Res2405 scialog web aut

Major advances in automated instrumentation and artificial intelligence (AI) are creating enhanced opportunities for innovation in basic research. Integrating automation and AI into chemical and biological laboratories could have profound impacts by broadening access within the chemical enterprise, optimizing results, improving safety and reproducibility of experiments, enabling people from across the world to conduct experiments they could not do at their own institutions, and increasing the time scientists dedicate to analyzing and understanding research outputs while reducing time spent on rote tasks. When deployed at scale, automation could lower many barriers in the field of synthetic chemistry. With full tele-synthesis and analysis available, ideas for novel synthetic targets could be taken from conceptualization to execution rapidly and efficiently.

This Scialog series will bring together about 50 early career scientists from distinct fields including all areas of synthetic chemistry (organic, inorganic, materials and biological), integrated and automated instrument development, engineering, materials science, computer and data science, and AI computer research. The goal is to create a dynamic, interdisciplinary community that will accelerate progress in the chemical sciences and laboratory automation through collaborative projects marrying advances in automation and AI to key questions in fundamental research. The group is also expected to have additional discussions on how the chemistry curriculum and workforce development must adapt to the changes in how basic chemistry research is conducted.

2024 Team Awards

Calibration-Free Quantitation of Reaction Yields in High-Throughput Reaction Screening through Absolute Carbon Quantification by LC-FID

  • James Grinias
    Chemistry & Biochemistry
    Rowan University
  • Connor Coley
    Chemical Engineering & Electrical Engineering and Computer Science
    Massachusetts Institute of Technology
  • Jessica Sampson
    Chemistry and Biochemistry
    University of Delaware

Getting on the Grid: Parallel Nano-Crystallography for Large-Scale Data Generation

  • Michael McGuirk
    Chemistry
    Colorado School of Mines
  • Andrea Pickel
    Mechanical Engineering
    University of Rochester

Automated Workflows to Assess Physical Constraints in Neural Networks for Molecular Property Prediction

  • Grant Rotskoff
    Chemistry
    Stanford University
  • Aditi Krishnapriyan
    Chemical Engineering / Computer Science
    University of California, Berkeley
  • Andrew Zahrt
    Chemistry
    University of Pennsylvania

Reducing the Cost of Device Development with Closed-Loop Proxy Measurements and Supplemental Characterization

  • Martin Seifrid
    Materials Science and Engineering
    North Carolina State University
  • Cory Simon
    Chemical Engineering
    Oregon State University
  • Connor Bischak
    Chemistry
    University of Utah

Closed-Loop Hypothesis Generation for Automated Chemical Synthesis

  • Jolene Reid
    Chemistry
    University of British Columbia         
  • Yu Gan
    Biomedical Engineering
    Stevens Institute of Technology

Structure Identification in Complex Chemical Mixtures Using Boltzmann Spectroscopy

  • Daniel Schwalbe-Koda
    Materials Science and Engineering
    University of California, Los Angeles
  • Gabe Gomes
    Chemistry / Chemical Engineering
    Carnegie Mellon University
  • Jeffrey Lopez
    Chemical and Biological Engineering
    Northwestern University

A Data-Driven Approach for Derisking Chemical Synthesis

  • Laura Ackerman-Biegasiewicz
    Chemistry
    Emory University
  • Gabe Gomes
    Chemistry / Chemical Engineering
    Carnegie Mellon University
2025 Team Awards

Achieving the Theoretical Limits of Information Gains in Automated Experimentation under Hardware Restrictions 

  • Daniel Schwalbe-Koda
    Materials Science and Engineering 
    University of California, Los Angeles 
  • Shijing Sun 
    Mechanical Engineering 
    University of Washington 

Autonomous Discovery of Single-phase High-Entropy Transition Metal Chalcogenides 

  • Zakaria Al Balushi 
    Materials Science and Engineering 
    University of California, Berkeley  
  • Pieremanuele Canepa 
    Electrical and Computer Engineering 
    University of Houston 
  • Shijing Sun 
    Mechanical Engineering 
    University of Washington 

CrysSolv: A Predictive Program for Solvent-Mediated Molecular Crystallization  

  • Michael McGuirk 
    Chemistry 
    Colorado School of Mines  
  • Andrew Zahrt 
    Chemistry 
    University of Pennsylvania 

Temporally Adaptive Design of Organic Flow Battery Systems 

  • Cailin Buchanan 
    Materials Science Division 
    Argonne National Laboratory  
  • Daniel Tabor
    Chemistry 
    Texas A&M University 

An Open-Source Modular Automated Laboratory System for Real-Time Monitoring of Continuous Electrosynthesis 

  • James Grinias 
    Chemistry & Biochemistry 
    Rowan University 
  • Long Luo 
    Chemistry 
    University of Utah 
  • Glen O’Neil 
    Chemistry & Biochemistry 
    Montclair State University 

Automated Design of Next-Generation Anion Exchange Membranes for Fuel Cells and Beyond  

  • Cailin Buchanan 
    Materials Science Division
    Argonne National Laboratory  
  • Badri Narayanan 
    Mechanical Engineering 
    University of Louisville  
  • Johanna Schwartz 
    Materials Science Division / Physical Life Sciences 
    Lawrence Livermore National Laboratory 

CRISIS: Comprehensive Reproducibility Initiative for Scientific Integrity and Standardization

  • Mark Hendricks 
    Chemistry 
    Whitman College  
  • Jessica Sampson 
    Chemistry and Biochemistry 
    University of Delaware 
  • Martin Seifrid 
    Materials Science and Engineering 
    North Carolina State University