چکیده مقاله
Nanoreactors represent cutting edge platforms for precise chemical synthesis, offering unprecedented control over reaction dynamics at the nanoscale However, their design, optimization, and scalability pose significant challenges that demand innovative computational tools This study explores the application of artificial intelligence AI , encompassing deep learning, reinforcement learning, and evolutionary optimization algorithms, to advance nanoreactor development Leveraging a hybrid dataset combining simulated and experimental data from microfluidic nanoreactors and porous nanostructures, we developed advanced models, including deep neural networks DNN , convolutional neural networks CNN , recurrent neural networks RNN , random forests RF , and genetic algorithms GA Statistical analyses, such as nonlinear multivariate regression, Bayesian sensitivity analysis, multilevel statistical modeling, uncertainty quantification, and spatiotemporal analysis, were employed to evaluate the models' accuracy, stability, and generalizability The results demonstrate that the hybrid DNN CNN RNN model outperformed others, achieving a coefficient of determination R² of 0 97, a root mean square error RMSE of 0 012, and a Bayesian information criterion BIC of 1600 Bayesian analysis identified temperature, pressure, nanoreactor geometry, flow rate, and surface properties of nanostructures as the most critical factors influencing yield, purity, and energy efficiency This study proposes an integrated framework for designing intelligent nanoreactors equipped with real time sensors, poised to revolutionize applications in pharmaceuticals, nanomaterials, clean energy, and advanced catalysis Furthermore, we introduce an innovative approach to integrate AI with self regulating nanoreactors, enabling dynamic optimization during reactions
کلیدواژهها
نویسندگان
Sepehr Ghasemlou
Bachelor of Engineering and Materials Science, Urmia University
Shayan Ghasemlou
Bachelor of Mechanical Engineering, Urmia University
شیوه ارجاع
Ghasemlou, Sepehr and Ghasemlou, Shayan,1404,Application of Artificial Intelligence in the Development of Nanoreactors for Precise Chemical Synthesis: An Integrated Approach Based on Deep Learning, Advanced Statistical Analysis, and Multiscale Optimization,21st International Conference on Innovation and Research in Engineering Sciences
ارائهشده در
مجموعه مقالات بیست و یکمین کنفرانس بین المللی نوآوری و تحقیق در علوم مهندسی31 تیر 1404