Inspired by biological systems, materials scientists have long sought to harness self-assembly to build nanomaterials. The challenge: the process seemed random and notoriously difficult to predict.

Researchers uncover geometric principles governing how particles self-assemble, solving a long-standing challenge in ...

Ferrocene is a key molecule for developing molecular machines. However, it readily decomposes on the surface of flat noble metal substrates, marking a significant challenge. Now researchers have ...

Princeton researchers have developed a new tool to speed the discovery of advanced materials known as metal organic ...

Scientists have developed molecular devices that can switch roles, behaving as memory, logic, or learning elements within the ...

As regulatory pressure increases, chemical companies are turning to AI to identify and replace PFAS and other restricted ...

With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green ...

If nonliving materials can produce rich, organized mixtures of organic molecules, then the traditional signs we use to ...

A new machine learning tool developed at Princeton will enable researchers to sift through trillions of design options to predict which metal organic framework will be useful in laboratories or ...

A recent study shows that bacteria living inside colorectal tumors form distinct ecosystems that are closely linked to how ...

Researchers say the innovation, known as SmartEM, will speed scanning sevenfold and open the field of connectomics to a ...