Zvakananga Mabasa eArtificial Intelligence muKucheneswa kwezvinhu

I. Raw Material Kuongorora uye Pretreatment Optimization

1. .High-Precision Ore Grading: Kudzidza kwakadzama-kwakavakirwa kucherechedzwa kwemifananidzo masisitimu anoongorora hunhu hweores (semuenzaniso, saizi yechidimbu, ruvara, magadzirirwo) munguva chaiyo, kuwana pamusoro pe80% yekudzikisa kukanganisa zvichienzaniswa nekurongwa nemaoko.
2. .High-Efficiency Material Kuongorora: AI inoshandisa muchina kudzidza algorithms kukurumidza kuona vakachena-yakanyanya kuchena kubva kumamirioni emusanganiswa wezvinhu. Semuyenzaniso, mu lithium-ion bhatiri electrolyte kuvandudzwa, kuongorora kushanda zvakanaka kunowedzera nemirairo yehukuru kana ichienzaniswa nemaitiro echinyakare.

II. Dynamic Kugadziridzwa kweMatanho Paramita

1. .Key Parameter Optimization: Mu semiconductor wafer kemikari vapor deposition (CVD), ma AI mamodheru anotarisisa paramita se tembiricha uye kuyerera kwegasi munguva chaiyo, kushandura zvine simba maitiro ekudzikisa kusachena kwasara ne22% uye kuvandudza goho ne18%.
2. .Multi-Process Collaborative Control: Yakavharwa-loop mhinduro masisitimu anobatanidza kuyedza dhata neAI fungidziro kukwirisa synthesis nzira uye maitiro ekuita, kuderedza kucheneswa kushandiswa kwesimba nepamusoro pe30%.

III. Hungwaru Kusachena Kuonekwa uye Kudzora Hunhu

1. .Microscopic Defect Identification: Kuona kwekombiyuta yakabatanidzwa nepamusoro-resolution imaging inoona kuputika kwenanoscale kana kuparadzirwa kwehutsvina mukati mezvinhu, kuwana 99.5% yakarurama uye kudzivirira kusvibiswa kwekuita mushure mekuchenesa ⁸ .
2. .Spectral Data Analysis: AI algorithms inodudzira otomatiki X-ray diffraction (XRD) kana Raman spectroscopy data kuti ikurumidze kuona mhando dzetsvina uye kutariswa, ichitungamira nzira dzakanangana dzekuchenesa.

IV. Maitiro otomatiki uye Kubudirira Kuwedzera

1. .Robhoti-Inobatsirwa Kuedza: Hungwaru marobhoti masisitimu anogadzirisa kudzokorora mabasa (semuenzaniso, kugadzirisa mhinduro, centrifugation), kuderedza kupindira kwemanyore ne60% uye kuderedza zvikanganiso zvekushanda.
2. .Kuedza kwepamusoro-soro: AI-inotyairwa otomatiki mapuratifomu anogadzira mazana ezviyedzo zvekunatsa zvakafanana, achimhanyisa kuzivikanwa kweakakwana maitiro musanganiswa uye kupfupisa R&D kutenderera kubva pamwedzi kusvika kumavhiki.

V. Data-Inofambiswa Nechisarudzo-Kuita uye Multi-Scale Optimization

1. .Multi-Source Data Kubatanidzwa: Nekubatanidza kuumbwa kwezvinhu, maparamita ekuita, uye data rekuita, AI inovaka mamodheru ekufembera emhedzisiro yekucheneswa, ichiwedzera R&D budiriro nepamusoro pe40%.
2. .Atomic-Level Structure Simulation: AI inobatanidza density functional theory (DFT) kuverenga kufanotaura nzira dzekutama kweatomu panguva yekucheneswa, ichitungamira nzira dzekugadzirisa retice defect.

Case Study Kuenzanisa

Kuburikidza nenzira idzi, AI haingogadzirise paradigm yeR&D yekucheneswa kwezvinhu asiwo inofambisa indasitiri kuhungwaru uye budiriro inoenderera.