Monga chitsulo chosowa kwambiri chosowa, tellurium imapeza ntchito zofunika m'maselo a dzuwa, zida za thermoelectric, ndi kuzindikira kwa infrared. Njira zoyeretsera mwachikhalidwe zimakumana ndi zovuta monga kuchepa kwachangu, kugwiritsa ntchito mphamvu zambiri, komanso kuwongolera pang'ono. Nkhaniyi ikufotokoza mwadongosolo momwe matekinoloje opangira nzeru angakwaniritsire bwino njira zoyeretsera za tellurium.

1. Mkhalidwe Wamakono wa Tellurium Purification Technology

1.1 Njira Zachizolowezi Zoyeretsa Tellurium ndi Zochepa

Njira Zazikulu Zoyeretsera:

• Vacuum distillation: Yoyenera kuchotsa zonyansa zowira pang'ono (mwachitsanzo, Se, S)
• Kuyenga madera: Kumathandiza makamaka kuchotsa zonyansa zazitsulo (mwachitsanzo, Cu, Fe)
• Electrolytic refining: Kutha kuchotsa zonyansa zosiyanasiyana
• Kuyendera kwa nthunzi wamankhwala: Kumatha kupanga ultra-high-purity tellurium (kalasi ya 6N ndi pamwambapa)

Zovuta zazikulu:

• Zosintha zimatengera zomwe zikuchitika m'malo mongokhathamiritsa mwadongosolo
• Kuchotsa zonyansa kumafika m'mabotolo (makamaka pa zonyansa zopanda zitsulo monga mpweya ndi carbon)
• Kugwiritsa ntchito mphamvu kwambiri kumabweretsa kukwera kwamitengo yopangira
• Kusiyana kwakukulu kwa chiyero cha batch-to-batch ndi kusakhazikika bwino

1.2 Zofunikira Zofunikira pakukhathamiritsa kwa Tellurium Purification

Core Process Parameter Matrix:

2. AI Application Framework for Tellurium Purification

2.1 Kapangidwe Kakapangidwe kaukadaulo

Dongosolo la magawo atatu a AI Optimization System:

1. Zosanjikiza zolosera: Mitundu yolosera za zotsatira za kuphunzira pamakina
2. Zosanjikiza: Ma algorithms okhathamiritsa amitundu yambiri
3. Control layer: Real-time process control systems

2.2 Dongosolo la Kupeza Data ndi Kukonza

Multi-source Data Integration Solution:

• Deta ya sensor ya zida: magawo 200+ kuphatikiza kutentha, kupanikizika, kuthamanga
• Zambiri zowunikira: Zotsatira zakuwunika kwapaintaneti ndi spectroscopic
• Zambiri zakusanthula kwa labotale: Zotsatira zoyesa pa intaneti kuchokera ku ICP-MS, GDMS, ndi zina.
• Zambiri zopanga mbiri: Zolemba zopanga zaka 5 zapitazo (mabatchi 1000+)

Ntchito Zopanga:

• Nthawi zotsatizana zimakhala ndi m'zigawo pogwiritsa ntchito njira yotsetsereka ya zenera
• Kupanga mawonekedwe a kinetic kusuntha kosasunthika
• Kupititsa patsogolo matrices a process parameter interaction
• Kukhazikitsa zinthu ndi mphamvu zoyendera bwino

3. Tsatanetsatane wa Core AI Optimization Technologies

3.1 Kukwezeka Kwambiri pa Phunzirani Kutengera Njira

Neural Network Architecture:

• Zosanjikiza: magawo 56-dimensional process (zokhazikika)
• Zigawo zobisika: 3 LSTM zigawo (256 neurons) + 2 zigawo zogwirizana kwathunthu
• Zosanjikiza zotulutsa: Zizindikiro za 12-dimensional (kuyera, zodetsedwa, ndi zina)

Njira Zophunzitsira:

• Kusamutsa maphunziro: Kuphunzitsidwa kale pogwiritsa ntchito zoyeretsera zitsulo zofanana (mwachitsanzo, Se)
• Kuphunzira mwachidwi: Kukonza zopangira zoyesera pogwiritsa ntchito njira ya D-optimal
• Kuphunzira kulimbikitsa: Kukhazikitsa ntchito za mphotho (kuwongolera chiyero, kuchepetsa mphamvu)

Zochitika Zowonjezereka:

• Kukhathamiritsa kwa mbiri ya vacuum distillation: 42% kuchepetsa zotsalira za Se
• Kukhathamiritsa kwa kukhathamiritsa kwa Zone: 35% kusintha kwa Cu kuchotsa
• Kukhathamiritsa kwa Electrolyte: Kuwonjezeka kwa 28% pakuchita bwino kwapano

3.2 Maphunziro Othandizira Kuchotsa Zonyansa Zothandizira Pakompyuta

Mafanizidwe a Molecular Dynamics:

• Kupititsa patsogolo kwa Te-X (X=O,S,Se, ndi zina) ntchito zomwe zingatheke
• Kuyerekezera zonyansa kulekana kinetics pa kutentha osiyana
• Kuneneratu za mphamvu zowonjezera-zonyansa zomangira mphamvu

Kuwerengera Mfundo Zoyamba:

