Abstract Machine learning is a powerful tool that can provide a way to revolutionize the
material science. Its use for the designing and screening of materials for polymer solar cells …

For next-generation all-solid-state metal batteries, the computation can lead to the discovery
of new solid electrolytes with increased ionic conductivity and excellent safety. Based on …

Non-fullerene small molecules must absorb in a broader wavelength range for achieving
high efficiencies. This work presents seven indacenodithiophene core-based acceptor …

Density functional theory, along with its time dependent computational approach were
employed in order to fine tune the photovoltaic attributes along with the efficiency of the MO …

The competence of organic solar cells (OSCs) could be enhanced by improving the light
absorption capabilities as well as the open-circuit voltage (V oc) of utilized molecules. To …

Solid‐state lithium batteries (SSLBs) have received considerable attention due to their
advantages in thermal stability, energy density, and safety. Solid electrolyte (SE) is a key …

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 …

A new strategy of implementing intramolecular noncovalent interactions (INCIs) has been
adopted to design readily synthesizable acceptors for enhancing power conversion …

The earth's average temperature is being elevated owing to burning of fossil fuels, explicitly
releasing enormous amounts of CO 2 into the atmosphere. Therefore, effective collection …

Heavy metal ions are toxic causing a variety of health complications. Heavy metal ions
mainly include Cr (VI), Hg (II), Pb (II), Cd (II), Cu (II), Fe (III) and Co (II). The adsorption …