From the 1 of 7 linked papers with an AI index.
7 papers
Dynamics of Null and Electrostatic Blind Spots for Quantitative PFM
Marti Checa, Holland Swicegood, Ruben Millan-Solsona +5
The paper investigates two operating conditions—null spots and electrostatic blind spots—in piezoresponse force microscopy, showing they are fundamentally different and providing m…
AEcroscopyWave: Towards Self-Driving Characterization Platforms for Agentic AI
Yongtao Liu, Jawad Chowdhury, Ganesh Narasimha +8
The characterization of electronic materials has traditionally been stratified into two distinct regimens: industry-scale automated systems to inspect materials for defects and ens…
Beyond Scalar Objectives: Expert-Feedback-Driven Autonomous Experimentation for Scientific Discovery at the Nanoscale
Ralph Bulanadi, Jefferey Baxter, Arpan Biswas +5
Self-driving laboratories or autonomous experimentation are emerging as transformative platforms for accelerating scientific discovery. Bayesian optimization (BO) is among the most…
Auto-3DPFM: Automating Polarization-Vector Mapping at the Nanoscale
Ralph Bulanadi, Marti Checa, Michelle Wang +9
The functional properties of ferroelectric materials are strongly influenced by ferroelectric polarization orientation; as such, access to consistent and precise characterization o…
Human-AI collaborative autonomous synthesis with pulsed laser deposition for remote epitaxy
Asraful Haque, Daniel T. Yimam, Jawad Chowdhury +10
Autonomous laboratories typically rely on data-driven decision-making, occasionally with human-in-the-loop oversight to inject domain expertise. Fully leveraging AI agents, however…
Beyond Optimization: Exploring Novelty Discovery in Autonomous Experiments
Ralph Bulanadi, Jawad Chowdhury, Funakubo Hiroshi +4
Autonomous experiments (AEs) are transforming how scientific research is conducted by integrating artificial intelligence with automated experimental platforms. Current AEs primari…