【Industry News】Gallium Oxide with Diversified Development

Announcement on publicly soliciting opinions on the Guiding Opinions on Cultivating and Developing Future Industries in Ningbo City (Draft)

      In order to accelerate the future industrial development of Ningbo City, cultivate new growth drivers, take the first step in development, obtain new competitive advantages, and promote the high-quality and high-speed transformation and development of the economy, the Municipal Development and Reform Commission drafted the Guiding Opinions on Cultivating and Developing Future Industries in Ningbo City (Draft).

      It clearly points out that the cutting-edge materials is at the first place in the direction of development. Future work will focus on graphene-based materials, flexible electronics, fourth-generation semiconductors, etc., to strengthen key technologies such as graphene and carbon nanotube electrodes, conductive inks and thin films, flexible sensing and other key technology research, to actively develop flexible OLED and folding display special film key materials, flexible display luminescent materials and intermediate materials, flexible polyimide materials and key materials for flexible circuit board manufacturing, etc.; the large-scale preparation of graphene materials such as graphene oxide, graphene microsheets and graphene thin films will be accelerated, to promote the industrial application of super copper, carbon-based chips and ene carbon fiber; diamond, gallium oxide and other ultra-wide band gap fourth generation semiconductor and related device technology will be laid out in advance, to accelerate the development of the new generation of electronic information materials industry.

Award list of the 3rd Shanghai Postdoctoral Innovation and Entrepreneurship Competition in 2023

      From August 24 to 25, Shanghai held the 2023 Shanghai Professional and Technical Personnel and Project docking Conference, during which the third Shanghai Postdoctoral Innovation and Entrepreneurship Competition and the first Shanghai Young and Middle-aged Engineers Innovation and Entrepreneurship Competition was held. The Shanghai Postdoctoral Innovation and Entrepreneurship Competition, which was held for the third consecutive year, has gradually become the same flagship project as the "Super Postdoctoral Competition". In this postdoctoral innovation and Entrepreneurship Competition, Xu Wenhui, a postdoctoral fellow from Shanghai Institute of Microsystems and Information Technology, Chinese Academy of Sciences, and the project of "wafer level Gallium oxide heterointegrated materials based on intelligent stripping technology" has achieved excellent results in the competition of new materials of the Innovation Group.

Cao Bingyang's research group of the School of Aeronautics and Astronautics, Tsinghua University,  has made new progress in the field of amorphous gallium oxide thermal conductivity

      Amorphous materials refer to the solid materials that lack long-range periodicity, which exist in nature and are also the most widely used materials in industrial production and daily life. Amorphous gallium oxide has ultra-wide band width and excellent physical and chemical characteristics, which is an important basic material for manufacturing high-power chips and flexible optoelectronic devices. The study of the thermal transport characteristics of amorphous gallium oxide is crucial to its application in the thermal management and energy conversion of energy and optoelectronic devices. In recent years, some progress has been made in the thermal conductivity theory of amorphous materials due to the mode coherence and the contributions anharmonicity makes to the thermal conductivity. However, due to the complexity of the atomic scale structure of amorphous materials and the limitations of current experimental and computational means, it is still a tough challenge in the physics of condensed matter materials to fully understand the influence mechanism of the structure of amorphous materials on thermal transport characteristics and establish the quantitative relationship between the two.

      Recently, professor Cao Bingyang’s group from Tsinghua University aiming at amorphous gallium oxide system, using machine learning, molecular dynamics simulation and experimental measurement method, successfully revealed the atomic structure of the amorphous gallium oxide, thermal transport properties and "structure-thermal transport properties" internal influence mechanism and quantitative relationship. Since it is difficult to directly observe the three-dimensional atomic structure of amorphous materials in current experimental techniques, the team accurate atomic-scale modeling of amorphous materials with the help of machine learning potential function to simulate the melting-quenching process with quantum mechanical accuracy. The research team studied the thermal conductivity of amorphous gallium oxide using nonequilibrium molecular dynamics simulation, Allen-Feldmen (AF) simple harmonic theory and unified theory (UF). The experimental results show that the machine learning potentials automatically generated based on random structure search and Boltzmann energy map sampling can accurately predict the structure and thermal conductivity of amorphous gallium oxide (Figure 1). It is also revealed that the thermal conductivity of amorphous gallium oxide is dominated by the mode coherence and the contribution of the mode propagation to the thermal conductivity is negligible.

