Work

Comprehensive analysis and machine learning-based solutions for drift behavior in ambient Atomic Force Microscope conditions

Year: 2025

Type: article

Source: Engineering Applications of Artificial Intelligence

DOI: 10.1016/j.engappai.2025.111678

Authors: D. Gemici Deveci, T. Karakoyun Barandır, Ö. Ünverdi, C. Celebi, L.Ö. Temur, D.Ç. Atilla

Institutions: Altınbaş University, Izmir Institute of Technology, Yaşar University

Language: English

Topic: Force Microscopy Techniques and Applications

Subfield: Atomic and Molecular Physics, and Optics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4412447482

FWCI: 1.929

Cites: 47

Cited by: 7

Related to: 10