Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Overview of Microscopy Techniques01:22

Overview of Microscopy Techniques

The early pioneers of microscopy opened a window into the invisible world of microorganisms. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes that leveraged nonvisible light, such as fluorescence microscopy that uses an ultraviolet light source and electron microscopy that uses short-wavelength electron beams. These advances significantly improved magnification, image resolution, and contrast. By comparison, the...
Atomic Force Microscopy01:08

Atomic Force Microscopy

Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
The probe is regarded as the heart of any AFM setup and comprises the...
Scanning Electron Microscopy01:07

Scanning Electron Microscopy

A scanning electron microscope (SEM) is used to study the surface features of a sample by using an electron beam that scans the sample surface in a two-dimensional manner. Typically, areas between ~1 centimeter to 5 micrometers in width can be imaged. SEM can be used to image bacteria, viruses, tissues as well as larger samples like insects. Conventional SEM gives a magnification ranging from 20X to 30,000X and spatial resolution of 50 to 100 nanometers.
Fundamental Principles
Accelerated...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Beyond Optimization: Exploring Novelty Discovery in Autonomous Experiments.

ACS nanoscience Au·2026
Same author

Automated Construction of Artificial Lattice Structures with Designer Electronic States.

ACS nano·2025
Same author

Polarization Switching on the Open Surfaces of the Wurtzite Ferroelectric Nitrides: Ferroelectric Subsystems and Electrochemical Reactivity.

Advanced materials (Deerfield Beach, Fla.)·2025
Same author

Harnessing data and control with AI/ML-driven polymerization and copolymerization.

Faraday discussions·2025
Same author

Curvature-Controlled Polarization in Adaptive Ferroelectric Membranes.

Small (Weinheim an der Bergstrasse, Germany)·2025
Same author

Ferroelastic Domain-Induced Electronic Modulation in Halide Perovskites.

ACS applied materials & interfaces·2025

Related Experiment Video

Updated: Jul 16, 2026

Active Probe Atomic Force Microscopy with Quattro-Parallel Cantilever Arrays for High-Throughput Large-Scale Sample Inspection
05:04

Active Probe Atomic Force Microscopy with Quattro-Parallel Cantilever Arrays for High-Throughput Large-Scale Sample Inspection

Published on: June 13, 2023

Self-Driving Scanning Probe Microscopy: From Acceleration to Discovery and Manipulation.

Ganesh Narasimha1, Ralph Bulanadi1, Jawad Chowdhury1

  • 1Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States.

Accounts of Chemical Research
|July 14, 2026
PubMed
Summary

Self-driving microscopy (SDM) integrates artificial intelligence (AI) and machine learning (ML) to automate scanning probe microscopy. This accelerates discovery by enabling real-time data analysis and adaptive experimental control for materials science.

More Related Videos

Hand Controlled Manipulation of Single Molecules via a Scanning Probe Microscope with a 3D Virtual Reality Interface
11:00

Hand Controlled Manipulation of Single Molecules via a Scanning Probe Microscope with a 3D Virtual Reality Interface

Published on: October 2, 2016

Remote Magnetic Actuation of Micrometric Probes for in situ 3D Mapping of Bacterial Biofilm Physical Properties
14:42

Remote Magnetic Actuation of Micrometric Probes for in situ 3D Mapping of Bacterial Biofilm Physical Properties

Published on: May 2, 2014

Related Experiment Videos

Last Updated: Jul 16, 2026

Active Probe Atomic Force Microscopy with Quattro-Parallel Cantilever Arrays for High-Throughput Large-Scale Sample Inspection
05:04

Active Probe Atomic Force Microscopy with Quattro-Parallel Cantilever Arrays for High-Throughput Large-Scale Sample Inspection

Published on: June 13, 2023

Hand Controlled Manipulation of Single Molecules via a Scanning Probe Microscope with a 3D Virtual Reality Interface
11:00

Hand Controlled Manipulation of Single Molecules via a Scanning Probe Microscope with a 3D Virtual Reality Interface

Published on: October 2, 2016

Remote Magnetic Actuation of Micrometric Probes for in situ 3D Mapping of Bacterial Biofilm Physical Properties
14:42

Remote Magnetic Actuation of Micrometric Probes for in situ 3D Mapping of Bacterial Biofilm Physical Properties

Published on: May 2, 2014

Area of Science:

  • * Materials Science and Nanotechnology: Focus on advanced materials, heterostructures, and quantum materials characterization.
  • * Surface Science: Investigating surface energetics and reactions at the nanoscale.
  • * Spectroscopy and Imaging: Utilizing multimodal imaging for spatially resolved functional material property analysis.

Background:

  • * Traditional microscopy relies on sequential, operator-driven workflows, limiting throughput and efficient use of complex data.
  • * Current methods struggle to recognize critical information in real-time data streams.
  • * Limitations hinder the full potential of advanced materials characterization.

Purpose of the Study:

  • * To discuss the evolution of self-driving microscopy (SDM) from automated platforms to autonomous systems.
  • * To highlight the implementation of SDM for real-time data processing, optimization, and feature identification.
  • * To showcase how AI/ML integration in microscopy accelerates scientific discovery and material manipulation.

Main Methods:

  • * Integration of artificial intelligence (AI) and machine learning (ML) into microscopy workflows.
  • * Development of self-driving laboratories (SDL) and self-driving microscopy (SDM) systems.
  • * Application of advanced optimization strategies like Bayesian optimization and reinforcement learning.

Main Results:

  • * SDM enables real-time data processing and adaptive, decision-driven experimental operation.
  • * AI/ML integration accelerates microscopy, enabling efficient exploration of multidimensional parameter spaces.
  • * Autonomous workflows facilitate active material manipulation for nanoscale structure creation.

Conclusions:

  • * Self-driving microscopy significantly accelerates research by closing the loop between data acquisition, analysis, and control.
  • * SDM enhances the utilization of complex, high-dimensional data for scientific discovery.
  • * Formalized algorithmic workflows improve integration and scalability, positioning SDM at the forefront of experimental science.