arXiv subjects

Vladimir V. Shvartsman

Publications and source records attributed to Vladimir V. Shvartsman.

14 recordsLinked to original sources

arXiv2026

Hierarchical automation of scanning probe microscopy through agentic orchestration and algorithmic control

Rapid advances in agentic artificial intelligence enable scientific systems to interpret open-ended objectives, combine heterogeneous information, invoke specialized tools, and revise experimental strategies as evidence accumulates. However, physical experimentation also contains many tasks for which agentic reasoning provides little advantage and can reduce reliability. Quantitative analysis, optimization, spatial targeting, validation, and instrument execution are often better posed as deterministic or algorithmic operations with explicit objectives and verifiable outputs. Here, we introduce a hierarchical architecture for autonomous experimentation that separates these roles. Agentic components interpret scientific intent, construct task-dependent experimental representations, evaluate accumulated evidence, and select high-level actions, whereas deterministic algorithms perform numerical analysis, coordinate selection, validation, and physical execution. We implement this architecture in piezoresponse force microscopy. Starting from a broad scientific question concerning the relation between local domain structure and polarization switching, the system constructs spatial descriptors from multichannel imaging, selects and analyzes local hysteresis measurements, adapts the spectroscopy waveform, and terminates the experiment when additional measurements cease to provide new evidence. The autonomous trajectory also identifies a confounding relationship between polarization state and domain-wall proximity and recognizes that the requested contrast is not independently represented within the available field of view. These results demonstrate a route toward scientific autonomy in which agents determine what evidence is required while algorithms determine how that evidence is acquired reproducibly and within validated physical constraints.

cond-mat.mtrl-sci↗

arXiv2026

Dynamic Multiband Microscopy: A Universal Paradigm for Quantitative Nanoscale Metrology

Scanning Probe Microscopy (SPM) is the primary tool for exploring nanoscale functionality, yet standard single-frequency operation is fundamentally limited, because the dynamic tip-sample interaction is mathematically underdetermined. While advanced methods such as Dual Amplitude Resonance Tracking (DART) and Band Excitation (BE) address this by tracking resonance, they face critical limitations: DART suffers from feedback instability on complex topographies, while Band Excitation is constrained by severe trade-offs between spectral resolution and acquisition speed. Here, we introduce Dynamic Multiband Microscopy (DMM), a general framework that bridges these gaps by combining multifrequency excitation with continuous frequency sweeping. We implement this within an automated experimental workflow that autonomously identifies and targets measurement points of interest. In combination with quantitative interferometric detection, this approach brings SPM to the fundamental limits of noise and spectral sensitivity. Validated on ferroelectric nanofibers, this platform enables simultaneous, crosstalk-free 3D polarization mapping, establishing a universal framework for autonomous, high-fidelity nanoscale metrology.

cond-mat.mtrl-sci↗

arXiv2025

Reward driven discovery of the optimal microstructure representations with invariant variational autoencoders

Microscopy techniques generate vast amounts of complex image data that in principle can be used to discover simpler, interpretable, and parsimonious forms to reveal the underlying physical structures, such as elementary building blocks in molecular systems or order parameters and phases in crystalline materials. Variational Autoencoders (VAEs) provide a powerful means of constructing such low-dimensional representations, but their performance heavily depends on multiple non-myopic design choices, which are often optimized through trial-and-error and empirical analysis. To enable automated and unbiased optimization of VAE workflows, we investigated reward-based strategies for evaluating latent space representations. Using Piezoresponse Force Microscopy data as a model system, we examined multiple policies and reward functions that can serve as a foundation for automated optimization. Our analysis shows that approximating the latent space with Gaussian Mixture Models (GMM) and Bayesian Gaussian Mixture Models (BGMM) provides a strong basis for constructing reward functions capable of estimating model efficiency and guiding the search for optimal parsimonious representations.

cs.LG↗

arXiv2025

Attention-Based Explainability for Structure-Property Relationships

Machine learning methods are emerging as a universal paradigm for constructing correlative structure-property relationships in materials science based on multimodal characterization. However, this necessitates development of methods for physical interpretability of the resulting correlative models. Here, we demonstrate the potential of attention-based neural networks for revealing structure-property relationships and the underlying physical mechanisms, using the ferroelectric properties of PbTiO3 thin films as a case study. Through the analysis of attention scores, we disentangle the influence of distinct domain patterns on the polarization switching process. The attention-based Transformer model is explored both as a direct interpretability tool and as a surrogate for explaining representations learned via unsupervised machine learning, enabling the identification of physically grounded correlations. We compare attention-derived interpretability scores with classical SHapley Additive exPlanations (SHAP) analysis and show that, in contrast to applications in natural language processing, attention mechanisms in materials science exhibit high efficiency in highlighting meaningful structural features.

cond-mat.mtrl-sci↗

arXiv2025

Materials Discovery in Combinatorial and High-throughput Synthesis and Processing: A New Frontier for SPM

For over three decades, scanning probe microscopy (SPM) has been a key method for exploring material structures and functionalities at nanometer and often atomic scales in ambient, liquid, and vacuum environments. Historically, SPM applications have predominantly been downstream, with images and spectra serving as a qualitative source of data on the microstructure and properties of materials, and in rare cases of fundamental physical knowledge. However, the fast-growing developments in accelerated material synthesis via self-driving labs and established applications such as combinatorial spread libraries are poised to change this paradigm. Rapid synthesis demands matching capabilities to probe structure and functionalities of materials on small scales and with high throughput. SPM inherently meets these criteria, offering a rich and diverse array of data from a single measurement. Here, we overview SPM methods applicable to these emerging applications and emphasize their quantitativeness, focusing on piezoresponse force microscopy, electrochemical strain microscopy, conductive, and surface photovoltage measurements. We discuss the challenges and opportunities ahead, asserting that SPM will play a crucial role in closing the loop from material prediction and synthesis to characterization.

cond-mat.mtrl-sci↗

arXiv2024

Measurements with Noise: Bayesian Optimization for Co-optimizing Noise and Property Discovery in Automated Experiments

We have developed a Bayesian optimization (BO) workflow that integrates intra-step noise optimization into automated experimental cycles. Traditional BO approaches in automated experiments focus on optimizing experimental trajectories but often overlook the impact of measurement noise on data quality and cost. Our proposed framework simultaneously optimizes both the target property and the associated measurement noise by introducing time as an additional input parameter, thereby balancing the signal-to-noise ratio and experimental duration. Two approaches are explored: a reward-driven noise optimization and a double-optimization acquisition function, both enhancing the efficiency of automated workflows by considering noise and cost within the optimization process. We validate our method through simulations and real-world experiments using Piezoresponse Force Microscopy (PFM), demonstrating the successful optimization of measurement duration and property exploration. Our approach offers a scalable solution for optimizing multiple variables in automated experimental workflows, improving data quality, and reducing resource expenditure in materials science and beyond.

cond-mat.mtrl-sci↗

arXiv2020

The influence of the distribution function of ferroelectric nanoparticles sizes on their electrocaloric and pyroelectric properties

We consider a model of a nanocomposite based on non-interacting spherical single-domain ferroelectric nanoparticles of various sizes embedded in a dielectric matrix. The size distribution function of these nanoparticles is selected as a part of the Gaussian distribution from minimum to maximum radius (truncated normal distribution). For such nanocomposites, we calculate the dependences of the reversible part of the electric polarization, the electrocaloric temperature change, and the dielectric permittivity on the external electric field, which have the characteristic form of hysteresis loops. We then analyze the change in the shape of the hysteresis loops relative to the particle size distribution parameters. We demonstrate that for the same mean-square dispersion, the remanent polarization, coercive field, dielectric permittivity maximums, maximums and minimums of the electrocaloric temperature change depend most strongly on the most probable radius, moderately depend on the dispersion, and have the weakest dependency on the nanoparticle maximum radius. We calculated and analyzed the dependences of pyroelectric figures of merit on the average radius of the nanoparticles in the composite. The dependences confirm the presence of a phase transition induced by the size of the nanoparticles, which is characterized by the presence of a maxima near the critical average radius of the particles, the value of which increases with increasing dispersion of the distribution function.

cond-mat.mes-hall↗

arXiv2019

Analytical description of the size effect on pyroelectric and electrocaloric properties of ferroelectric nanoparticles

