recently-proposed photomolecular effect wherein polar liquids, principally pure water,can be made to evaporate at higher rates than possible through thermal evaporation alone under specific illumination conditions is experimentally investigated. Specifically, measurements of water mass loss were taken while independently varying illumination wavelength, intensity, angle of incidence and polarization. Prior experiments that resulted in data supporting the existence of the proposed effect were duplicated in an effort to obtain confirming results. Additionally, past experiments producing data consistent with the proposed photomolecular effect were duplicated and extended to evaluate their previously-unexplained results in the context of the photomolecular effect. An experiment specifically intended to directly measure vapor generated by the photomolecular effect was also conceived and built. The presented experiments ultimately failed to confirm or refute the existence of the proposed photomolecular effect, however qualitative analysis of obtained results suggests that the effect is considerably weaker than previously thought, depends on yet-unknown criteria, or possibly does not exist as expected.

The dynamics of photo-excited charge carriers near defects and interfaces plays a fundamental role in determining the efficiency and performance of a wide variety of optoelectronic and solar devices. Conventional optical pump-probe optical spectroscopies possess femtosecond temporal resolution, but their spatial resolution is constrained by the optical diffraction limit. One option to achieve simultaneously high temporal and spatial resolution is to integrate femtosecond lasers with electron microscopes. By coupling femtosecond photon pulses to the cathode in an electron microscope, it is possible to generate ultrafast, sub-picosecond electron pulses that are not constrained by optical diffraction.

Scanning ultrafast electron microscopy (SUEM) is a recently developed photon-pump electron-probe technique that uses short electron pulses to image the response of a sample surface after the impact of a photon pulse. SUEM is highly sensitive to surface charge dynamics, and has been used to study photocarrier diffusion in uniform materials and near interfaces. This dissertation describes the development process of SUEM at UCSB and documents various technical challenges encountered during its construction.

SUEM is then used to visualize the diffusion of photocarriers in BAs, a semiconductor with a unique phonon band structure and ultrahigh thermal conductivity. We observed ambipolar diffusion at low optical fluence with persistent hot carrier dynamics for above 200 ps, which can likely be attributed to the large frequency gap between acoustic and optical phonons, the same feature that is responsible for the high thermal conductivity. At higher optical fluence, we observed spontaneous electron-hole separation. Our results show BAs is an attractive optoelectronic material combining high thermal conductivity and excellent photocarrier transport properties.

Once thought to be an ordinary semiconductor, RuCl3 is a Mott-Hubbard insulator and host to a variety of exotic physics, including predictions of a photoinduced insulator-to-metal transition. We use SUEM to image the response of RuCl3 to photoexcitation. At low optical fluences, SUEM images show uniform bright contrast and slow carrier diffusion. At higher fluences, the material response becomes non-linear, potentially due to the predicted phase transition.

This thesis establishes SUEM as a platform to study the spatio-temporal evolution of excited carriers on extreme time and length scales. It then demonstrates its potential to study photocarrier transport in emerging and scientifically relevant systems. Future iterations of SUEM can continue improve upon spatial and temporal resolution and integrate other SEM detectors in order to be expanded into a versatile characterization platform.

The utilization of sustainable energy sources, such as solar energy and thermoelectric energy, has gained significant attention in addressing the global energy challenge. Despite their potential, the efficiency of the energy devices still requires improvement. A comprehensive understanding of the underlying mechanisms is essential for rationalizing efficient energy conversion systems. However, the conventional characterization techniques limited by their resolutions are insufficient for the mechanism study. To overcome this limitation, it is imperative to develop new characterization techniques to probe carrier and energy transport in the energy devices. This thesis employs theoretical and experimental approaches to investigate carrier and energy transport using three distinct novel techniques: a theoretical study of photo-carrier dynamics through Monte Carlo simulations in scanning ultrafast electron microscopy (SUEM), transient grating spectroscopy for simultaneous characterization of thermal transport and photocarrier dynamics in organic semicondutors, and customized cryogenic steady-state transport measurements to explore thermoelectric transport in topological materials.

