{"title":"原子力显微镜悬臂梁的非线性随机动力学研究","authors":"Aman K Singh, Subramanian Ramakrishnan","doi":"10.1115/1.4063601","DOIUrl":null,"url":null,"abstract":"Abstract Atomic Force Microscopy (AFM) serves characterization and actuation in nanoscale applications. We study the stochastic dynamics of an AFM cantilever under tip-sample interactions represented by the Lennard–Jones and Morse potential energy functions. In both cases, we also study the contrasting dynamic effects of additive (external) and multiplicative (internal) noise. Moreover, for multiplicative noise, we study the two sub-cases arising from the Ito and Stratonovich interpretations of stochastic integrals. In each case, we also investigate stochastic stability of the system by tracing the time evolution of the maximal Lyapunov exponent. Additionally, we obtain stationary probability densities for the unforced dynamics using stochastic averaging.","PeriodicalId":327130,"journal":{"name":"ASME Letters in Dynamic Systems and Control","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On the nonlinear stochastic dynamics of an Atomic Force Microscope cantilever\",\"authors\":\"Aman K Singh, Subramanian Ramakrishnan\",\"doi\":\"10.1115/1.4063601\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Atomic Force Microscopy (AFM) serves characterization and actuation in nanoscale applications. We study the stochastic dynamics of an AFM cantilever under tip-sample interactions represented by the Lennard–Jones and Morse potential energy functions. In both cases, we also study the contrasting dynamic effects of additive (external) and multiplicative (internal) noise. Moreover, for multiplicative noise, we study the two sub-cases arising from the Ito and Stratonovich interpretations of stochastic integrals. In each case, we also investigate stochastic stability of the system by tracing the time evolution of the maximal Lyapunov exponent. Additionally, we obtain stationary probability densities for the unforced dynamics using stochastic averaging.\",\"PeriodicalId\":327130,\"journal\":{\"name\":\"ASME Letters in Dynamic Systems and Control\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ASME Letters in Dynamic Systems and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4063601\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ASME Letters in Dynamic Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4063601","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the nonlinear stochastic dynamics of an Atomic Force Microscope cantilever
Abstract Atomic Force Microscopy (AFM) serves characterization and actuation in nanoscale applications. We study the stochastic dynamics of an AFM cantilever under tip-sample interactions represented by the Lennard–Jones and Morse potential energy functions. In both cases, we also study the contrasting dynamic effects of additive (external) and multiplicative (internal) noise. Moreover, for multiplicative noise, we study the two sub-cases arising from the Ito and Stratonovich interpretations of stochastic integrals. In each case, we also investigate stochastic stability of the system by tracing the time evolution of the maximal Lyapunov exponent. Additionally, we obtain stationary probability densities for the unforced dynamics using stochastic averaging.