{"title":"三维笛卡尔泊松-玻尔兹曼方程的解","authors":"F. Fonseca","doi":"10.12988/ces.2023.93001","DOIUrl":null,"url":null,"abstract":"We solve the 3d-Cartesian Poisson-Boltzmann equation (PBEq) for a 1 : 1 electric charge configuration, using the tanh, Ricatti functions and Jacobi elliptic solitary wave methods. Also, we apply a deep learning algorithm, specifically, physics-informed neural networks (PINNs), which is implemented in a Python library known as DeepXDE, finding good agreement between the analytical and the PINNs results.","PeriodicalId":10543,"journal":{"name":"Contemporary engineering sciences","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A solution of a 3d Cartesian Poisson-Boltzmann equation\",\"authors\":\"F. Fonseca\",\"doi\":\"10.12988/ces.2023.93001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We solve the 3d-Cartesian Poisson-Boltzmann equation (PBEq) for a 1 : 1 electric charge configuration, using the tanh, Ricatti functions and Jacobi elliptic solitary wave methods. Also, we apply a deep learning algorithm, specifically, physics-informed neural networks (PINNs), which is implemented in a Python library known as DeepXDE, finding good agreement between the analytical and the PINNs results.\",\"PeriodicalId\":10543,\"journal\":{\"name\":\"Contemporary engineering sciences\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Contemporary engineering sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12988/ces.2023.93001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contemporary engineering sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12988/ces.2023.93001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A solution of a 3d Cartesian Poisson-Boltzmann equation
We solve the 3d-Cartesian Poisson-Boltzmann equation (PBEq) for a 1 : 1 electric charge configuration, using the tanh, Ricatti functions and Jacobi elliptic solitary wave methods. Also, we apply a deep learning algorithm, specifically, physics-informed neural networks (PINNs), which is implemented in a Python library known as DeepXDE, finding good agreement between the analytical and the PINNs results.