Amitesh Maiti

Images are common means to represent spatial property variations in physical systems, but comparing images is nuanced due to stochastic variations and spatial correlations, which are neglected in routine analyses like the Kolmogorov-Smirnov test. To this end, we develop an image distinguishability analysis (IDA) test that makes pixel-by-pixel comparisons between image-like datasets through a generalized distance metric in the principal component (PC) space. Based on the supported hypothesis that inherent stochasticity is represented by independent Normal behavior of the PCs, we derive a statistical distribution and criticality criterion to determine whether images are distinguishable from established baselines. We apply the IDA test on images generated from molecular dynamics simulations to demonstrate scale invariance in the complex patterns of a nonequilibrium process. The IDA test is notably general with diverse potential applications, including microstructure classification and change detection, uncertainty quantification of property fields, and model validation against high-fidelity simulations and experiments.

Aminopolymer-based adsorbents are a prominent class of materials being used for direct air capture of CO2 at the industrial scale. However, improving their working lifetime, specifically by increasing their resilience to oxidative degradation, remains an ongoing challenge. Towards this end, functionalization of aminopolymers with non-amine functionalities such as hydroxyls has emerged in recent years as a promising strategy towards improving adsorbent lifetime. Although there is a growing body of work demonstrating the effectiveness of this approach and investigating the origin of this improved stability, studies to date have primarily focused on branched aminopolymer systems such as branched poly(ethylenimine). In this work, we use hydroxyl-functionalized linear poly(ethylenimine) to continue to probe the underlying protective mechanism of this strategy. A combination of thermogravimetric analysis, NMR relaxometry, differential scanning calorimetry, and computational simulations is used to better understand the relationship between extent of chemical functionalization, physical properties, and adsorbent performance.

3D printing of polymeric foams by direct-ink-write is a recent technological breakthrough that enables the creation of versatile compressible solids with programmable microstructure, customizable shapes, and tunable mechanical response including negative elastic modulus. However, in many applications the success of these 3D printed materials as a viable replacement for traditional stochastic foams critically depends on their mechanical performance and micro-architectural stability while deployed under long-term mechanical strain. To predict the long-term performance of the two types of foams we employed multi-year-long accelerated aging studies under compressive strain followed by a time-temperature-superposition analysis using a minimum-arc-length-based algorithm. The resulting master curves predict superior long-term performance of the 3D printed foam in terms of two different metrics, i.e., compression set and load retention. To gain deeper understanding, we imaged the microstructure of both foams using X-ray computed tomography, and performed finite-element analysis of the mechanical response within these microstructures. This indicates a wider stress variation in the stochastic foam with points of more extreme local stress as compared to the 3D printed material, which might explain the latter’s improved long-term stability and mechanical performance.

Pentaerythritol tetranitrate (PETN) is a commonly used energetic material with both military and civilian applications. Good ignition properties mandate a powdered material with a high surface area. However, existing experimental data on PETN powder suggest an active surface that leads to particle coarsening and gradual reduction of the specific surface area over time. In this work we review some of the atomic‐level and coarse‐grained potential models developed for PETN and discuss their applications for studying particle morphology, growth, and surface kinetics, including molecular diffusion and evaporation/condensation rates. Simulation methods include classical molecular dynamics, kinetic Monte Carlo, and transition state calculations.

It is a common practice to approximate the desorption rate of atoms from crystal surfaces with an expression of the form ν_eff exp(−ΔE/k_BT), where ΔE is an activation barrier to desorb and ν_eff is an effective vibrational frequency ∼10¹² s^-1. For molecular solids, however, such an approximation can lead to a many orders of magnitude underestimation of vapor pressure and sublimation rates due to neglected contributions from molecular internal degrees of freedom. Here, we develop a simple working formula that yields good estimates for a general molecular (or atomic) solid and illustrate the approach by computing equilibrium vapor pressure of three different molecular solids and an atomic solid, as well as the desorption rate of a foreign (inhibitor) molecule from the surface of a molecular solid.

A class II atomistic force field with Lennard-Jones 6–9 nonbond interactions is used to investigate equations of state (EOS) for important high explosive detonation products N2 and H2O in the temperature range of 700–2500K and pressure range of 0.1–10GPa. A standard sixth order parameter-mixing scheme is then employed to study a 2:1 (molar) H2O:N2 mixture, to investigate, in particular, the possibility of phase separation under detonation conditions. The simulations demonstrate several important results, including (i) the accuracy of computed EOS for both N2 and H2O over the entire range of temperature and pressure considered, (ii) accurate mixing-demixing phase boundary as compared to experimental data, and (iii) the departure of mixing free energy from that predicted by ideal mixing law. The results provide comparison and guidance to state-of-the-art chemical kinetic models.

Using the energetic material pentaerythritol tetranitrate as a specific example of molecular crystal, we describe the development of a simple coarse-graining procedure by grouping several atoms or whole functional groups into single charge-neutral beads. As compared to fully atomistic calculations the coarse-grained model speeds up simulations by more than two orders of magnitude. Yet, by adjusting only two parameters in the coarse-grained interaction, the model accurately predicts the lattice constants, sublimation energy, pressure-volume curve up to P=10GPa, and energetically the most stable facets. Computed surface and desorption energies, bulk modulus, and equilibrium morphology are reported as well.