Chemical Process Systems

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1 papers in the last 28 days · 0.0% of indexed attention

Twelve weeks of publication activity for this topic as it is defined today.

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Period ending 2026-09-07

1 new paper

A weekly snapshot of new work published in Chemical Process Systems.

17 papers

Latest in Chemical Process Systems

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  1. Differentiable Hybrid Modelling for Learning and Optimising Chemical Transport Processes from Experimental Data

    Sep 3, 2026Arthur Jessop, Mohammed Alsubeihi, Ben Moseley +1Chemical Process SystemsDifferentiable Relaxation

  2. DASyR-LLM: Domain-Aware Symbolic Regression with LLMs for Kinetic Model Discovery

    Aug 5, 2026Roberto Aliaga Medina, Paulina Quintanilla, Antonio del Rio ChanonaIncomplete KineticsSymbolic Regression

  3. CRAFTS: Collaborative Role-Adaptive Fine-Tuning of LLM Agents for Chemical Process Simulation

    Aug 2, 2026Ziyun Zhang, Yuxin Lin, Eldin Wee Chuan Lim +1Chemical Process SystemsEngineering

  4. Shared Symbolic Backbones for Physically Consistent Multi-Output Symbolic Regression

    Jul 29, 2026Manuel RodriguezSymbolic RegressionMultiple-Input Multiple-Output

  5. An LLM-Driven Workflow for Automated Process Control Strategy Generation and Tuning from Dynamic Process Models

    Jul 23, 2026Ari Luna Rueda, Eike Cramer, Klaus Hellgardt +1Chemical Process SystemsFeedback Linearization

  6. Synergizing Physically Constrained MCMC and Chemical-Informed Gaussian Processes for Reaction Network Discovery

    Jun 22, 2026Runzhe Liu, Zihao Wang, Wenbo Yang +1Chemical Process SystemsGaussian Process

  7. Embedding Linear Equality Constraints in Probabilistic Neural Networks for Dynamic Modelling

    Jun 19, 2026Matthew Marsh, Benoit Chachuat, Antonio del Rio ChanonaInequality ConstraintsChemical Process Systems

  8. Structure from Reasoning, Numbers from Search: On-Premise Open LLMs as Structural Priors for Coupled MIMO Controller Tuning

    Jun 9, 2026Jiaxuan Chen, Haonan Li, Yang ShuTuningFeedback Linearization

  9. Bayesian Optimization of a Multi-Product Chemical Reactor Using Composite Models and Partial Physics Knowledge

    Jun 7, 2026Liqiu Dong, Marta Zagórowska, Mehmet MercangözChemical Process SystemsBayesian Optimization

  10. Machine Learning-Driven Chemical Reactor Network Modeling of the Sandia-D Flame

    Jun 1, 2026Nicolas J. Tricard, Benjamin C. Koenig, Sili DengTurbofan EnginesChemical Process Systems

  11. Physics-Informed Deep Learning for Entropy Prediction in Heterogeneous Systems: Thermodynamic and Information-Theoretic Case Studies

    May 31, 2026Biswajeet Sahoo, Debadutta PatraConventional Physics-Informed Neural NetworksPhysics-Informed Deep Learning

  12. A Comparative Analysis of Machine Learning Algorithms for Multi-Task Prediction of the Parameters of the Pectin Hydrolysis--Extraction Process

    May 30, 2026Mullosharaf K. Arabov, Shavkat Yo. Kholov, Zainiddin K. MuhiddinChemical Process SystemsMulti--Task Learning

  13. Reinforcement Learning-based Control via Y-wise Affine Neural Networks: Comparative Case Studies for Chemical Processes

    May 20, 2026Austin Braniff, Yuhe TianChemical Process SystemsNeural Control

  14. From Data to Action: Accelerating Refinery Optimization with AI

    May 14, 2026Dániel Pfeifer, Ábrahám Papp, Tibor Bernáth +4Mixed-Integer Linear ProgrammingChemical Process Systems

  15. Meta-learning for sample-efficient Bayesian optimisation of fed-batch processes

    May 6, 2026Becky Langdon, Gabriel D. Patrón, Chrysoula D. Kappatou +6Bayesian OptimizationChemical Process Systems

  16. Privacy-Preserving Federated Learning Framework for Distributed Chemical Process Optimization

    Apr 28, 2026Teetat Pipattaratonchai, Aueaphum AueawatthanaphisutFederated Learning FrameworkChemical Process Systems

  17. Iterative Model-Learning Scheme via Gaussian Processes for Nonlinear Model Predictive Control of (Semi-)Batch Processes

    Apr 24, 2026Tai Xuan Tan, Alexander Mitsos, Eike CramerChemical Process SystemsGaussian Process