Understanding the transport of photogenerated charge carriers in semiconductors is crucial for improving the performance of photovoltaics. While recent experimental studies using SUEM have demonstrated that the local change in the secondary electron emission induced by photoexcitation enables direct visualization of the photocarrier dynamics in space and time, the origin of the corresponding image contrast still remains unclear. Here, we investigate the impact of photoexcitation on secondary electron emissions from semiconductors using a Monte Carlo simulation aided by time-dependent density functional theory. Particularly, we examine two photoinduced effects: the generation of photocarriers in the sample bulk and the surface photovoltage (SPV) effect. Using doped silicon as a model system and focusing on primary electron energies below 1 keV, we found that both the hot photocarrier effect immediately after photoexcitation and the SPV effect play dominant roles in changing the secondary electron yield (SEY), while the distribution of photocarriers in the bulk leads to a negligible change in SEY. Our work provides insights into electron–matter interaction under photo-illumination and paves the way toward a quantitative interpretation of the SUEM contrasts.

In addition, the thermal management as well as carrier dynamics are both keys to the operational efficiency and stability for energy devices. Experimental techniques that can simultaneously characterize both properties are still lacking. We manage to characterize thin films of the archetypal organic semiconductor regioregular poly(3-hexylthiophene) and its blends with the electron acceptor [6,6]-phenyl-C61-butyric acid methyl ester on glass substrate. While the thermal responses from the thin film and the substrate cannot be distinguished due to their similar thermal diffusivities, we show that the recombination dynamics of photocarriers in the organic semiconductor thin films occur on a similar timescale and can be separated from the thermal response. Our measurements indicate that the photocarrier dynamics are determined by multiple recombination processes and our extracted recombination rates are in good agreement with previous reports using other techniques. We further apply TG spectroscopy to characterize another conjugated polymer and a molecular fluorescent material to demonstrate its general applicability. Our study indicates the potential of transient grating spectroscopy to simultaneously characterize thermal transport and photocarrier dynamics in organic optoelectronic devices.

In addition to semiconductors, topological semimetals have been shown to possess intriguing thermoelectric properties promising for energy harvesting and cooling applications. However, thermoelectric transport in heterostructures formed by topological and conventional materials remains less explored. Here, we systematically examine thermoelectric transport in a series of topological Dirac semimetal (Cd3As2)/ semiconductor(GaSb) heterostructures by employing a customized cryogenic steady-state transport measurement. Surprisingly, we found a significantly enhanced Seebeck coefficient at cryogenic temperatures when the Cd3As2 layer was thin. Combining angle-dependent quantum oscillation analysis, magneto-thermoelectric measurement, transport modeling and first-principles simulation, we reveal the contribution from multiple conducting channels in the heterostructure, including bulk and topological surface states. Our analysis showcases the rich transport physics in a topological Dirac semimetal/semiconductor heterostructure and suggests new routes to achieving unusual thermoelectric performance at cryogenic temperatures.

The quest for sustainable, efficient energy systems is more pressing than ever as we step into the 21st century. Finding the suitable materials for a specific technology is a very challenging task. The required properties can be unique to particular chemical compositions and structures. Furthermore, achieving high performance often demands the precise alignment of multiple interacting properties, which can have competing effects. Additional economic constraints, such as the cost of raw materials and the manufacturing process, further add to the challenges. Traditionally, this journey has been arduous, relying on slow and laborious experimental techniques. One pivotal approach that has revolutionized the pace and efficiency of this discovery process is High-throughput screening (HTS). HTS is a powerful and systematic methodology that enables the rapid evaluation of a large number of materials in a relatively short period by leveraging large databases, accurate and efficient computational techniques including ab initio calculations and machine learning. When large libraries of materials are screened based on specific properties or descriptors, only a limited amount of the most promising ones pass to the final stage for further validation through expensive calculations and experiments. This thesis aims to develop HTS pipelines on finding promising candidates for two energy applications: thermoelectric materials that convert heat into electricity, allowing for waste heat recovery, and magnetocaloric materials that serve an environmental friendly cooling technology. The integration of predictive models and screening pipelines significantly reduces the time and cost associated with material discovery, transforming the traditional methods of discovering and developing novel materials.

