Polymers are diverse and versatile materials that have met a wide range of material
application demands. They come in several flavors and architectures (eg, homopolymers …

The artificial intelligence-based prediction of the mechanical properties derived from the
tensile test plays a key role in assessing the application profile of new polymeric materials …

As the problem of antibiotic resistance continues to escalate, there is an immediate need for
fresh antimicrobial strategies. Traditional antibiotic development processes are time …

Over the years, the grinding wheels industry has played a crucial role in mechanical
engineering. Grinding wheel specification is composed of various factors such as abrasive …

In this work, the straightforward synthesis of amphiphilic zwitterionic bioderived block
copolymers (BCPs) using glutamic acid (Glu) and cholesterol (Chol) as building blocks are …

We develop a probabilistic machine learning model and use it to screen for new hybrid
organic-inorganic perovskites (HOIPs) with targeted electronic band gap. The data set used …

Designing polymer membranes with high gas permeability and selectivity is a difficult multi-
task constrained problem due to the trade-off between these two properties. In this work, we …

In this study, an intricate machine learning assisted framework is introduced for the
designing of polymer acceptors. Machine learning (ML) models are trained to predict the …

Polymer informatics is an emerging discipline that has benefited from the strong
development that data science has experienced over the last decade. Machine learning …

Designing the materials with desirable properties is very difficult task. Experimental
approaches are expensive and time consuming. Machine learning (ML) guided screening is …