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Article
Open AccessDeep learning with plasma plume image sequences for anomaly detection and prediction of growth kinetics during pulsed laser deposition
Materials synthesis platforms that are designed for autonomous experimentation are capable of collecting multimodal diagnostic data that can be utilized for feedback to optimize material properties. Pulsed las...
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Article
Open AccessA dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments
Optimization of experimental materials synthesis and characterization through active learning methods has been growing over the last decade, with examples ranging from measurements of diffraction on combinator...
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Article
Open AccessLearning the right channel in multimodal imaging: automated experiment in piezoresponse force microscopy
We report the development and experimental implementation of the automated experiment workflows for the identification of the best predictive channel for a phenomenon of interest in spectroscopic measurements....
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Article
Open AccessDeep learning for exploring ultra-thin ferroelectrics with highly improved sensitivity of piezoresponse force microscopy
Hafnium oxide-based ferroelectrics have been extensively studied because of their existing ferroelectricity, even in ultra-thin film form. However, studying the weak response from ultra-thin film requires impr...
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Article
Experimental discovery of structure–property relationships in ferroelectric materials via active learning
Emergent functionalities of structural and topological defects in ferroelectric materials underpin an extremely broad spectrum of applications ranging from domain wall electronics to high dielectric and electr...
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Article
Anisotropic epitaxial stabilization of a low-symmetry ferroelectric with enhanced electromechanical response
Piezoelectrics interconvert mechanical energy and electric charge and are widely used in actuators and sensors. The best performing materials are ferroelectrics at a morphotropic phase boundary, where several ...
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Chapter and Conference Paper
Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery
Future scientific discoveries will rely on flexible ecosystems that incorporate modern scientific instruments, high performance computing resources, parallel distributed data storage, and performant networks a...
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Article
Open AccessDeep Bayesian local crystallography
The advent of high-resolution electron and scanning probe microscopy imaging has opened the floodgates for acquiring atomically resolved images of bulk materials, 2D materials, and surfaces. This plethora of d...
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Article
Open AccessGaussian process analysis of electron energy loss spectroscopy data: multivariate reconstruction and kernel control
Advances in hyperspectral imaging including electron energy loss spectroscopy bring forth the challenges of exploratory and physics-based analysis of multidimensional data sets. The multivariate linear unmixin...
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Article
Open AccessThermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging
Exploration of structure-property relationships as a function of dopant concentration is commonly based on mean field theories for solid solutions. However, such theories that work well for semiconductors tend...
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Article
Open AccessOff-the-shelf deep learning is not enough, and requires parsimony, Bayesianity, and causality
Deep neural networks (‘deep learning’) have emerged as a technology of choice to tackle problems in speech recognition, computer vision, finance, etc. However, adoption of deep learning in physical domains bri...
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Article
Open AccessExploring physics of ferroelectric domain walls via Bayesian analysis of atomically resolved STEM data
The physics of ferroelectric domain walls is explored using the Bayesian inference analysis of atomically resolved STEM data. We demonstrate that domain wall profile shapes are ultimately sensitive to the natu...
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Article
Open AccessAuthor Correction: Tensor factorization for elucidating mechanisms of piezoresponse relaxation via dynamic Piezoresponse Force Spectroscopy
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Article
Open AccessCausal analysis of competing atomistic mechanisms in ferroelectric materials from high-resolution scanning transmission electron microscopy data
Machine learning has emerged as a powerful tool for the analysis of mesoscopic and atomically resolved images and spectroscopy in electron and scanning probe microscopy, with the applications ranging from feat...
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Article
Open AccessTensor factorization for elucidating mechanisms of piezoresponse relaxation via dynamic Piezoresponse Force Spectroscopy
Spatially resolved time and voltage-dependent polarization dynamics in PbTiO3 thin films is explored using dynamic piezoresponse force microscopy (D-PFM) in conjunction with interferometric displacement sensing. ...
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Article
Open AccessImaging mechanism for hyperspectral scanning probe microscopy via Gaussian process modelling
We investigate the ability to reconstruct and derive spatial structure from sparsely sampled 3D piezoresponse force microcopy data, captured using the band-excitation (BE) technique, via Gaussian Process (GP) ...
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Article
Open AccessAuthor Correction: Deep learning analysis of defect and phase evolution during electron beam-induced transformations in WS2
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Article
Open AccessRevealing ferroelectric switching character using deep recurrent neural networks
The ability to manipulate domains underpins function in applications of ferroelectrics. While there have been demonstrations of controlled nanoscale manipulation of domain structures to drive emergent properti...
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Article
Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics
The use of statistical/machine learning (ML) approaches to materials science is experiencing explosive growth. Here, we review recent work focusing on the generation and application of libraries from both expe...
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Article
Open AccessNon-conventional mechanism of ferroelectric fatigue via cation migration
The unique properties of ferroelectric materials enable a plethora of applications, which are hindered by the phenomenon known as ferroelectric fatigue that leads to the degradation of ferroelectric properties...
