Earth-abundant materials for solar hydrogen generation

A critical challenge for the 21st century is shifting from the predominant use of fossil fuels to renewables for energy. Among many options, sunlight is the only single renewable resource with sufficient abundance to replace most or all of our current fossil energy use. However, existing photovoltaic and solar thermal technologies cannot be scaled infinitely due to the temporal and geographic intermittency of sunlight. Therefore efficient and inexpensive methods for storage of solar energy in a dense medium are needed in order to greatly increase utilization of the sun as a primary resource. For this purpose we have proposed an artificial photosynthetic system consisting of semiconductors, electrocatalysts, and polymer membranes to carry out photoelectrochemical water splitting as a method for solar fuel generation.

This dissertation describes efforts over the last five years to develop critical semiconductor and catalyst components for efficient and scalable photoelectrochemical hydrogen evolution, one of the half reactions for water splitting. We identified and developed Ni–Mo alloy and Ni₂P nanoparticles as promising earth-abundant electrocatalysts for hydrogen evolution. We thoroughly characterized Ni–Mo alloys alongside Ni and Pt catalysts deposited onto planar and structured Si light absorbers for solar hydrogen generation. We sought to address several key challenges that emerged in the use of non-noble catalysts for solar fuels generation, resulting in the synthesis and characterization of Ni–Mo nanopowder for use in a new photocathode device architecture. To address the mismatch in stability between non-noble metal alloys and Si absorbers, we also synthesized and characterized p-type WSe₂ as a candidate light absorber alternative to Si that is stable under acidic and alkaline conditions.

Sustainable IT and IT for sustainability

Energy and sustainability have become one of the most critical issues of our generation. While the abundant potential of renewable energy such as solar and wind provides a real opportunity for sustainability, their intermittency and uncertainty present a daunting operating challenge. This thesis aims to develop analytical models, deployable algorithms, and real systems to enable efficient integration of renewable energy into complex distributed systems with limited information.

The first thrust of the thesis is to make IT systems more sustainable by facilitating the integration of renewable energy into these systems. IT represents the fastest growing sectors in energy usage and greenhouse gas pollution. Over the last decade there are dramatic improvements in the energy efficiency of IT systems, but the efficiency improvements do not necessarily lead to reduction in energy consumption because more servers are demanded. Further, little effort has been put in making IT more sustainable, and most of the improvements are from improved "engineering" rather than improved "algorithms". In contrast, my work focuses on developing algorithms with rigorous theoretical analysis that improve the sustainability of IT. In particular, this thesis seeks to exploit the flexibilities of cloud workloads both (i) in time by scheduling delay-tolerant workloads and (ii) in space by routing requests to geographically diverse data centers. These opportunities allow data centers to adaptively respond to renewable availability, varying cooling efficiency, and fluctuating energy prices, while still meeting performance requirements. The design of the enabling algorithms is however very challenging because of limited information, non-smooth objective functions and the need for distributed control. Novel distributed algorithms are developed with theoretically provable guarantees to enable the "follow the renewables" routing. Moving from theory to practice, I helped HP design and implement industry's first Net-zero Energy Data Center.

The second thrust of this thesis is to use IT systems to improve the sustainability and efficiency of our energy infrastructure through data center demand response. The main challenges as we integrate more renewable sources to the existing power grid come from the fluctuation and unpredictability of renewable generation. Although energy storage and reserves can potentially solve the issues, they are very costly. One promising alternative is to make the cloud data centers demand responsive. The potential of such an approach is huge.

To realize this potential, we need adaptive and distributed control of cloud data centers and new electricity market designs for distributed electricity resources. My work is progressing in both directions. In particular, I have designed online algorithms with theoretically guaranteed performance for data center operators to deal with uncertainties under popular demand response programs. Based on local control rules of customers, I have further designed new pricing schemes for demand response to align the interests of customers, utility companies, and the society to improve social welfare.