Exploring energy storage properties of norbornadiene binary liquid mixtures: DFT, TDDFT and surface plasmon analysis

Abstract This research aims to offer a comprehensive understanding of the complex interplay of molecular interactions in binary liquid mixtures containing norbornadiene (NBD). Molecular fluorescence and energy storage properties of NBD liquid mixture in presence of surface plasmons is studied along with Density Functional Theory (DFT), and Time-Dependent Density Functional Theory (TDDFT). These techniques allow for a detailed exploration of energetics, bonding patterns, solute–solvent interactions, and absorption spectra, providing a theoretical framework for understanding the mechanisms driving the behaviour of the mixtures. Additionally, this study examines the interaction between surface plasmons and NBD to uncover the underlying mechanisms and efficiency of fluorescence enhancement. The role of gold (Au) and zirconium nitride (ZrN) nanoparticles in modulating the fluorescence properties of NBD is analyzed, with a focus on extending the absorption range into the ultraviolet and visible regions for improved solar energy storage. Together, these investigations offer valuable insights into molecular interactions, fluorescence enhancement mechanisms, and energy storage capabilities, contributing to the development of advanced materials for energy capture and photo-switch applications.

Authors

Institutions

Publication Details

Journal
Physica Scripta
Published
2025-05-20
DOI
https://doi.org/10.1088/1402-4896/addafd
Citations
1
Primary Topic
Advanced Thermodynamics and Statistical Mechanics
Type
article
Field-Weighted Citation Impact
1.32
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring energy storage properties of norbornadiene binary liquid mixtures: DFT, TDDFT and surface plasmon analysis

Pratima Rajput, Richa Verma
1 citations
Physica Scripta
Advanced Thermodynamics and Statistical Mechanics
1.32
article

Exploring energy storage properties of norbornadiene binary liquid mixtures: DFT, TDDFT and surface plasmon analysis

Pratima Rajput, Richa Verma
article en
1 citations

Abstract

Abstract This research aims to offer a comprehensive understanding of the complex interplay of molecular interactions in binary liquid mixtures containing norbornadiene (NBD). Molecular fluorescence and energy storage properties of NBD liquid mixture in presence of surface plasmons is studied along with Density Functional Theory (DFT), and Time-Dependent Density Functional Theory (TDDFT). These techniques allow for a detailed exploration of energetics, bonding patterns, solute–solvent interactions, and absorption spectra, providing a theoretical framework for understanding the mechanisms driving the behaviour of the mixtures. Additionally, this study examines the interaction between surface plasmons and NBD to uncover the underlying mechanisms and efficiency of fluorescence enhancement. The role of gold (Au) and zirconium nitride (ZrN) nanoparticles in modulating the fluorescence properties of NBD is analyzed, with a focus on extending the absorption range into the ultraviolet and visible regions for improved solar energy storage. Together, these investigations offer valuable insights into molecular interactions, fluorescence enhancement mechanisms, and energy storage capabilities, contributing to the development of advanced materials for energy capture and photo-switch applications.

Physica ScriptaVol. 100(7)
Dr. A.P.J. Abdul Kalam Technical University (IN), Excel Life Sciences (India) (IN)
Openalex Percentile: Top 20%
Advanced Thermodynamics and Statistical Mechanics
1.32
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.