Using Landau-Ginzburg-Devonshire theory and effective medium approximation, we analytically calculate typical dependences of the pyroelectric and electrocaloric coefficients on external electric field, temperature and radius for spherical single-domain ferroelectric nanoparticles. The considered physical model corresponds to the nanocomposite with small fraction of ferroelectric nanoparticles. Within the framework of the analytical model we establish how the size changes determine the temperature and field behavior pyroelectric and electrocaloric coefficients on example of BaTiO3 nanoparticles covered by a semiconducting shell and placed in a dielectric polymer. We show that by changing the particle size one can induce maxima of the pyroelectric coefficient and electrocaloric temperature variation, control their width, height and sign. Obtained analytical expressions allow selecting the interval of particle sizes, voltage, and/or temperature for which pyroelectric energy conversion and electrocaloric coefficient are optimal for applications. The observed size effect opens the possibility to control pyroelectric and electrocaloric properties of ferroelectric nanocomposites that can be important for their advanced applications in energy convertors and cooling systems.

cond-mat.mtrl-sci↗

arXiv2019

Ferromagnetic-like behavior of Bi0.9La0.1FeO3-KBr nanocomposites

We studied magnetostatic response of the Bi0.9La0.1FeO3-KBr composites (BLFO-KBr) consisting of nanosized (about 100 nm) ferrite Bi0.9La0.1FeO3 (BLFO) conjugated with fine grinded ionic conducting KBr. When the fraction of KBr is rather small (less than 15 wt percent) the magnetic response of the composite is very weak and similar to that observed for the BLFO (pure KBr matrix without Bi1-xLaxFeO3 has no magnetic response as anticipated). However, when the fraction of KBr increases above 15percent, the magnetic response of the composite changes substantially and the field dependence of magnetization reveals ferromagnetic-like hysteresis loop with a remanent magnetization about 0.14 emu/g and coercive field about 1.8 Tesla (at room temperature). Nothing similar to the ferromagnetic-like hysteresis loop can be observed in BLFO ceramics, which magnetization quasi linearly increases with magnetic field. Different physical mechanisms were considered to explain the unusual experimental results for BLFO-KBr nanocomposites, but only those among them, which are highly sensitive to the interaction of antiferromagnetic Bi0.9La0.1FeO3 with ionic conductor KBr, can be relevant. An appropriate mechanism turned out to be ferro-magneto-ionic coupling.

cond-mat.mtrl-sci↗

arXiv2018

Rotomagnetic coupling in fine grained multiferroic BiFeO3: Theory and experiment

Using Landau-Ginzburg-Devonshire (LGD) theory for BiFeO3 dense fine grained ceramics with quasi spherical grains and nanosized inter grain spaces enriched by elastic defects, we calculated a surprisingly strong size-induced increase of the AFM temperature caused by the joint action of rotomagnetic and magnetostrictive coupling. Notably that all parameters included in the LGD functional have been extracted from experiments, not assumed. Complementary we performed experiments for dense BiFeO3 ceramics, which revealed that the shift of antiferromagnetic transition to 690 K instead of 645 K for a single crystal. To explain theoretically the result, we consider the possibility to control antiferromagnetic state of multiferroic BiFeO3 via biquadratic antiferrodistortive rotomagnetic, rotoelectric, magnetostrictive and magnetoelectric couplings. According to our calculations the highest is the rotostriction contribution, the magnetostrictive and electrostriction contributions appeared smaller.

cond-mat.mtrl-sci↗

arXiv2018

Fixed Volume Effect on Polar Properties and Phase Diagrams of Ferroelectric Semi-ellipsoidal Nanoparticles

For advanced applications in modern industry it is very important to reduce the volume of ferroelectric nanoparticles without serious deterioration of their polar properties. In many practically important cases fixed volume (rather than fixed size) corresponds to realistic technological conditions of nanoparticles fabrication. The letter is focused on the theoretical study of the behavior of ferroelectric polarization, paramagnetoelectric coefficient and phase diagrams of semi-ellipsoidal nanoparticles with fixed volume V. Our approach combines the Landau-Ginzburg-Devonshire phenomenology, classical electrostatics and elasticity theory. Our results show that the size effects of the phase diagrams and polarization of semi-ellipsoidal BiFeO3 nanoparticles nontrivially depends on V. These findings provide a path to optimize the polar properties of nanoparticles by controlling their phase diagrams at a fixed volume.

