A gallium oxide single crystal particle according to the present invention is an α-Ga.sub.2O.sub.3 single crystal particle and has a diameter and a height that exceed 100 μm.

Methods of preparing a mineral-coated rock micromodel can include 3D-printing a transparent porous micromodel with photo-curable polymer, seeding a thin layer of mineral nanoparticles in the network of pores inside the micromodel, and subsequently growing a mineral layer on the thin layer of mineral nanoparticles. The thin layer of mineral nanoparticles can be introduced by injecting a suspension containing the mineral nanoparticles through the microporous polymer micromodel, and the mineral layer can be grown in-situ on the thin layer of mineral nanoparticles in the network of pores by injecting an ion-rich solution configured to crystallize from solution in response to contacting the mineral nanoparticles.

A method for manufacturing epitaxial films with multiple stress states, comprising steps of: providing a first single crystal substrate, and forming a sacrificial layer and a first epitaxial film on the first single crystal substrate, wherein the first epitaxial film is made of a first material;

removing the sacrificial layer to separate the first epitaxial film from the first single crystal substrate; transferring the first epitaxial film to a second single crystal substrate, wherein the second single crystal substrate is made of a second material, a partial surface of the second single crystal substrate being overlapped by the first epitaxial film; applying epitaxies onto the first epitaxial film and the second single crystal substrate to form a second epitaxial film on the first epitaxial film and the second single crystal substrate.

A method of producing an ultraviolet protective agent composition, which has high transparency and excellent protection ability against a light of ultraviolet region of wavelengths of 200 to 420 nm, and an ultraviolet protective agent composition obtained by the production method are provided. The method of producing an ultraviolet protective agent composition includes at least step (a) of precipitating iron oxide microparticles by mixing with a microreactor an iron oxide raw material fluid containing at least Fe.sup.3+ ion, and an iron oxide precipitation fluid containing at least a basic substance; and step (b) of dispersing the above precipitated iron oxide microparticles in a dispersion medium to obtain iron oxide microparticle dispersion, wherein a haze value of the iron oxide microparticle dispersion is 2.0% or less, and a transmittance of the iron oxide microparticle dispersion for the light of the wavelengths of 200 to 420 nm is 2.0% or less.

A method of producing an ultraviolet protective agent composition, which has high transparency and excellent protection ability against a light of ultraviolet region of wavelengths of 200 to 420 nm, and an ultraviolet protective agent composition obtained by the production method are provided. The method of producing an ultraviolet protective agent composition includes at least step (a) of precipitating iron oxide microparticles by mixing with a microreactor an iron oxide raw material fluid containing at least Fe.sup.3+ ion, and an iron oxide precipitation fluid containing at least a basic substance; and step (b) of dispersing the above precipitated iron oxide microparticles in a dispersion medium to obtain iron oxide microparticle dispersion, wherein a haze value of the iron oxide microparticle dispersion is 2.0% or less, and a transmittance of the iron oxide microparticle dispersion for the light of the wavelengths of 200 to 420 nm is 2.0% or less.

An epitaxial deposition process, such as atomic layer deposition, is provided for forming a thin film comprising beta-gallium oxide (β-Ga.sub.2O.sub.3) on a substrate, such as sapphire. The process involves depositing a buffer layer of metastable Ga.sub.2O.sub.3, such as α-Ga.sub.2O.sub.3, on the substrate, and then reacting a gallium precursor, such as TEG, with an oxygen precursor, such as oxygen plasma, to deposit a layer comprising β-Ga.sub.2O.sub.3 on the buffer layer. The Ga.sub.2O.sub.3 film formed by the process may comprise highly oriented crystalline β-Ga.sub.2O.sub.3, with negligible amounts of other Ga.sub.2O.sub.3 polymorphs.

A quality prediction method, a preparation method and a system of high resistance gallium oxide based on deep learning and Czochralski method. The quality prediction method includes the steps of obtaining preparation data of high resistance gallium oxide single crystal prepared by Czochralski method. The preparation data includes a seed crystal data, an environmental data, and a control data. The environmental data includes doping element concentration and doping element type; preprocessing the preparation data to obtain a preprocessed preparation data; preparing the preprocessed data is input to a trained neural network model, and a predicted quality data corresponding to the high resistance gallium oxide single crystal is obtained through the trained neural network model, and the predicted quality data includes a predicted resistivity.

A quality prediction method, a preparation method and a system of high resistance gallium oxide based on deep learning and Czochralski method. The quality prediction method includes the steps of obtaining preparation data of high resistance gallium oxide single crystal prepared by Czochralski method. The preparation data includes a seed crystal data, an environmental data, and a control data. The environmental data includes doping element concentration and doping element type; preprocessing the preparation data to obtain a preprocessed preparation data; preparing the preprocessed data is input to a trained neural network model, and a predicted quality data corresponding to the high resistance gallium oxide single crystal is obtained through the trained neural network model, and the predicted quality data includes a predicted resistivity.

A high resistance gallium oxide quality prediction method based on deep learning and an edge-defined film-fed crystal growth method, a preparation method and a system; the quality prediction method includes the following steps: obtaining preparation data of a high resistance gallium oxide single crystal prepared by the edge-defined film-fed crystal growth method, the preparation data including seed crystal data, environment data and control data, and the control data including doping element concentration and doping element type; preprocessing the preparation data to obtain preprocessed preparation data; inputting the preprocessing preparation data into a trained neural network model, acquiring the predicted quality data corresponding to the high resistance gallium oxide single crystal through the trained neural network model, the predicted quality data including predicted resistivity.

A high resistance gallium oxide quality prediction method based on deep learning and an edge-defined film-fed crystal growth method, a preparation method and a system; the quality prediction method includes the following steps: obtaining preparation data of a high resistance gallium oxide single crystal prepared by the edge-defined film-fed crystal growth method, the preparation data including seed crystal data, environment data and control data, and the control data including doping element concentration and doping element type; preprocessing the preparation data to obtain preprocessed preparation data; inputting the preprocessing preparation data into a trained neural network model, acquiring the predicted quality data corresponding to the high resistance gallium oxide single crystal through the trained neural network model, the predicted quality data including predicted resistivity.