A team of researchers led by Rensselaer Polytechnic Institute’s Edwin Fohtung, associate professor of materials science and engineering, has combined expertise in mathematics and condensed matter physics with technological advances to discover new properties of magnetic ferroelectric materials.  

A recent career fair at Rensselaer Polytechnic Institute served as a bit of a family reunion for the Dalakos family.

Thanks to a $304,084 Major Research Instrumentation award from the National Science Foundation (NSF), Rensselaer Polytechnic Institute is now home to a state-of-the-art single-crystal X-ray diffractometer.

Rensselaer Polytechnic Institute researchers have developed an accessible way to make N95 face masks not only effective barriers to germs, but on-contact germ killers. The antiviral, antibacterial masks can potentially be worn longer, causing less plastic waste as the masks do not need to be replaced as frequently.

Accurate predictive simulations of the electrochemical reactions that power solar fuel generators, fuel cells, and batteries could advance these technologies through improved material design, and by preventing detrimental electrochemical processes, such as corrosion. However, electrochemical reactions are so complex that current computational tools can only model a fraction of all relevant factors at one time — with limited accuracy. This leaves researchers reliant on the trial and error of significant and expensive experimentation.

TROY, N.Y. — Optoelectronic materials that are capable of converting the energy of light into electricity, and electricity into light, have promising applications as light-emitting, energy-harvesting, and sensing technologies. However, devices made of these materials are often plagued by inefficiency, losing significant useful energy as heat. To break the current limits of efficiency, new principles of light-electricity conversion are needed.

A COVID-19 transmission model inspired by gas-phase chemistry is helping the Centers for Disease Control and Prevention (CDC) forecast COVID-19 deaths across the country. Developed by Yunfeng Shi, an associate professor of materials science and engineering at Rensselaer Polytechnic Institute, and Jeff Ban, a professor of civil engineering at the University of Washington, the model uses fatality data collected by Johns Hopkins University and mobility data collected by Google to predict disease spread based on how much a population is moving within its community.