The Flow Chemistry Platform performs continuous-flow synthesis of monomers and polymers with precise reagent control, efficient mixing and heat transfer, and the safety and scalability advantages of flow over batch. A fully integrated in-line analytics suite monitors reactions in real time, generating on the order of 10,000 data points per run and supporting both discovery-scale screening and production-scale synthesis within a Design–Build–Test–Learn (DBTL) materials pipeline.

Key Specifications

Reactor Modules

Reactor modules share common pumping, mixing, and residence-time control and can be coupled for multi-step sequences.

Integrated In-Line Analytics

Simultaneous, in-line reaction monitoring from the reaction stream eliminates the bottleneck of off-line characterization and enables closed-loop control.

Representative Chemistries & Workflows

Core Flow-Synthesis Modalities

• Continuous-flow polymerization — controlled radical and other chain-growth systems with precise control of residence time, temperature, flow rate, molar ratios, and comonomer identity
• Photochemical and electrochemical synthesis — wavelength-selective and continuous electrochemical transformations, standalone or coupled in sequence
• Monomer synthesis and scale-up — continuous production of bio-derived building blocks (e.g., heterocyclic and disulfide-containing monomers), demonstrated to the kilogram scale
• Click and tolerant functionalization chemistries — water- and oxygen-tolerant schemes (e.g., thiol-ene) for biodegradable and biologically active polymers

Real-Time Monitoring & Kinetics Protocols

• In-line kinetic profiling — simultaneous NMR/FT-IR/UV-Vis monitoring of binary and ternary copolymerizations, capturing thousands of data points per run
• Residence-time and parameter optimization — systematic variation of residence time, molar ratios, flow rates, and temperature with immediate analytical feedback
• In-line molecular-weight determination — real-time weight-average molecular weight and dispersity via coupled SEC/MALS

Data-Driven & Closed-Loop Optimization

• Kinetic parameter estimation — across wide condition ranges (e.g., via Bayesian inference and Markov Chain Monte Carlo sampling)
• Predictive modeling — of monomer reactivity ratios, sequence distributions, and material properties such as degradability
• Standard outputs — scalable monomer/polymer product; time-resolved conversion, kinetic, and molecular-weight data; fully captured run metadata linking each run to its conditions (ELN/LIMS)