arXiv subjects

Christopher C. Walker

Publications and source records attributed to Christopher C. Walker.

3 recordsLinked to original sources

arXiv2026

Data-Driven Micromechanical Characterization and Mapping of Shale Rocks Using High Speed Nanoindentation

This study investigates the potential of high-speed nanoindentation in collaboration with data analytics and phase volume fractions to achieve micromechanical characterization of heterogeneous rocks. While micromechanical characterization can be performed using mechanical testing alone, integrating chemical analysis-such as elemental mapping techniques-provides essential phase identification. This enables more accurate interpretation of phase-specific mechanical properties. However, incorporating chemical analysis increases the complexity of the process. Hence, this study proposes data-driven micromechanical characterization and mapping of heterogeneous rocks based primarily on mechanical data and limited dependence on chemical analysis. In this study, Mancos shale rock is analyzed using high-speed nanoindentation to determine the mechanical properties at the microscale. Subsequently, a suite of unsupervised statistical learning techniques, such as Uniform Manifold Approximation and Projection (UMAP) with k-means Clustering, Gaussian Mixture Model (GMM), Dirichlet Process Mixture Model (DPMM), and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), are applied to the nanoindentation data. Additionally, an automated image processing and segmentation technique was developed and tested. The results from each technique have been systematically compared against the conventional chemo-mechanical approach using two metrics: weighted error and spatial error. Based on the results, UMAP with k-means clustering is the most appropriate technique, while DBSCAN, DPMM, and image segmentation techniques are more suitable as secondary approaches. This study demonstrates the capability of high-speed nanoindentation combined with machine learning techniques for micromechanical characterization with reduced analytical complexity and improved workflow efficiency.

cond-mat.mtrl-sci↗

arXiv2023

Rapid Quantification of Dynamic and Spall Strength of Metals Across Strain Rates

The response of metals and their microstructures under extreme dynamic conditions can be markedly different from that under quasistatic conditions. Traditionally, high strain rates and shock stresses are measured using cumbersome and expensive methods such as the Kolsky bar or large spall experiments. These methods are low throughput and do not facilitate high-fidelity microstructure-property linkages. In this work, we combine two powerful small-scale testing methods, custom nanoindentation, and laser-driven micro-flyer shock, to measure the dynamic and spall strength of metals. The nanoindentation system is configured to test samples from quasistatic to dynamic strain rate regimes (10$^{-3}$ s$^{-1}$ to 10$^{+4}$ s$^{-1}$). The laser-driven micro-flyer shock system can test samples through impact loading between 10$^{+5}$ s$^{-1}$ to 10$^{+7}$ s$^{-1}$ strain rates, triggering spall failure. The model material used for testing is Magnesium alloys, which are lightweight, possess high-specific strengths and have historically been challenging to design and strengthen due to their mechanical anisotropy. Here, we modulate their microstructure by adding or removing precipitates to demonstrate interesting upticks in strain rate sensitivity and evolution of dynamic strength. At high shock loading rates, we unravel an interesting paradigm where the spall strength of these materials converges, but the failure mechanisms are markedly different. Peak aging, considered to be a standard method to strengthen metallic alloys, causes catastrophic failure, faring much worse than solutionized alloys. Our high throughput testing framework not only quantifies strength but also teases out unexplored failure mechanisms at extreme strain rates, providing valuable insights for the rapid design and improvement of metals for extreme environments.

cond-mat.mtrl-sci↗

arXiv2022

How cooperatively folding are homopolymer molecular knots?

Detailed thermodynamic analysis of complex systems with multiple stable configurational states allows for insight into the cooperativity of each individual transition. In this work we derive a heat capacity decomposition comprising contributions from each individual configurational state, which together sum to a baseline heat capacity, and contributions from each state-to-state transition. We apply this analysis framework to a series of replica exchange molecular dynamics simulations of linear and 1-1 coarse-grained homo-oligomer models which fold into stable, configurationally well-defined molecular knots, in order to better understand the parameters leading to stable and cooperative folding of these knots. We find that a stiff harmonic backbone bending angle potential is key to achieving knots with specific 3D structures. Tuning the backbone equilibrium angle in small increments yields a variety of knot topologies, including $3_1$, $5_1$, $7_1$, and $8_{19}$ types. Populations of different knotted states as functions of temperature can also be manipulated by tuning backbone torsion stiffness or by adding side chain beads. We find that sharp total heat capacity peaks for the homo-oligomer knots are largely due to a coil-to-globule transition, rather than a cooperative knotting step. However, in some cases the cooperativity of globule-to-knot and coil-to-globule transitions are comparable, suggesting that highly cooperative folding to knotted structures can be achieved by refining the model parameters or adding sequence specificity.

cond-mat.stat-mech↗