M. Parans Paranthaman, an expert in solid-state chemistry and materials science at the Department of Energy’s Oak Ridge National Laboratory, has been named R&D World’s 2026 Researcher of the Year. The honor recognizes his career translating fundamental materials research into practical technologies with real-world applications. Paranthaman, an ORNL Corporate Fellow and UT-Battelle Distinguished Inventor, joined ORNL in 1993. He has authored more than 500 peer-reviewed publications and possesses 65 U.S. patents.

The inherent aggregation-induced spectral broadening of organic narrowband emitters limits their practical applications. To address this challenge, Chinese researchers proposed a molecular conformation control strategy based on a central 8π-electron system, and successfully realized a groundbreaking photophysical phenomenon: Aggregation-induced ultra-narrowband emission (AIUNE). This unique AIUNE character demonstrates superiority in highly-doped OLED devices, achieving a record-narrowed electroluminescent FWHM of 13 nm. This research expands the library of narrowband emission materials and enriches relevant molecular design methodologies.

Researchers have developed a cellulose-based hydrogel sensor that maintains stable sensing performance in extreme cold using a zinc chloride and lithium bromide molten salt hydrate system, offering a sustainable and biodegradable platform for next-generation flexible wearable devices and human-machine interfaces. Published in Journal of Bioresources and Bioproducts, the study introduces a binary molten salt hydrate approach to dissolve natural cellulose efficiently within ten minutes. The resulting ionically conductive hydrogel achieves an impressive conductivity of 4.48 S/m and compressive strength of 2.48 MPa. Differential scanning calorimetry confirmed no water crystallization exothermic peaks from -80°C to 20°C, indicating exceptional anti-freezing capability. The material's shear-thinning properties further enable 3D printing of customized sensor geometries for human-machine interfaces.

A new review from Hasanuddin University highlights how chitosan and alginate-based composite beads could be the next-generation solution for sustainable wastewater remediation. By combining naturally derived biopolymers with functional additives, these composite beads demonstrate improved adsorption capacity, mechanical stability, reusability, and stronger pollutant binding. The review outlines a roadmap for advancing such composites into stimuli-responsive smart materials and extending their applications beyond water treatment to circular bioeconomy, smart agriculture, and even precision medicine.

What is heat, and what is useful work if a machine consists only of an atom and light particles? In modern quantum technologies, this kind of question connects thermodynamics with quantum physics. Researchers at the University of Basel, Switzerland, have developed a theoretical approach that can reconcile both theories.  

Designing Latent Heat Thermal Energy Storage (LHTES) systems requires time-consuming and computationally expensive computational fluid dynamics simulations. To overcome this bottleneck, a new study presents a hybrid physics-informed neural network (PINN) framework trained on a sparse ground-truth dataset. Together with a genetic algorithm-based multi-objective design optimization, this PINN framework enables rapid, autonomous exploration of the continuous LHTES design space and thermohydraulic trade-offs. This approach serves as a crucial tool for developing next-generation LHTES systems.