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Machine Learning of Temperature-dependent Chemical Kinetics Using Parallel Droplet Microreactors
Temperature is a fundamental regulator of chemical and biochemical kinetics, yet capturing nonlinear thermal effects directly from experimental data remains a major challenge due to limited throughput and model flexibility. Recent advances in machine learning have enabled flexible modeling beyond co
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