Figure 1. The experimental measurement results of the amorphous gallium oxide thermal conductivity are compared with the theoretical predicted value

      The absence of long-range disorder makes medium-and short-range ordering the most important structural feature of amorphous materials. At the same time, the short-range ordered structure largely determines the physical and chemical properties of amorphous materials. To this end, the team used machine learning-driven quenching simulations to reveal the short-range ordered structure of the amorphous gallium oxide from high density to low density regions (Figure 2). The results on the distribution function indicate that the average bond length of amorphous gallium oxide is about 1.9Å (Figure 2b). In addition, the study shows that as the density increases, the average atomic coordination number of the amorphous gallium oxide atomic network increases, the proportion of tetrahedral-like environments decreases, and the proportion of octahedral-like environments increases (Figure 2c-e). The statistical distribution of the shortest path loop decayed rapidly with increasing density, which shows that the scale of the calculation unit used in the simulation guarantees the recurrence of the medium-range order structure (Figure 2f). The results of the simultaneous ring distribution show that the high-density system has a medium-range ordered structure more similar to that of the crystal.

Figure 2. Characterization of the short-range and medium-range ordered structure of amorphous gallium oxide

      In order to deeply analyze the mechanism of structural changes on the microscopic thermal conductivity of amorphous gallium oxide, the research team further calculated the reciprocal participation ratio and mode diffusivity of different amorphous gallium oxide systems (Figure 3). The participation ratio can measure the localization of vibration modes, while the mode diffusivity can describe the rate of heat diffusion. The results show that the localization of vibrational modes mainly occurs in the high frequency region, while the diffusivity of localized modes is generally low. With increasing material density, the participation ratio reciprocal decreases, while the mode diffusivity increases. This indicates that the proportion of the modal localization is decreasing, while the scalability of the mode in space is increasing, which is finally reflected in the enhancement of the thermal conductivity of the material. The effect of the density on the thermal conductivity can be attributed more deeply to the effect of the atomic-scale structure on the thermal transport process. As mentioned above, the increase in the system density leads to an increase in the average number of atomic coordination sites and the increased proportion of the octahedral-like environment, which provides more action channels for the transport of heat, which in turn leads to enhanced heat transport.

Figure 3. Participation ratio reciprocal and vibration mode diffusion rate distribution of different amorphous gallium oxide systems

      From the perspective of material informatics, in order to establish the quantitative relationship between the material structure and the thermal conductivity, the researchers first proposed the structural descriptive device of the amorphous material with physical interpretability, namely the structural similarity factor (SSF). From the atomic scale, amorphous materials and crystalline materials have similar polyhedral units, resulting in the difference in the structure and properties of the two mainly come from the differences in the connection number, orientation and distortion of polyhedrdral units. SSF represents the structural characteristics of amorphous by measuring the similarity to the chemical environment of the crystal material. In essence, SSF has a high sensitivity to the density and components of the material system. A larger SSF indicates a more dense atomic network, a higher average coordination number, and a larger thermal conductivity of the corresponding material. Meanwhile, SSF skillfully quantifies the similarity of the intermediate program structures of crystalline and amorphous materials. The larger the SSF, the more similar the intermediate program structure of the amorphous material and the crystal, which can be verified by the shortest path loop distribution shown in Figure 2f. The results show that there is a strong linear relationship between SSF and thermal conductivity, so a quantitative relationship between structure and thermal conductivity can be constructed using a small amount of data, which helps to quickly and accurately predict thermal conductivity directly from the structural information of amorphous systems and accelerate the screening of amorphous materials with excellent thermal properties.

Figure 4. Relationship between density, component ratio, and structure descriptor SSF and thermal conductivity of amorphous gallium oxide

      The results are important for the development of thermal management techniques for amorphous gallium oxide electronic devices. The results also demonstrate the ability of machine learning models to solve real-world physical problems. Given the complexity and importance of heat transport in the amorphous phase, this work provides a new starting point for the future accelerated exploration of the heat transport properties and mechanisms of other important amorphous materials.

      The results mentioned above is published in the international journal Advanced Materials, titled “Unraveling Thermal Transport Correlated with Atomistic Structures in Amorphous Gallium Oxide via Machine Learning Combined with Experiments”.

      The corresponding authors of the paper are Professor Cao Bingyang, School of Aeronautics and Astronautics, Tsinghua University, and Professor Gábor Csányi , Department of Engineering, University of Cambridge, UK. The first author is Liu Yuanbin, a doctoral student from Tsinghua University (graduated, now a postdoctoral fellow at Oxford University), and Tsinghua University is the first unit of this paper. Other important collaborators of the paper include Liang Lei, Yang Guang, associate researcher of the Institute of Physics, Chinese Academy of Sciences, and doctoral student of the School of Navigation of Tsinghua University. The research was supported by key projects of National Natural Science Foundation of China.