arXiv subjects

Hemant Nanavati

Publications and source records attributed to Hemant Nanavati.

4 recordsLinked to original sources

arXiv2026

Defining Ideal Phantom Polymer Networks

Elastomers are modeled as networks with $ϕ$-functional junctions containing $N$ ideal, $n$-segment, freely jointed chains (FJCs) per unit volume (p.u.v.). Our compact model of the exact FJC length probability density (Treloar, 1975), accurately yields their exact distribution moments (Flory, 1969). The governing geometry of fluctuations of $N_X = 2N/ϕ$ junctions p.u.v., parametrically maps their $λ$(elongation ratio)-dependent distribution to an equivalent FJC consisting of $n_{fϕ} = (n/ϕ)(1-Λ)$ segments, where $Λ= (1/3n)(λ^2 + 2/λ))$. The resulting elastic pre-factor, $N_{\text{eff}}kT = (N - ηN_X)kT$, with junction effectiveness $η= ϕ(1-Λ)/(ϕ-Λ)$, defines ideal phantom networks

cond-mat.soft↗

arXiv2025

PBPU Elastomer Network Architecture Determination via Corresponding States Analysis of Mechanical Behavior

In this work we examine the effect of R=[NCO]/[OH] in the R=<1 regime, on the resultant structural topology of polybutadiene polyurethane (PBPU) elastomer networks based on hydroxy-terminated polybutadiene (HTPB). We employ stress-elongation behavior and its modeling, as a tool. We examine this property via a combination of our model for the finite chain phantom networks incorporating the HTPB structural information, with the slip-tube model from the literature, suitably modified phenomenologically. We implement a further normalized Mooney-Rivlin (MR) representation (corresponding deformation states plots), to remove any magnitude bias on the model parameters. The now revealed curvatures of all the MR plots, in turn, reveals the non-correlation between the chain size and crosslink density. This discrepancy occurs due to the R-dependent majority presence of network defects due to sol effects (as obtained from swelling experiments) and non-load bearing pendant branches on the load-bearing network chains.

cond-mat.soft↗

arXiv2024

Physical phenomena during nanoindentation deformation of amorphous glassy polymers

We identify for visco-elasto-plastic (VEP) glassy polymers, physical phenomena during Berkovich nanoindentation, a locally imposed deformation. Live visuals via in situ nanoindentation indicate mainly sink-in during loading, with pile-up after unloading. Scanning Probe Microscopy (SPM) indicates significant volume conserving upflow below the tip, for these high nu, compliant materials, with compliance correlated high geometric fractional contact (including blunt height, h_b), (h_c+h_b)/(h_m+h_b)~0.86-0.95. We adapt the ideal conical indentation framework to VEP Berkovich nanoindentation, to calculate the contact area and visually depict the upflow and the displacement paths, in the material. The combination of SPM and P-h data, indicates a mixed comparison with uniaxial modulus and yield stress, with conventionally defined hardness, H<3*sig_y, and nanoindentation modulus E_N>E. By rationally removing viscoelastic (VE) effects from the loading P-h data, we find instant, zero-time hardness, H_L0>3*sig_y. We apply the power law model to only the recovery onset, to estimate pure elastic recovery. We then deconvolute the VEP nanoindentation into the conventional EP and elastic contributions, isolating the VE component. Constraint-induced sink-in, pile-up and VE recovery of the highly yielded tip-apex region, mirror the converse constrained deformation effects, governing the trends in conventionally defined H_L0 and E_N for glassy polymers.

cond-mat.soft↗

arXiv2024

Uniaxial Recovery Perspective of Glassy Polymer Nanoindentation

Sharp tip nanoindentation of glassy polymers is a constrained, localized viscoelastoplastic deformation. We interpret this complexity, in terms of the well-understood uniaxial deformation. From the uniaxial compression data in the literature, for PMMA, PC and crosslinked SU-8, we obtain their universal, yield-normalized recovery curves, with eps*=eps/eps_y, being one measure of the corresponding strain states (CSS). Nanoindentation recovery is determined from the 2sec constant rate unloading h-P data, modeled by a generalized power-law (variable power exponent). Comparing these data-sets, yields the correlation coefficient between the notional nanoindentation strain rate epsdot_N and strain and true strain rate and strain, c=epsdot_N/epsdot_t=eps_N/eps_t. The equivalent strain, eps, and the c value for any polymer, are within a narrow range, from the onset of indentation. Combining residual profiles via scanning probe microscopy with mathematical modeling of the indenter tip, provides the strain distribution beneath the tip. CSS measures examined here, indicate polymer-specific regions to regions common to glassy polymers, which are reached very early in the nanoindentation.

cond-mat.soft↗