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Cited by in F6Publishing
For: Lathrop PM, Duan Z, Ling C, Elabd YA, Kravaris C. Modeling and Observer-Based Monitoring of RAFT Homopolymerization Reactions. Processes 2019;7:768. [DOI: 10.3390/pr7100768] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.3] [Reference Citation Analysis]
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1 Dürr R, Duvigneau S, Seidel C, Kienle A, Bück A. Multi-Rate Data Fusion for State and Parameter Estimation in (Bio-)Chemical Process Engineering. Processes 2021;9:1990. [DOI: 10.3390/pr9111990] [Reference Citation Analysis]
2 Bhadriraju B, Kwon JS, Khan F. Risk-based fault prediction of chemical processes using operable adaptive sparse identification of systems (OASIS). Computers & Chemical Engineering 2021;152:107378. [DOI: 10.1016/j.compchemeng.2021.107378] [Cited by in Crossref: 15] [Cited by in F6Publishing: 8] [Article Influence: 7.5] [Reference Citation Analysis]
3 Kandelhard F, Schuldt K, Schymura J, Georgopanos P, Abetz V. Model‐Assisted Optimization of RAFT Polymerization in Micro‐Scale Reactors—A Fast Screening Approach. Macromol React Eng 2021;15:2000058. [DOI: 10.1002/mren.202000058] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
4 Soroush M. Special Issue on “Computational Methods for Polymers”. Processes 2020;8:386. [DOI: 10.3390/pr8040386] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]