In the pursuit of innovative solutions for sustainable energy, thermoelectric materials hold undeniable potential to transform energy generation. They possess the unique ability to convert thermal energy into electricity, offering promising avenues for harnessing waste heat and enhancing energy efficiency. Achieving high thermoelectric performance requires efficient manipulation of thermal conductivity and a fundamental understanding of the microscopic mechanisms of phonon transport in crystalline solids. One of the major challenges in thermal transport is achieving ultralow lattice thermal conductivity. We use the anti-bonding character of the highest-occupied valence band as an efficient descriptor for discovering new materials with an ultralow thermal conductivity. We first examine the relationship between anti-bonding valence bands and low lattice thermal conductivity in model systems PbTe and CsPbBr3. Then, we perform a high-throughput search in the Materials Project database and identify over 600 experimentally stable binary semiconductors and report the anti-bonding strength in their valence bands. From our candidate list, we conduct a comprehensive analysis of the chemical bonds and the thermal transport in the XS family, where X=K, Rb, and Cs are alkaline metals. These materials all exhibit ultralow thermal conductivities less than 1~W/(m K) at room temperature despite simple structures. We attribute the ultralow thermal conductivity to the weakened bonds and increased phonon anharmonicity due to their anti-bonding valence bands. Our results provide chemical intuitions to understand lattice dynamics in crystals and open up a convenient venue towards searching for materials with an intrinsically low lattice thermal conductivity.

In another search for new energy materials, magnetocaloric materials are requested as promising candidates for energy-efficient and eco-friendly cooling technologies. These materials exhibit the magnetocaloric effect, where their temperature changes in response to the addition or removal of an external magnetic field. This unique property opens doors to environmentally friendly refrigeration systems since it eliminates the need for refrigerants with high global warming potential. Magnetic cooling based on the magnetocaloric effect is a promising solid-state refrigeration technology for a wide range of applications in different temperature ranges. Previous studies have mostly focused on near room temperature (300K) and cryogenic temperature (<10K) ranges, while important applications such as hydrogen liquefaction call for efficient magnetic refrigerants for the intermediate temperature 10K to 100K. For efficient use in this range, new magnetocaloric materials with matching Curie temperatures need to be discovered, while conventional experimental approaches are typically time-consuming and expensive. In this work, we report a computational material discovery pipeline based on a materials database containing more than 6000 entries auto-generated by extracting reported material properties from literature using a large language model. We then use this database to train a machine learning model that can efficiently predict magnetocaloric properties of materials based on their chemical composition. We further verify the magnetocaloric properties of predicted compounds using ab initio atomistic spin dynamics simulations to close the loop for computational material discovery. Using this approach, we identify 11 new promising magnetocaloric materials for the target temperature range. The joined force of AI advances and high-throughput search pipelines enables more efficient prediction and iteration. Together they are revolutionizing the conventional ways to discover new materials.

This research investigates using transient grating spectroscopy (TGS), a time-resolved optical technique that can generate and detect acoustic wave signatures with micrometer-scale wavelengths, to mechanically characterize hydrogels and other inhomogeneous soft matter in the frequency range of hundreds of MHz. Hydrogels are of interest because they are easily fabricated, tunable, and are compatible with biological tissues. Despite extensive studies of the static mechanical properties of hydrogels, their high-frequency mechanical response remains less explored. I provide a systematic approach across a range of polymer groups, from silicone rubbers to hydrogels in different solvents, to decompose the effects of crosslinking, swelling, and entanglements on their bulk acoustic wave speeds, which can then be related to a material’s elastic modulus. The information obtained from these bulk acoustic wave signals were also analyzed to understand the differences that arise in damping within each material. Through comparison of TGS results to static and/or low-frequency results obtained with traditional characterization methods like indentation and rheometry, the mechanical properties of hydrogels differ significantly in dynamic and static conditions. In particular, higher frequencies lead to similar mechanical properties despite polymer content differences. These differences are attributed to different response time scales of the polymer matrix and the embedded water. These results represent the first step to developing TGS as a noncontact, nondestructive characterization method to monitor hydrogels and related biological systems with potential applications in biomedical engineering. This project also demonstrates how we can model and subsequently develop hydrogels with precisely tunable and dynamic mechanical properties. By mapping broadband behavior of these soft matters from 0 Hz to the hundreds of MHz observed with TGS, this information can then be extrapolated to biological structures with similar properties and compositions and provide more information on less understood dynamic behavior of these gels.