Work

Driving school for self-driving labs

Year: 2023

Type: article

Abstract: Self-driving labs benefit from occasional and asynchronous human interventions. We present a heuristic framework for how self-driving lab operators can interpret progress and make changes during a campaign.

Source: Digital Discovery

DOI: 10.1039/d3dd00150d

Authors: Kelsey L. Snapp, Keith A. Brown

Institution: Boston University

Language: English

Topic: Scientific Computing and Data Management

Subfield: Information Systems and Management

Field: Decision Sciences

Domain: Social Sciences

SDG: Quality education

Open Access status: diamond

Funders: National Science Foundation, U.S. Department of Energy, Google, Boston University, Honeywell Federal Manufacturing and Technologies, U.S. Army Combat Capabilities Development Command Soldier Center, National Nuclear Security Administration, Division of Civil, Mechanical and Manufacturing Innovation

Awards: G1635817318, RCN: Building an Interdisciplinary Community of Big Microdata Researchers, G2745467714, G2966921652, G3163715151, G4017088194, G4065033466, Tip-based Nanochemistry for Printing Soft Materials, G4714902204, G5467297720, G5784385526, G7725706467, G8334151965

OpenAlex ID: W4386870993

FWCI: 4.377

Cites: 55

Cited by: 17

Related to: 10