• Kuwerengera mphamvu zopanga zonyansa mu thiti ya tellurium
• Kuneneratu kwa mulingo woyenera kwambiri chelating mamolekyulu
• Kukhathamiritsa kwa njira zoyendetsera nthunzi

Zitsanzo za Ntchito:

• Kupezeka kwa buku lakale la oxygen scavenger LaTe₂, kuchepetsa mpweya kukhala 0.3ppm
• Mapangidwe a ma chelating agents, kukonza bwino kuchotsa mpweya ndi 60%

3.3 Digital Twin ndi Virtual Process Optimization

Digital Twin System Construction:

1. Mtundu wa geometric: Kutulutsa kolondola kwa zida za 3D
2. Chitsanzo chakuthupi: Kutengera kutentha kophatikizana, kusamutsa misa, ndi mphamvu zamadzimadzi
3. Chemical model: Integrated impurity reaction kinetics
4. Chitsanzo chowongolera: Mayankhidwe a machitidwe oyeserera

Njira Yowongoleredwa Mwachilungamo:

• Kuyesa 500+ kuphatikizika kwa njira mu digito
• Kuzindikiritsa magawo ofunika kwambiri (CSV kusanthula)
• Kuneneratu kwa mawindo abwino kwambiri (kusanthula kwa OWC)
• Kutsimikizira kulimba kwa njira (kuyerekeza kwa Monte Carlo)

4. Njira Yogwiritsira Ntchito Mafakitale ndi Kusanthula Mapindu

4.1 Ndondomeko Yoyendetsera Ntchito

Gawo I (miyezi 0-6):

• Kutumiza kwa machitidwe oyambira kupeza deta
• Kukhazikitsa database ya process
• Kupanga zitsanzo zolosera koyambirira
• Kukhazikitsa zowunikira zofunikira

Gawo II (miyezi 6-12):

• Kumaliza kwa digito mapasa system
• Kukhathamiritsa kwa ma core process modules
• Kukhazikitsa koyendetsa kotseka kozungulira
• Kupititsa patsogolo kachitidwe ka traceability

Gawo III (miyezi 12-18):

• Kukhathamiritsa kwathunthu kwa AI
• Machitidwe owongolera osinthika
• Machitidwe osamalira mwanzeru
• Njira zophunzirira mosalekeza

4.2 Zopindulitsa Pazachuma Zomwe Akuyembekezera

Nkhani Yophunzira ya 50-ton Year High-Purity Tellurium Production:

5. Mavuto Aukadaulo ndi Mayankho

5.1 Mabotolo Ofunika Kwambiri Aukadaulo

1. Zokhudza Ubwino wa Data:
   • Deta ya mafakitale imakhala ndi phokoso lalikulu komanso zosowa
   • Miyezo yosagwirizana pakati pa magwero a data
   • Kutenga nthawi yayitali kwa data yowunikira kwambiri
2. Generalization:
   • Kusiyanasiyana kwazinthu zopangira kumapangitsa kulephera kwachitsanzo
   • Kukalamba kwa zida kumakhudza kukhazikika kwadongosolo
   • Kufotokozera kwatsopano kwazinthu kumafuna kuphunzitsidwanso kwachitsanzo
3. Zovuta Zophatikiza System:
   • Kugwirizana pakati pa zida zakale ndi zatsopano
   • Kuchedwa kuyankha kwa nthawi yeniyeni
   • Zovuta zotsimikizira chitetezo ndi kudalirika

5.2 Njira Zatsopano

Kusintha kwa Data Yosinthira:

• GAN-based process data kupanga
• Kusamutsa maphunziro kubweza kusowa kwa data
• Kuphunzira koyang'aniridwa pang'ono pogwiritsa ntchito deta yopanda zilembo

Njira Yopangira Ma Hybrid Modelling:

• Fizikisi-zoletsa deta zitsanzo
• Mechanism-guided neural network architectures
• Multi-fidelity model fusion

Edge-Cloud Collaborative Computing:

• Kutumiza kwa Edge kwa ma algorithms owongolera ovuta
• Cloud computing ya ntchito zovuta kukhathamiritsa
• Kuyankhulana kwapafupi kwa 5G

6. Njira Zachitukuko Zamtsogolo

1. Intelligent Material Development:
   • AI yopangidwa ndi zida zapadera zoyeretsera
   • Kuwunika kopitilira muyeso kwa kuphatikiza kowonjezera koyenera
   • Kuneneratu za njira zatsopano zogwirira zonyansa
2. Kukhathamiritsa Kwathunthu:
   • Kudzizindikira ndondomeko limati
   • Self-optimizing ntchito magawo
   • Kudzikonza nokha kusakhazikika
3. Njira Zoyeretsera Green:
   • Kukhathamiritsa kwa njira zocheperako
   • Njira zobwezeretsanso zinyalala
   • Kuwunika kwenikweni kwa carbon footprint

Kupyolera mu kuphatikizika kwakuya kwa AI, kuyeretsedwa kwa tellurium kukuchitika kusintha kosinthika kuchoka pazochitika zoyendetsedwa ndi deta, kuchokera ku kukhathamiritsa kwamagulu mpaka kukhathamiritsa kwathunthu. Makampani amalangizidwa kuti atsatire njira ya "master planing, kukhazikitsidwa kwapang'onopang'ono", kuyika patsogolo zopambana pamasitepe ovuta ndikumanga pang'onopang'ono njira zoyeretsera zanzeru.