Explore the Impact of Dimensional Characteristics on the Thermal Behavior of Nanomaterials

This research explains how temperature acts in tiny particles, such as ZrO₂, Ag, ZnO, NiO, and Al, using some cool tools: the Dixit–Srivastava EOS, the Birch–Murnaghan EOS, and a heat-focused model. We're essentially using these models to predict how temperature changes as these nanoparticles expand, and then verifying if our predictions match real-world experiments. Turns out, the Dixit–Srivastava EOS usually nails it, giving us the most accurate forecasts for all the materials. Interestingly, metals seem to cool down faster due to their surface, but ionic oxides are tougher and hold onto their heat better. So, it seems these EOS models with nanoscale adjustments work well, and we can use this knowledge to create better nanomaterials for electronics, energy, and structures.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-31
DOI
https://doi.org/10.5281/zenodo.18333572
Primary Topic
nanoparticles nucleation surface interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Explore the Impact of Dimensional Characteristics on the Thermal Behavior of Nanomaterials

R. C. Srivastava, Abhay P. Srivastava, Anod Kumar Singh, H. C. Srivastava et al.
Zenodo (CERN European Organization for Nuclear Research)
nanoparticles nucleation surface interactions
article

Explore the Impact of Dimensional Characteristics on the Thermal Behavior of Nanomaterials

R. C. Srivastava, Abhay P. Srivastava, Anod Kumar Singh, H. C. Srivastava, Brijesh Kumar Pandey
article en

Abstract

This research explains how temperature acts in tiny particles, such as ZrO₂, Ag, ZnO, NiO, and Al, using some cool tools: the Dixit–Srivastava EOS, the Birch–Murnaghan EOS, and a heat-focused model. We're essentially using these models to predict how temperature changes as these nanoparticles expand, and then verifying if our predictions match real-world experiments. Turns out, the Dixit–Srivastava EOS usually nails it, giving us the most accurate forecasts for all the materials. Interestingly, metals seem to cool down faster due to their surface, but ionic oxides are tougher and hold onto their heat better. So, it seems these EOS models with nanoscale adjustments work well, and we can use this knowledge to create better nanomaterials for electronics, energy, and structures.

Zenodo (CERN European Organization for Nuclear Research)
BML Munjal University (IN), University of Lucknow (IN), Sanskriti Samvardhan Mandal (IN), Indian Institute of Management Lucknow (IN)
Openalex Percentile: Top 30%
nanoparticles nucleation surface interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Explore the Impact of Dimensional Characteristics on the Thermal Behavior of Nanomaterials — R. C. Srivastava, Abhay P. Srivastava, et al. · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS