Q4 2026

Artificial intelligence for electrode quality control in battery manufacturing: Evaluating machine learning, deep learning, and transfer learning models for Tin, Zinc, and Titanium electrodes

Anesu Nyabadza · Muhammad Usman · Muhammad Bilal · Muhammad Arslan Ashraf · Ahmed Abdullahi · Waqas Ali · Ajaykumar Dubey · Sindhuja Arepalli · Palak Choubey · Dimuthu Fernando · Lola Azoulay-Younes · Dermot Brabazon
10.1016/j.jer.2026.02.010 385 المشاهدات 0 الاقتباسات
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الاستشهاد بهذا المقال (APA)
Anesu, N., Muhammad, U., Muhammad, B., Muhammad, A. A., Ahmed, A., Waqas, A., Ajaykumar, D., Sindhuja, A., Palak, C., Dimuthu, F., Lola, A., Dermot, B. (2026). Artificial intelligence for electrode quality control in battery manufacturing: Evaluating machine learning, deep learning, and transfer learning models for Tin, Zinc, and Titanium electrodes. Journal Engineering Research. https://doi.org/10.1016/j.jer.2026.02.010
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الوصول
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نُشر في
الرقم الدولي ISSN 2307-1877
الربعية Q4
درجة المؤشر القياس العربي 40
التخصص Engineering & Technology
الناشر Elsevier
الدولة 🇰🇼 Kuwait
عرض ملف المجلة →
المؤلفون
تفاصيل النشر
السنة 2026
اللغة English
أُضيف في 01 Aug 2026