Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2504.18525

Automating Nanoindentation: Optimizing Workflows for Precision and Accuracy

Vivek Chawla·Dayakar Penumadu·Sergei Kalinin
View original source ↗Read source document ↗Export metadata ↓

Abstract

Nanoindentation is vital for probing mechanical properties, yet traditional grid-based workflows are inefficient for targeting specific microstructural features. We present an automated nanoindentation framework that integrates machine learning, real-time alignment, and adaptive indentation strategies. The system operates in three modes: standard automation, feature-based indentation via image-to-coordinate mapping, and large-scale indentation with full x, y, and z axis alignment. A key challenge (precise sample positioning across imaging and indentation stages) was met by correcting initial travel-distance errors (2.5-6 micrometres) through pixel-to-micron calibration, reducing alignment errors to the submicron level. Benchmark tests demonstrate phase-specific and orientation-guided indentation enabled by self-organising maps and macro imaging. The framework markedly improves precision, minimises user intervention, and enables efficient, targeted characterisation of complex materials. By providing a direct interface between nanoindentation instruments and Python-based automation frameworks, it can be adopted on most existing platforms. This work lays the foundation for next-generation autonomous mechanical testing tailored to microstructurally complex materials.

Explore related subjects

physics.ins-detcond-mat.mtrl-sci

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Vivek Chawla, Dayakar Penumadu, Sergei Kalinin. 2025-04-25. Automating Nanoindentation: Optimizing Workflows for Precision and Accuracy. https://arxiv.org/abs/2504.18525

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

True Alternating Current Scanning Tunneling Microscope (ACSTM): tunneling on insulators

Scanning Tunneling Microscopy (STM) has revolutionized our atomic scale understanding of surfaces and accelerated progress in nanotechnology. This technique, however, is restricted to metal or semiconducting samples, as it requires a tiny current to stabilize the tip-sample distance with atomic scale precision. We developed a new imaging and feedback method that relies on true alternating current (AC) without any direct current (DC) component. This technique does not only enable the imaging on non-conducting surfaces with atomic step resolution, like (thin) glass and oxides, it provides also access to high-frequency electronic signal coming from the sample. We demonstrate that it is possible to measure on 25nm thick silicon oxide with 10 MHz tunneling current.

physics.ins-det↗
arXiv2026

Charged-particle topology reconstruction with an in-liquid SiPM array

Liquid scintillator detectors instrumented with photosensors inside the scintillation volume preserve local optical information that is largely lost in conventional boundary-readout geometries. We demonstrate that this information is sufficient for charged-particle topology reconstruction using a sparse three-dimensional lattice of silicon photomultipliers. After validating the Geant4 detector response against measured photon-count distributions, a simulation-trained, time-informed convolutional neural network reconstructs the entry and exit points of through-going muons with median residuals of 1.91~cm and 2.39~cm, respectively. The reconstructed endpoints are geometrically consistent with acceptance regions defined by external trigger counters in cosmic-ray muon data. The same framework also reconstructs the production vertices of simulated positron starting-track events with a median residual of about 4.5~cm. These results establish the feasibility of topology-sensitive reconstruction using sparse in-liquid photosensor arrays in homogeneous liquid scintillator detectors.

physics.ins-det↗
arXiv2026

Characterization of immersed SiPM arrays in liquid scintillator between room temperature and $-30\,^{\circ}\mathrm{C}$

Liquid scintillator detectors instrumented with distributed silicon photomultiplier (SiPM) arrays can be used in compact, topology-sensitive, and low-background experiments, but the temperature dependence of SiPMs immersed directly in the scintillation medium has not been widely characterized. We report the operation of a 125-liter linear-alkylbenzene-based liquid scintillator detector read out by 125 SiPM channels immersed in the active volume, over the range from room temperature to $-30\,^{\circ}\mathrm{C}$. The detector response was measured with cosmic-ray muons, including stopping muons followed by their Michel-electron decay. Cooling from $+15\,^{\circ}\mathrm{C}$ to $-30\,^{\circ}\mathrm{C}$ reduced the SiPM dark-count rate by a factor of 13.5, increased the single-photoelectron response by 49.1%, and increased the cosmic-ray muon light yield by 16.7%. The improved photoelectron separation and baseline stability at low temperature enabled a selection of stopping-muon events, from which the effective muon lifetime was measured to be $1959\pm132\,\mathrm{ns}$, consistent with the value expected for a hydrocarbon scintillator once $μ^{-}$ capture on carbon is taken into account.

physics.ins-det↗