Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2503.13736

Near-zero Temperature Coefficient of Resistance for a Single-Walled Carbon Nanotube Polymer Nanocomposite

Milad Jafarypouria·Sergey Abaimov
View original source ↗Read source document ↗Export metadata ↓

Abstract

Temperature dependence of electrical resistance of single-walled carbon nanotube (SWCNTs)/epoxy nanocomposites, which is characterized by a temperature coefficient of resistance (TCR), is experimentally investigated. In the existing literature, there are biased TCR values with non-monotonic temperature dependence, including both negative and positive values. In this study, we demonstrate that the influence of environment temperature can be greatly minimized by ensuring the CNT/epoxy nanocomposite is fully cured along with controlling CNT concentration and selecting an appropriate polymer matrix. In addition, agglomeration of CNTs significantly influences the performance of CNT/polymer nanocomposites. Resistance values remained nearly constant at a CNT concentration of approximately 1 wt.% below the glass transition temperature. It is also observed that in a fully cured CNT/epoxy nanocomposite with the microscale conductive pathway as the main conductance mechanism, the coefficient of thermal expansion (CTE) of the matrix is a critical characteristic, resulting in a consistent increasing trend in TCR.

Explore related subjects

physics.app-ph

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Milad Jafarypouria, Sergey Abaimov. 2025-03-17. Near-zero Temperature Coefficient of Resistance for a Single-Walled Carbon Nanotube Polymer Nanocomposite. https://arxiv.org/abs/2503.13736

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

KEEP EXPLORING

Related papers

arXiv2026

Hyperbolic dynamic friction models for viscoelastic sliding and rolling contact

This paper considers the sliding and rolling contact between viscoelastic bodies. Combining linear viscoelastic rheologies for bristle-like elements with nonlinear dynamic friction models, and under the assumption of small deformations and displacement gradients, it derives a class of viscoelasto-kinematic equations, formulated as a system of semilinear partial differential equations (PDEs) governing the evolution of the frictional force, bristle deformations, and internal state variables at the interface between the contacting bodies. The resulting system is analysed mathematically, demonstrating that linear viscoelasticity preserves the hyperbolic character of the PDE systems typically encountered in rolling contact. The proposed theory is illustrated through representative examples of both sliding and rolling contact, highlighting that these two processes, whilst often treated as distinct, may in fact exhibit closely related underlying dynamics. Overall, the framework provides a general theoretical setting applicable to a broad class of viscoelastic frictional systems.

physics.app-ph↗
arXiv2026

Teaching an LLM agent to fit XRR curves with X-Ray Calc 3

The structure of a periodic multilayer X-ray mirror is obtained by fitting its X-ray reflectivity (XRR) curve, and the result depends on how the operator normalizes and trims the curve, frees parameters, and accepts a fit. The manual of the fitting program and the papers describing its engine leave these decisions to the operator, whose practice is tacit, so the fitting stays with the expert. To solve this problem, we proposed to develop a skill for a large language model (LLM) agent via elicitation: the expert's decisions were recorded during fitting and written as thirteen steps and a 22-item report template. The agent runs X-Ray Calc 3 through a Model Context Protocol (MCP) tool server. Fresh sessions, each given the skill, one curve, and a nominal design, were scored against fits the expert had withheld, under six tolerances fixed beforehand. The skill was developed on XRR curves of Co/C mirrors and of Ru/C mirrors from a public data deposit. The final version of the skill was tested on W/B4C multilayers. It was demonstrated that the skill recovered the mean period within 0.3 Å of the expert's fits and the period drift through the stack on both W/B4C specimens, and the W and B4C thicknesses within 1 Å on one of them.

physics.app-ph↗
arXiv2026

Dynamical Diversity for Reservoir Computing in Reconfigurable Nanomechanics

Physical reservoir computing uses nonlinear dynamics and a trained linear readout to process information. Nanoelectromechanical (NEMS) resonators combine geometric Duffing nonlinearity with fading memory, but most electromechanical implementations use a single resonance mode. Here, we demonstrate reservoir computing with two interacting modes of a single NEMS resonator measured through one readout port. We introduce dynamical diversity through complementary modal drive settings: the same input sequence is replayed under different allocations of drive amplitude between the modes, and the responses are concatenated into a single feature matrix. This multiplexing expands the representation available to the readout without additional devices or training of internal parameters. On NARMA-2, it reduces variance-normalized test error more than 28-fold relative to single-mode operation and more than threefold relative to the best individual two-mode setting. Linear memory-capacity measurements show that accessible recall spans only a few symbols at the tested symbol duration. Its rapid decline with delay, consistent with mechanical dissipation, accompanies rising NARMA error and the eventual loss of multiplexing gains at higher orders. We also use electrical feedthrough as an internal reference for assessing the computational contribution of the NEMS response. Separate linear readouts are trained on feedthrough features and features derived from the measured NEMS response, using the same recordings and matched drive settings and processing. On challenging nonlinear mapping tasks, the multiplexed NEMS features yield substantially lower errors than the feedthrough features. These results demonstrate how dynamical diversity through variations in modal drive amplitudes expands the computational capability of a single multimode NEMS resonator.

physics.app-ph↗