Phys Chem/Chem Phys Seminar

Abstract: Reliable theoretical prediction of complex chemical processes in condensed phases requires an accurate quantum mechanical description of interatomic interactions.  If these are to be used in a molecular dynamics calculation, they are often generated “on the fly” from approximate solutions of the electronic Schrödinger equation as the simulation proceeds, a technique known as ab initio molecular dynamics (AIMD).   However, due to the high computational cost of these quantum calculations, alternative approaches employing machine learning methods repre

Abstract: In order to harness the intrinsic ability of colloidal semiconductor nanocrystals to couple strongly with light, it is important to efficiently outcouple energy from photoexcited quantum dots (QDs), much like how nature uses molecular antennas to direct light during photosynthesis. This talk focuses on aromatic acceptor ligands for triplet-fusion based photon upconversion, where orbital overlap between the QD donor and molecular acceptor is critical for efficient energy transduction.

Abstract: Over that last 10+ years there has emerged some evidence that when a reaction vessel is reduced to the micron-sized dimensions (e.g. droplets), bimolecular reactions speed up by many orders of magnitude. The mechanism(s) for rate acceleration in droplets remains unclear but has clear implications for understanding the chemistry of atmospheric aerosols. A key uncertainty in the interpretation of droplet kinetics is how to properly link reaction rates measured in beaker scale containers with those occurring in micron-sized spaces.

Abstract: Reactions of the hydroxyl radical (OH) in the gas phase and at the gas-liquid interface initiate and propagate complex chemical schemes in combustion, planetary atmospheres, and the interstellar medium. In aqueous aerosols, the confinement of the reactants near the air-water interface leads to complex behavior of the particle reactive uptake with particle composition. In the gas phase, the branching ratio between the abstraction and addition mechanisms is highly dependent on the reactant’s structure and the gas temperature.

Absract: The promising optoelectronic properties of halide perovskites position them as candidate materials for solar cells, displays, and more. Their compositional and process flexibility provides a large and attractive design space and has led to outstanding optoelectronic figures of merit. However, the same flexibility also gives rise to challenges in reproducibility and phase stability.

Abstract: The efficiencies of devices utilizing semiconductor nanocrystals (NCs) are predominantly regulated by nonradiative processes. One key process in this regard is hot exciton cooling, wherein a highly excited electron-hole pair undergoes nonradiative relaxation to give rise to a band-edge exciton. The timescale and mechanism of this cooling process are not comprehensively understood.

Abstract: Solar hydrogen generation is pivotal to diversifying the global energy supply away from fossil fuels in the transportation sector and across major industries, including ammonia synthesis, process metallurgy, and hydrocarbon production [1,2].

Abstract: Many consequential chemical processes take place on ultrafast timescales, including molecular vibrations and bond breaking. Measurements that follow ultrafast molecular dynamics in real time are changing our understanding of these processes. We are designing new tools to study ultrafast molecular dynamics and quantum mechanics with the sensitivity enough to study the molecules in molecular beams and the spectral resolution sufficient for vibrational and rotational resolution.

Abstract: Quantum technologies based on molecules afford unique potential in miniaturization, spatial localization, and tunability through synthetic chemistry. Paramagnetic molecules constitute a platform for implementing quantum bits (qubits) and quantum sensors (qusors). While electron spin decoherence can potentially be leveraged in quantum sensing applications, its use is ultimately limited by spin relaxation, which effectively leaks quantum information into the environment.

Abstract: Machine-learning techniques are often applied to perform "end-to-end" predictions, that is to make a black-box estimate of a property of interest using only a coarse description of the corresponding inputs.
In contrast, atomic-scale modeling of matter is most useful when it allows to gather a mechanistic insight into the microscopic processes that underlie the behavior of molecules and materials.