Zero-carbon energy and negative emission technologies are crucial for achieving a carbon
neutral future, and nanomaterials have played critical roles in advancing such technologies …

As an implementation tool of data intensive scientific research methods, machine learning
(ML) can effectively shorten the research and development (R&D) cycle of new materials by …

Data-driven material design has gained the position of “fourth paradigm” with the first three
being experiments, theory, and simulation. The statistical analysis and visualization of data …

Organic solar cells (OSCs) are ecofriendly and an inexpensive source of electricity
production. However, high-throughput screening and designing new materials without …

Due to the large versatility in organic semiconductors, selecting a suitable (organic
semiconductor) material for photodetectors is a challenging task. Integrating computer …

Near-infrared organic semiconductors are attractive candidates for photodetector
applications due to their inherent characteristics such as room temperature operating …

Designing effective materials for organic solar cells (OSCs) is a challenging and time-
consuming process. To achieve high performance OSCs, efficient designing/screening of …

Abstract Machine learning (ML) analysis has gained huge importance among researchers
for predicting multiple parameters and designing efficient donor and acceptor materials …

Non-invasive imaging tools are essential for diagnosis of complex disease. Photoacoustic
(PA) imaging is a multiscale noninvasive imaging modality with high resolution and …

Predicting and understanding the charge transport properties of organic semiconductors is a
crucial target for constructing efficient electronic devices such as photodetectors. To this end …