activity
20052026
most citedHyperspectral near infrared imaging using a tunable spectral phasor

2 citations · 3 across the 10 of their papers we have counts for

collaborators

10 papers

cond-mat.mtrl-sci2026

An Interfacial Balance Rule Governs Binder-Electrolyte Coupling in Lead-Free Perovskite Energy Storage

Arun Kumar, Ayush Kumar Pandey, Ankur Yadav +4

Electrode binders are conventionally regarded as inert structural components. Here, we show that in lead-free perovskite supercapacitors, the binder defines the optimal electrolyte…

cond-mat.mtrl-sci2026

Revealing the Role of Confined Molecular H in the Passivation of Defective Silicon Using First-Principles Simulations

Hania Azzam, Tobias Binninger, Benedikt Fischer +2

The passivation of silicon dangling bonds by hydrogen is a crucial requirement for silicon-based optoelectronic technology, especially for solar cells. Recent experiments on intens…

physics.optics2025

Density-encoded line integral convolution: polarisation optical axis tractography using centroidal Voronoi tessellation

Darven Murali Tharan, Marco Bonesi, Daniel Everett +4

Visualising complex polarimetry optical axis fields is challenging. We introduce density-encoded line integral convolution (DELIC), a novel approach that builds on the classic line…

physics.optics2025

Depth-resolved polarisation sensitive optical coherence tomography reveals the complex microanatomical response of cartilage to compression

Darven Murali Tharan, Marco Bonesi, Daniel Everett +5

Conventional methods for analysing cartilage microstructure under mechanical loading are largely destructive. In this work, we evaluate the efficacy of using depth-resolved polaris…

cond-mat.mtrl-sci2025

Sb2S3 and GaAs Absorber Layer-based Quantum Dot Solar Cells with Cadmium Telluride-based HTL: A Comparative Study

Sayak Banerjee, Anupam Chetia, Satyajit Sahu

Quantum dot solar cells (QDSC) are widely acknowledged to be one of the best solar energy harvesting devices in the present world. Absorber layer is a core component of a QDSC with…

cond-mat.mtrl-sci2025

Composition based machine learning to predict phases & strength of refractory high entropy alloys

M. Sreenidhi Iyengar, M. K Anirudh, P. H. Anantha Desik +1

Refractory high-entropy alloys can function at temperatures exceeding those of nickel-based superalloys. Aluminum, as an alloying element, contributes multiple advantageous charact…