Framework design for weight-average molecular weight control in semi-batch polymerization

Salas, Santiago D.; Ghadipasha, Navid; Zhu, Wuming; McAfee, Terry; Zekoski, Thomas; Reed, Wayne F.; Romagnoli, José A.

doi:10.1016/j.conengprac.2018.06.004

Cited by 21 publications

(11 citation statements)

References 40 publications

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“…Free radical: solution, 193,201,206,[214][215][216][217] emulsion 161,210,211 ; stepgrowth, 207 olefin polymerisations, 208,209 RAFT 219,220 Artificial intelligence predictive/ modelling of reactions Prediction of appropriate conditions to obtain particular polymer properties Free radical, [221][222][223][224] olefin polymerisations 225,226 predictive/ modelling of properties…”

Section: Optimising Control Systemsmentioning

confidence: 99%

“…Recent work using the platform has shown not only automated analysis, but integration of optimisation systems. 185,[214][215][216][217] Targeting of molecular weight has been achieved both with simpler models 185,214 and using dynamic optimisation, with computational estimation of the state of the system from mathematical models in conjunction with the real-time analysis offered by ACOMP. [215][216][217] Further, the automatic tailoring of molecular weight distributions has also been achieved.…”

Section: Automationmentioning

confidence: 99%

“…185,[214][215][216][217] Targeting of molecular weight has been achieved both with simpler models 185,214 and using dynamic optimisation, with computational estimation of the state of the system from mathematical models in conjunction with the real-time analysis offered by ACOMP. [215][216][217] Further, the automatic tailoring of molecular weight distributions has also been achieved. 218 Predictive models have additionally been used elsewhere with online GPC to tailor MWDs.…”

Section: Automationmentioning

confidence: 99%

“…These researchers have also taken the next step in advancing the application of benchtop flow-NMR, whereby an algorithm was used to target a specific monomer conversion. 177 Summary of innovations in automation (relating to polymerisations) referred to in this section with a summary of the advantages offered (note: this is not designed to be a comprehensive library of all examples in the literature, rather a demonstration of the opportunities/possibilities with some relevant examples) 193,201,206,[214][215][216][217] emulsion; 161,210,211 step-growth, 207 olefin Fig. 7 Automated hybrid reactor for bottlebrush synthesis with fluid mechanical elements illustrated.…”

Section: Reaction Chemistry and Engineering Reviewmentioning

confidence: 99%

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Enabling technologies in polymer synthesis: accessing a new design space for advanced polymer materials

Knox

Warren

2020

React. Chem. Eng.

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Section: Optimising Control Systemsmentioning

confidence: 99%

Section: Automationmentioning

confidence: 99%

Section: Automationmentioning

confidence: 99%

Section: Reaction Chemistry and Engineering Reviewmentioning

confidence: 99%

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Enabling technologies in polymer synthesis: accessing a new design space for advanced polymer materials

Knox

Warren

2020

React. Chem. Eng.

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“…The main reason for using another algorithm as a measurement processor is to demonstrate that the estimator performance depends on the structure selection rather than estimation algorithm. EKF has been preferred for this validation because it is usually preferred in the industrial practice as it is easy to implement and robust if adequately calibrated [25,26]. Using the same number and choice of measured outputs Equation (19b) and partition between innovated and not innovated states Equation (22a), the estimation task has been addressed using the extended Kalman filter (Figure 8).…”

Section: Validationmentioning

confidence: 99%

A Geometric Observer-Assisted Approach to Tailor State Estimation in a Bioreactor for Ethanol Production

2020

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In this work, a systematic approach based on the geometric observer is proposed to design a model-based soft sensor, which allows the estimation of quality indexes in a bioreactor. The study is focused on the structure design problem where the set of innovated states has to be chosen. On the basis of robust exponential estimability arguments, it is found that it is possible to distinguish all the unmeasured states if temperature and dissolved oxygen concentration measurements are combined with substrate concentrations. The proposed estimator structure is then validated through numerical simulation considering two different measurement processor algorithms: the geometric observer and the extended Kalman filter.

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Automatic Continuous Online Monitoring and Control of Polymerization Reactions and Related Methods

Reed

2019

Encyclopedia of Analytical Chemistry

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Automatic continuous online monitoring and control of polymerization (ACOMP) is a widely applicable platform for monitoring and controlling polymerization reactions. It relies on the continuous extraction, dilution, and conditioning of a small sample stream from the reactor on which measurements by various combinations of detectors are made. By combining simultaneous data from multiple detectors continuous monitoring of salient reaction characteristics can be made, such as kinetics, conversion of comonomers, composition drift, evolution of molecular mass and intrinsic viscosity, and detection of unusual phenomena, such as microgelation and runaway reactions. A growing area for ACOMP is its integration into predictive and closed‐loop reaction control with intriguing possibilities for enhancement by machine learning and artificial intelligence. Typical detectors include light scattering (LS), ultraviolet (UV)/visible spectrophotometry, viscometry, refractivity, and polarimetry, while NMR, dynamic light scattering (DLS), Mie scattering, conductivity, and near infrared (IR) and Fourier‐transform infrared (FTIR) are also used. Recent additions to ACOMP include the ability to use multiple similar sensors to detect the onset and evolution of polymer stimuli responsive behavior during synthesis; for example copolymer compositions at which a lower critical solution temperature (LCST) occurs. ACOMP has been applied to free radical, controlled free radical, and condensation reactions, to micellar, emulsion, and inverse emulsion polymerization, to post‐polymerization and derivatization reactions, and to batch, semi‐batch, and continuous reactors. While ACOMP is not inherently a chromatographic method, its continuous stream can be used in automatic conjunction with gel permeation and other separation chromatographies. Recently, ACOMP has been deployed in full‐scale industrial polymerization reactors to optimize efficiency and product quality.

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Framework design for weight-average molecular weight control in semi-batch polymerization

Cited by 21 publications

References 40 publications

Enabling technologies in polymer synthesis: accessing a new design space for advanced polymer materials

Enabling technologies in polymer synthesis: accessing a new design space for advanced polymer materials

A Geometric Observer-Assisted Approach to Tailor State Estimation in a Bioreactor for Ethanol Production

Automatic Continuous Online Monitoring and Control of Polymerization Reactions and Related Methods

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