贵金属材料基因工程数据库建设策略

Database Architecture Design of Precious Metal Materials for Material Genetic Engineering

贵金属,尤其是其中的铂族金属因极度稀缺、价格昂贵,又具有难以替代的物理化学性能,被称为“第一高技术金属”和“工业维他命”,是国防军工高精尖领域不可替代、高新技术领域不可或缺的重要原材料。新材料研发主要采用传统的“试错法”依靠经验累积,存在贵金属消耗大、价格太高而“用不起”,应用性能要求太高、研发周期长而“效率低”两难问题。数据驱动的材料基因工程研究方法通过“大数据+人工智能”技术预测材料性能和设计新材料,再通过实验验证和开发新材料,可大幅缩短研发周期、降低研发成本,为有效解决贵金属新材料研发的两难问题提供了新思路。

There are eight elements in precious metals, including platinum group, gold and silver. Platinum group contains six elements, namely platinum, palladium, rhodium, osmium, iridium and ruthenium. Precious metals are scarce metals in the earth, especially platinum group metal resources. China is heavily dependent on imports, so its price is not only expensive but also greatly influenced by external factors. Precious metals also have irreplaceable physical and chemical properties, mainly used in large-scale integrated circuits, communications, new energy, biomedicine, environmental governance, aerospace, national defense and military and other high-end equipment and high-tech fields, known as the "first high-tech metal" and "industrial vitamin". It is an indispensable raw material in the field of national defense and high-tech. Therefore, these areas have high requirements for quality levels, performance indicators and batch consistency of precious metal materials, as well as technical research and development capabilities and efficiency of relevant material or product suppliers. At present, the traditional "empirical" and "trial and error" mode leads to high research and development cost and long research and development cycle, which seriously restricts the rapid development of new materials industry. Especially for the precious metal new materials industry, there are not only because of the high price of precious metal raw materials, large consumption, large process loss and "can not afford to use", but also because of the high application performance requirements, research and development difficulty, low success rate and "low efficiency" dilemma. The Materials Genome Project proposed by America in 2011 and The Chinese version of "Material Genetic Engineering" launched in China in 2015 had opened up a forward-looking research and development of a new path. Through the combination of computing, experiment, data technology and theory, a new model of "data-driven" intelligent prediction of materials research and development was established, and the traditional experimental trial-and-error method was reformed. Finally, the strategic goal of "double halving" was achieved, which was to shorten the research and development cycle by half and reduce the research and development cost by half. The "data-driven" research and development model was completely different from the "experiment-driven" or "computing-driven" research and development model. Based on a large amount of data, it used machine learning and data mining technology to establish the relationship between "composition, structure, process and performance" more quickly, accurately and cheaply. In this way, material properties could be predicted quickly and new materials could be discovered. Therefore, the data-driven model could effectively solve the dilemma of precious metal new material research and development. In 2018, based on the resource endowment and industrial advantages of rare and precious metal materials, Yunnan Province initiated a major scientific and technological project of rare and precious metal materials genetic engineering. Sino-Precious Metal Holding Co., Ltd. combined several units have made progress in building a genetic engineering database platform for rare metal materials, developing big data technology and establishing metadata standards. It was expected that under the new model of "data-driven" research and development, the key materials and technologies of precious metals would get rapid breakthrough and innovation, so as to provide important support for the rapid development of the precious metal new materials industry.