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VOL. 11, ISSUE 2 (2026)
Optimization techniques for chemically engineered nanomaterials using computational mathematics
Authors
D Shiny, V Sudhamami, E Premavathii, C George Braveen Singh, Athisaya Jensi
Abstract
The rapid advancement of
nanotechnology has enabled the design and synthesis of chemically engineered
nanomaterials with tailored properties for applications in medicine, energy,
and catalysis. However, traditional experimental approaches for optimizing
nanomaterial synthesis are time-consuming and resource-intensive. Computational
mathematics offers powerful optimization frameworks, including numerical
modeling, machine learning, and stochastic optimization, to accelerate the
design and performance tuning of nanomaterials. This paper presents a
comprehensive study of optimization techniques applied to chemically engineered
nanomaterials using computational methods. It discusses mathematical modeling
approaches, algorithmic optimization strategies, and multi-scale simulations
for predicting and controlling nanomaterial properties. The integration of
artificial intelligence, genetic algorithms, and uncertainty quantification is
also explored. The findings demonstrate that computational optimization
significantly enhances efficiency, accuracy, and scalability in nanomaterial
engineering, paving the way for next-generation materials design.
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Pages:22-27
How to cite this article:
D Shiny, V Sudhamami, E Premavathii, C George Braveen Singh, Athisaya Jensi "Optimization techniques for chemically engineered nanomaterials using computational mathematics". International Journal of Advanced Science and Research, Vol 11, Issue 2, 2026, Pages 22-27
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