7 results about "Reverse diffusion" patented technology

The invention discloses a lake pollution traceability analysis method based on multi-source data assimilation and reverse diffusion, and relates to water pollution traceability analys.The lake pollution traceability analysis method comprises the steps that chemical pollution is monitored at the downstream of a lake, monitoring data are imported into a hydrodynamic force-water quality model after Kalman filtering, and spatial and temporal distribution data of pollutants in a water body are obtained; pollution source inversion is carried out based on a differential evolution Markov chain Monte Carlo method, and pollution source parameters are obtained; forward simulation is carried out, a flow velocity field and water depth are solved through a hydrodynamic force-water quality model, then a pollutant transport model is generated, pollution source parameters are used as input, a finite volume method discrete control equation is used based on the pollutant transport model to predict pollutant concentration space-time evolution, and pollution duration under natural attenuation is evaluated; and comparing real-time monitoring data with an expected effect, and evaluating a pollution traceability analysis effect. Pollution source positioning errors are reduced, pollution contribution rate calculation accuracy is improved, traceability efficiency is improved, the risk of excessive reagents is avoided, and treatment cost is reduced.

The application discloses an ultrathin defect-free ZIFs@GO composite film, a preparation method and application thereof, and comprises the following steps: 1) preparing GO by a modified Hummers method; 2) depositing GO on a polymer base film to prepare a GO composite film; and 3) growing ZIFs coordination polymers on the GO composite film by an interfacial counter-diffusion method to prepare the composite film. The application optimizes the ZIFs synthesis conditions and reduces non-selective defects to improve the separation performance of the ZIFs film. In the reverse diffusion process, GO acts as a barrier to make the precursor diffuse along the interlamellar gap and greatly slow down the diffusion rate; by optimizing the driving force of diffusion in the solution, the ZIFs crystallization rate can be accurately matched, the ZIFs growth content can be effectively reduced, and the generation of intercrystalline defects can be reduced. The GO lamella is rich in oxygen functional groups, which provides sites for the heterogeneous nucleation of ZIFs, especially at the edges and defects of the GO lamella, so that the non-selective defects in the GO film can be effectively reduced; meanwhile, the nanoscale limitation enables the ZIFs heteroepitaxial growth to be carried out along the two-dimensional channel instead of the vertical direction, which is beneficial to the formation of an ultrathin crystal structure and realizes the preparation of the ultrathin defect-free composite film.

The invention discloses a cyclic peptide binding agent design deep learning algorithm based on discrete diffusion guidance. The method comprises the following specific steps: pre-training a discrete diffusion model by using polypeptide monomer data, and finely tuning polypeptide-protein compound data to enable the model to learn a peptide-protein interaction rule; and introducing a high-precision cyclopeptide structure prediction model as an external guide module, performing real-time structure evaluation on the intermediate sequence in a back diffusion sampling process, constructing a guide signal based on indexes such as interface accuracy and local structure confidence, dynamically correcting de-noising distribution, and guiding to generate a cyclopeptide sequence with structural rationality and high binding potential. According to the method, the cyclopeptide ligand sequence set with the potential binding capacity can be automatically generated only according to the input target protein sequence, the cyclopeptide drug design efficiency is remarkably improved, and a new calculation method is provided for cyclopeptide drug research and development.

The invention discloses a method for preparing a pure-phase doped ternary precursor by a spray pyrolysis method based on a chlorate system, and relates to the technical field of inorganic chemistry and material science, and the method comprises the following steps: in a spray pyrolysis temperature rise stage, continuously sampling an ion flux field containing a plurality of metal ions in the chlorate system, and establishing a metal ion migration asynchronous analysis baseline, and generating a migration-diffusion difference graph for representing the relative deviation of the metal ion migration rate. According to the method, by constructing a diffusion difference graph and a stress density spectrum and combining an electric static force field and acoustic flow regulation and control, doping and main metal migration synchronization is achieved; and through cooperation of chlorate structure reconstruction and magnetic heat, electroacoustic and photo-thermal three-field cooperative control, a reverse diffusion trap is eliminated, doping clamping is stabilized, and the phase purity and the structure consistency of the ternary precursor are improved.

The application discloses a lake pollution source tracing analysis method based on multi-source data assimilation and reverse diffusion, relates to water pollution source tracing analysis, and comprises the following steps: after chemical pollution is monitored downstream of a lake, the monitored data is introduced into a water dynamics-water quality model after Kalman filtering, and space-time distribution data of the pollutants in the water body are acquired; pollution source inversion is carried out based on a differential evolution Markov chain Monte Carlo method, and pollution source parameters are acquired; forward simulation is carried out, a pollutant transport model is generated after a flow velocity field and water depth are solved by using the water dynamics-water quality model, the pollution source parameters are used as input, the space-time evolution of the pollutant concentration is predicted by using a finite volume method to discretize a control equation based on the pollutant transport model, and the pollution duration under natural attenuation is evaluated; and the real-time monitored data is compared with the expected effect, and the pollution source tracing analysis effect is evaluated. The application reduces the positioning error of the pollution source, improves the calculation accuracy of the pollution contribution rate, improves the source tracing efficiency, avoids the risk of excessive reagents, and reduces the treatment cost.

The invention provides a protein structure generation method based on a diffusion model, relates to the technical field of artificial intelligence, and belongs to the technical field of biomedicine and AI crossing. According to the method, a new protein skeleton structure is constructed step by step by simulating a'generation-denoising 'process of protein, and the method comprises the following steps: expressing protein residues in a dual mode; wherein the dual modes comprise that the protein based on the point cloud is adopted only in the forward diffusion process and the protein based on the FSframe is adopted in the reverse diffusion process; performing feature fusion on the information of the protein residues; updating residue pair information after feature fusion through triangular multiplication; and improving the diffusion model to generate a protein structure. According to the invention, the contribution of amino acid to other sequence information can be selectively enhanced or weakened according to the relationship between amino acid and other amino acid, and key residue information between the amino acid and a protein structure can be more accurately captured.

This invention discloses an operation control method for achieving deep nitrogen removal in a membrane-aerated biofilm reactor, comprising the following steps: S1. Biofilm cultivation and thickness control; installing a hollow fiber permeable membrane module in the reactor, and controlling the ratio of membrane area to effective reactor volume to be 80-150 m². 2 / m 3 The invention employs the following steps: 1. Establishing a soft sensor for biofilm thickness based on the linear relationship between exhaust oxygen purity and bulk ammonia nitrogen concentration to regulate biofilm thickness; 2. Optimizing the denitrification process of the hybrid MABR process; Immersing the membrane module in anoxic suspended sludge zone, oxygen is transferred from the inside of the membrane to the outside biofilm via a reverse diffusion mechanism, while ammonia nitrogen and organic matter in the wastewater diffuse from the bulk liquid phase into the biofilm, forming an aerobic layer and anoxic layer from the inside out within the biofilm along the oxygen diffusion direction; 3. Deep denitrification and N2O emission reduction. This invention's operation control method reduces process energy consumption, achieves high denitrification rates, and saves energy and reduces emissions; furthermore, the biofilm exhibits excellent stability and extended lifespan.