Magnetic impurity doped monolayer transition metal dichalcogenides (TMDs) have been theoretically predicted to be above room temperature ferromagnets when doping/alloying levels are high (greater than 15% substitution of the transition metal). Due to their monolayer thickness, RT ferromagnetic TMDs could be useful in highly efficient memory devices as interface exchange and strain coupling scales as 1/t FM.
Traditionally materials design relies on empirical methods such as trial-and-error, high-throughput screening, or combinatory experimentation. In contrast, inverse materials design adopts a systematic and computational approach to identify and engineer materials suitable for specific purposes. In this talk, I will present case studies highlighting the power of molecular theory and machine learning for the inverse design of nanostructured materials for chemical separation, wet adhesion, and electrochemical energy storage.
Polaritons are quasiparticles of mixed optical-material nature that provide an opportunity for designing new properties in material systems. Coupling vibrational modes to optical cavities results in vibration-cavity polaritons that have been shown to modify chemical reaction rates and branching ratios. Our group has been investigating whether cavities alter transient properties such as relaxation of molecular vibrations, which might explain the modified chemistry.
The forthcoming era of energy systems, propulsion, space re-entry vehicles, and nuclear reactors points to structural materials that can withstand increasingly extreme thermal environments. Body- centered cubic (BCC) refractory alloys are attracting renewed attention owing to the nature of atomic bonding and internal plastic dissipation pathways, yet at ambient conditions, they tend to exhibit ceramic-like behavior characterized by low toughness and ductility.
When molecules are coupled to an optical cavity, new light-matter hybrid states, so- called polaritons, are formed due to quantum light-matter interactions. With the experimental demonstrations of modifying chemical reactivities by forming polaritons under strong light-matter interactions, theorists have been encouraged to develop new methods to simulate these systems and discover new strategies to tune and control reactions. In this talk, I will first introduce the concept of polariton and discuss its relevance in the recent molecular polariton and polariton chemistry investigations.
Gels are key materials in biological systems such as tissues and may control biocondensate formation and structure. To further understand the effects of elastic environments on biomacromolecular assembly, we have investigated phase behavior and radii of coacervate droplets in polyacrylamide (PAM) networks as a function of the gel modulus. Poly-L-lysine (PLL) and sodium hyaluronate (HA) coacervate phases were prepared in PAM gels with moduli varying from 0.035 – 9.0 kPa. The size of the coacervate droplets is reported from brightfield microscopy and confocal fluorescent microscopy.
Small-Angle Scattering (SAS), including Small-Angle X-ray and Neutron Scattering (SAXS and SANS), is a powerful characterization technique for investigating the structure of biomacromolecules and their interactions. SAXS/SANS allows us to characterize structural features across a wide range of length scales, spanning from just a few nanometers to several hundred nanometers.
Conventional rechargeable batteries are formed using slurry-cast electrodes whose random nature and porosity limits both energy density and rate performance. As a general rule, such composite electrodes, consisting of a mixture of active material, solid electrolyte, and often conductive additives exhibit power and energy limitations due to the tortuosity of the ion and electron conduction pathways and lower than ideal energy densities due to the volume and mass of the additives.
An exciting research area in condensed matter and materials physics is the response of matter to ultrafast stimuli, such that the eigenmode oscillation period is relatively long. In ferroic materials, the strongly coupled order parameters (magnetization, polarization, strain) and their highly nonlinear responses to fields (magnetic, electric, mechanical, and thermal) provide additional design flexibility for discovering new fundamental phenomena and new device applications.
Computational approaches are increasingly employed to guide and understand experiments, offering a systematic and accelerated path to materials discovery. Automated ab-initio frameworks like aflow++ have rapidly expanded the volume of materials data, enabling the use of data-science methods for the prediction of new materials. These approaches have been used to study superconductors and thermoelectrics, and have proved fruitful with the discovery of new permanent Heusler magnets, superalloys, high-entropy ceramics, and phase change memory compositions.
