5results about How to "Help capture" patented technology

The invention relates to the technical field of photosynthesis power generation, and discloses a device and a method for realizing photosynthesis power generation based on a liquid metal-semiconductor junction. The negative electrode comprises a metal-semiconductor junction (MSJs) consisting of liquid metal and a silicon wafer; the thylakoid suspension is positioned between the positive electrode and the negative electrode and is extracted from spinach. The liquid metal is eGaInSn room temperature liquid metal. The method comprises the following steps: extracting crushed chloroplasts and thylakoid which are rich in photosynthetic devices such as a photosystem I (PSI), a photosystem II (PS) and the like in spinach leaves by using a salt solution separation method; in combination with flexible transparent indium tin oxide (ITO), the photosynthesis power generation device with the structure of Si / LMs / BBY / ITO is manufactured. The liquid metal and the silicon wafer are combined to obtain the MSJs as the negative electrode, the electron transfer efficiency of the power generation device is enhanced, the preparation is simple, the performance is excellent, and green power generation is realized.

The invention relates to a stirring casting preparation method suitable for a superfine SiCp reinforced aluminum-based composite material. The problems that in a traditional technology, wettability of SiCp and aluminum melt is poor, agglomeration is prone to occurring, an Al4C3 brittle phase is prone to occurring, and the melt is prone to being polluted by impurities and high in porosity are solved. The preparation method comprises the following steps: performing in-situ growth of graphene on the surface of SiCp through pulse laser-methane micro-explosion to form a composite reinforced phase; carrying out aluminum alloy fractional smelting and step-by-step stirring to obtain a composite melt; an external coil-iron core assembly is adopted to carry out pulse magnetic oscillation on the melt, and mechanical stirring and argon degassing are synchronously matched; and finally casting and molding. According to the method, generation of Al4C3 can be avoided, uniform dispersion of SiCp is achieved, the density of the obtained composite material is larger than or equal to 99.2%, the 0.2% yield strength is larger than or equal to 220 MPa, the heat conductivity retention rate is larger than or equal to 99%, the increment of the iron content of the melt is smaller than or equal to 50 ppm, ton-level mass production can be achieved based on conventional equipment, and the method is suitable for industrial preparation of the high-performance aluminum-based composite material in the fields of aerospace and automobiles.

The invention provides a dynamic penetration testing device and method based on effective penetration energy, and relates to geotechnical engineering reconnaissance, the device comprises a support, a displacement sensor, a guide rod, a center penetrating hammer, a hammer seat, a probe rod, a pipe wrench, a cable, a processor, an energy collection connector and the like, and a strain and acceleration sensor is arranged in the energy collection connector; the strain and acceleration sensor is used for collecting the strain and acceleration fed back by the penetration of the sounding probe into the soil body, and calculating the effective penetration energy of the sounding probe in the hammering process based on the data. The method has the beneficial effects that the effective penetration energy in the successive hammering process is accurately obtained, and fine division of a stratum structure is facilitated; absorption and dissipation of hammering energy by hole depth, side friction resistance and drill rod vibration are eliminated in measurement data, and the measurement data are not limited by the penetration depth in the industry specification any more; proper hammer weight and drop distance can be flexibly selected according to the actual test depth; the automation degree is high, automatic data acquisition and processing can be achieved, and manual errors are effectively avoided.

The application relates to a high-function autism screening method based on a clinician-child dialogue, and relates to the technical field of natural language processing and medical auxiliary diagnosis. The application aims to solve the problem that existing screening relies on expensive equipment or manual features and is difficult to capture subtle abnormalities in children's language. The implementation steps are as follows: obtaining a doctor-child question and answer dialogue text; adopting a sliding window to combine multiple continuous question and answer pairs into an input sequence; using a pre-trained BERT model to extract word-level deep semantic representation; dynamically weighting the contribution of each word by an adaptive word aggregation module to obtain sequence-level aggregated features; performing paragraph-level classification; averaging the prediction results of all paragraphs of the same child to obtain individual screening results. The application realizes low-cost and high-efficiency early screening of HFA by analyzing the semantic, syntactic and pragmatic abnormalities in the dialogue language, and highlights fine-grained language clues with diagnostic value.

The application discloses a mixed geometric representation-based pre-training generalization operation method and system of a mechanical arm, and belongs to the field of generalization operation of the mechanical arm. The method comprises the following steps: constructing a 3D-MOV data set containing an object, a fine-grained scene and a desktop 3D point cloud; pre-training a mixed geometric representation encoder based on the data set; rendering the 3D point cloud from multiple perspectives, mapping to a hyperbolic space, optimizing learning, returning to the Euclidean space to complete self-supervised reconstruction; and based on the encoder, fine-tuning a mechanical arm operation task: rendering the scene observation point cloud into an RGB image, processing the image, distributing the image through two channels, fusing information in a strategy network to complete fine-tuning, and predicting the mechanical arm action. The hyperbolic geometric representation is introduced into the 3D multi-perspective visual self-supervised pre-training, and the 3D multi-perspective representation based on the mixed geometric space is pre-trained for the mechanical arm operation, so that the next operation action can be effectively predicted, and the generalization operation capability of the mechanical arm in different scenes is greatly enhanced.