Publications by authors named "S Kalinin"
Scanning Transmission Electron Microscopy (STEM) coupled with Electron Energy Loss Spectroscopy (EELS) presents a powerful platform for detailed material characterization via rich imaging and spectroscopic data. Modern electron microscopes can access multiple length scales and sampling rates far beyond human perception and reaction time. Recent advancements in machine learning (ML) offer a promising avenue to enhance these capabilities by integrating ML algorithms into the STEM-EELS framework, fostering an environment of active learning.
View Article and Find Full Text PDFStructurally diverse pyrroles, indoles and imidazoles bearing an -ω-azidoalkyl moiety and an aldehyde or ketone function were prepared and successfully introduced into imine generation the intramolecular Staudinger/aza-Wittig tandem reaction. Reduction of the generated imines led to medicinally relevant nitrogen-containing fused heterocycles such as tetrahydropyrrolo[1,2-]pyrazines and diazepines. Rare 8-membered hexahydropyrrolo[1,2-][1,4]diazocine and 9-membered dihydro-4,8-(metheno)pyrrolo[1,2-][1,4]diazacycloundecine were also synthesized.
View Article and Find Full Text PDFArticle Synopsis
- The advancement of computation power and machine learning is enabling the automation of scientific discovery using scanning probe microscopes (SPM).* -
- A new Python interface library has been created to control SPMs from both local and remote high-performance computers, meeting the computational demands of machine learning.* -
- The developed platform allows for the operation of SPM in various workflows, facilitating automated processes for routine tasks and autonomous scientific research.*
Article Synopsis
- Combinatorial spread libraries enable the study of material properties across various concentrations and conditions, but traditionally require extensive functional property measurements.
- The authors introduce automated piezoresponse force microscopy (PFM) to efficiently analyze these libraries, specifically in the SmBiFeO system, which features a unique phase boundary between ferroelectric and antiferroelectric states.
- By utilizing PFM and developing a mathematical framework based on Ginzburg-Landau theory, they aim to streamline materials discovery and make their data accessible for further research in the field.
Article Synopsis
- * To speed up this process, integrating theory with automated experiments—known as "theory in the loop"—is becoming a key focus, allowing for real-time updates of theoretical models during experiments.
- * The authors propose a Bayesian method that creates digital twins of materials by simultaneously developing surrogate models for simulations and experiments, reducing uncertainty, and enhancing research applications across various complex material properties.