Journal Article10.1021/OP500169M
Design of Experiments (DoE) and Process Optimization. A Review of Recent Publications
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TL;DR: This review summarizes selected publications from Organic Process Research & Development using DoE to show how processes can be optimized efficiently and how DoE findings may be applied to scale-up.
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About: This article is published in Organic Process Research & Development. The article was published on 20 Nov 2015.
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Citations
Evaluation of Reverse Microemulsion Parameters Over the Catalytic Performance of Promoted Fe–Co Catalysts for the Production of Light Olefins from Syngas Using Box–Behnken Design
TL;DR: In this paper, Mn and K promoted Fe-Co nanocatalysts supported on MgO were synthesized via microemulsion technique, and the effect of fabrication parameters (aging time, precursor concentration and annealing temperature) on the performance of the catalyst in Fischer-Tropsch synthesis was assessed.
การทำนายสมบัติของของไหลไฮบริดนาโนโดยใช้โครงข่ายประสาทเทียมและการประยุกต์ในการถ่ายโอนความร้อน
สหัสวัต แซวรัมย์
TL;DR: ทำนายสมบัติของของไหลไฮบริดนาโนโดยใช้โครงข่ายประสาทเทียมและการประยุกต์ในการถ่ายโอนความร้อน โดยใช้โครงข่ายประสาทเทียมแบบส่งไปข้างหน้า และแบบส่งไปข้างหน้าและด้านข้าง และใช้รูปแบบการเรียนรู้แบบ Levenbreg-Marquard พัฒนาโครงข่ายประสาทเทียมสำหรับทำนายสมบัติการนำความร้อน ความจุความร้อนจำเพาะ ความหนืด และความหนาแน่นของของไหลไฮบริดนาโนได้ค่า R มากกว่า 0.90
Enhancing thermal efficiency of earth-air tunnel heat exchangers (EATHE) through response surface methodology
Mohamed amine KHORCHEF,Mohamed Serier,Aboubakeur Benariba,Sheymaa Alazzawi +3 more
TL;DR: This study optimizes Earth-Air Tunnel Heat Exchanger systems using Response Surface Methodology, identifying pipe depth, length, air velocity, and thermal conductivity as critical factors influencing air temperature reduction in Algeria's Timimoun region.
How to Develop Organometallic Catalytic Reactions in the Pharmaceutical Industry
TL;DR: In this article , it is shown that a modest level of kinetic analysis is necessary to develop truly effective catalytic reactions, in addition to the utilization of modern technologies such as high-throughput experimentation and classical optimization tools such as Design of Experiments.
TCAD-Enabled Machine Learning—An Efficient Framework to Build Highly Accurate and Reliable Models for Semiconductor Technology Development and Fabrication
TL;DR: In this paper , a framework for automated data generation with the goal of efficiently providing a data set sufficient to build a reliable and actionable model is presented, which is applied to semiconductor fabrication, wherein TCAD, a set of simulation tools that reproduce the physical processing and the final electrical performance of semiconductor devices, is a well-established capability.
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