提高对各种工业和技术过程的理解。这项工作是通过卡尔法德期刊及其年度会议传播的。欢迎在这些和相关领域，特别是第一原理计算领域、热化学和相平衡数据的实验测量、相转换以及卡尔法德工作所基于或使用的工艺和材料设计方面做出高质量的贡献。
https://www.evise.com/evise/faces/pages/login/login.jspx?resourceUrl=%2
The design of industrial processes requires reliable thermodynamic data. CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry) aims to promote computational thermodynamics through development of models to represent thermodynamic properties for various phases which permit prediction of properties of multicomponent systems from those of binary and ternary subsystems, critical assessment of data and their incorporation into self-consistent databases, development of software to optimize and derive thermodynamic parameters and the development and use of databanks for calculations to improve understanding of various industrial and technological processes. This work is disseminated through the CALPHAD journal and its annual conference. Contributions of high quality in these and related fields, especially the fields of first-principles calculations, experimental measurements of thermochemical and phase equilibrium data, phase transformations, and the process and materials designs that the CALPHAD works are based on or used for, are welcome.