cond-mat.mtrl-sci↗

arXiv2017

The electrocaloric effect in BaTiO$_3$ at all three ferroelectric transitions: anisotropy and inverse caloric effects

We study the electrocaloric (EC) effect in bulk BaTiO$_3$ (BTO) using molecular dynamics simulations of a first principles-based effective Hamiltonian, combined with direct measurements of the adiabatic EC temperature change in BTO single crystals. We examine in particular the dependence of the EC effect on the direction of the applied electric field at all three ferroelectric transitions, and we show that the EC response is strongly anisotropic. Most strikingly, an inverse caloric effect, i.e., a temperature increase under field removal, can be observed at both ferroelectric-ferroelectric transitions for certain orientations of the applied field. Using the generalized Clausius-Clapeyron equation, we show that the inverse effect occurs exactly for those cases where the field orientation favors the higher temperature/higher entropy phase. Our simulations show that temperature changes of around 1 K can in principle be obtained at the tetragonal-orthorhombic transition close to room temperature, even for small applied fields, provided that the applied field is strong enough to drive the system across the first order transition line. Our direct EC measurements for BTO single crystals at the cubic-tetragonal and at the tetragonal-orthorhombic transitions are in good qualitative agreement with our theoretical predictions, and in particular confirm the occurrence of an inverse EC effect at the tetragonal-orthorhombic transition for electric fields applied along the [001] pseudo-cubic direction.

cond-mat.mtrl-sci↗

arXiv2017

Weak ferromagnetism and short range polar order in NaMnF$_3$ thin films

The orthorhombically distorted perovskite NaMnF$_{3}$ has been predicted to become ferroelectric if an $a=c$ distortion of the bulk $Pnma$ structure is imposed. In order to test this prediction, NaMnF$_{3}$ thin films were grown on SrTiO$_{3}$ (001) single crystal substrates via molecular beam epitaxy. The best films were smooth and single phase with four different twin domains. In-plane magnetization measurements revealed the presence of antiferromagnetic ordering with weak ferromagnetism below the Néel temperature $T_N=66$ K. For the dielectric studies, NaMnF$_{3}$ films were grown on a 30 nm SrRuO$_{3}$ (001) layer used as a bottom electrode grown via pulsed laser deposition. The complex permittivity as a function of frequency indicated a strong Debye-like relaxation contribution characterized by a distribution of relaxation times. A power-law divergence of the characteristic relaxation time revealed an order-disorder phase transition at 8 K. The slow relaxation dynamics indicated the formation of super-dipoles (superparaelectric moments) that extend over several unit cells, similar to polar nanoregions of relaxor ferroelectrics.

cond-mat.mtrl-sci↗

arXiv2016

State transition and electrocaloric effect of BaZr$_{x}$Ti$_{1-x}$O$_3$: simulation and experiment

The electrocaloric effect (ECE) of BaZr$_{x}$Ti$_{1-x}$O$_3$ (BZT) is closely related to the relaxor state transition of the materials. This work presents a systematic study on the ECE and the state transition of the BZT, using a combined canonical and microcanonical Monte Carlo simulations based a lattice-based on a Ginzburg-Landau-type Hamiltonian. For comparison and verification, experimental measurements have been carried on BTO and BZT ($x=0.12$ and $0.2$) samples, including the ECE at various temperatures, domain patterns by Piezoresponse Force Microscopy at room temperature, and the P-E loops at various temperatures. Results show that the dependency of BZT behavior of the Zr-concentration can be classified into three different stages. In the composition range of $ 0 \leq x \leq 0.2 $, ferroelectric domains are visible, but ECE peak drops with increasing Zr-concentration harshly. In the range of $ 0.3 \leq x \leq 0.7 $, relaxor features become prominent, and the decrease of ECE with Zr-concentration is moderate. In the high concentration range of $ x \geq 0.8 $, the material is almost nonpolar, and there is no ECE peak visible. Results suggest that BZT with certain low range of Zr-concentration around $x=0.12 \sim 0.3 $ can be a good candidate with relatively high ECE and simutaneously wide temperature application range at rather low temperature.

cond-mat.mtrl-sci↗