CCL

Research note

Accounts of Chemical Research

Automation and AI-Powered Prediction in Chromatographic Separation

Chengchun Liu and Fanyang Mo

A research perspective connecting automated experimentation, retention prediction, condition optimization, and closed-loop chromatographic separation.

10.1021/acs.accounts.5c00677

01 / Problem

Problem

Separation development connects molecular interactions, stationary phases, instruments, and operating conditions, yet these layers are often optimized separately through iterative experimentation.

02 / Approach

Approach

The perspective organizes the field across scales, linking automated experiments, retention prediction, condition optimization, and closed-loop decision making.

03 / Why it matters

Why it matters

It shows how predictive models and experimental automation can be treated as one connected workflow rather than isolated tools.

04 / Publication details

Publication details

Authors
Chengchun Liu and Fanyang Mo
Journal
Accounts of Chemical Research
Year

BibTeX

@article{liu2026aichromatography,
  title   = {Automation and AI-Powered Prediction in Chromatographic Separation},
  author  = {Chengchun Liu and Fanyang Mo},
  journal = {Accounts of Chemical Research},
  year    = {2026},
  date    = {2025-12-22},
  volume  = {59},
  number  = {1},
  pages   = {138--150},
  doi     = {10.1021/acs.accounts.5c00677},
  url     = {https://doi.org/10.1021/acs.accounts.5c00677}
}