Professor Alán Aspuru-Guzik seeks to make a difference in facing the most important challenge of the 21st century, namely the transition to a renewable energy economy. One of the key aspects that holds us back is the current slow and painful cycle of materials discovery. Alán is a pioneer in the emerging area of materials genomics: He uses a powerful combination of millions of quantum chemical calculations, state-of-the-art machine learning algorithms and big data techniques to sift through millions and millions of candidate molecules in search of the next generation of materials. He works with experimental groups around the world to collaborate in a virtuous cycle of computational design and experimental synthesis and characterization that promises to accelerate materials discovery by a factor of ten. Alán focuses on the discovery of inexpensive organic solar cells that could help provide power to the 1.4 billion people that lack access to the electrical grid. He works in the development of all-organic flow batteries for large-scale energy storage that promise to free the world from fossil fuels. He also works in the development of organic light-emitting diodes that could help provide efficient and inexpensive lighting sources with innovative form factors.

In another line of research, Professor Alán Aspuru-Guzik wants to go beyond the use of traditional or classical computers. These computers, which range from your cell phone to the largest supercomputers in the world, cannot simulate molecules and materials exactly. A new promising class of computers, quantum computers, enable the exact simulation of molecules and materials. Alán is a pioneer in the development of algorithms for these computers to simulate materials and in collaborating with experimental groups around the world to implement them.

Working at the interface of theoretical chemistry and other fields, in particular computer science, applied mathematics, and physics, allows Alán and his research group to embrace a true culture of innovation. He and his team strive for a flat structure that rewards innovation and seeks to find connections amongst fields. His multidisciplinary team, composed of chemists, physicists, software engineers, and systems biology students, collaborates with computer scientists that work on machine learning and with experimental teams on quantum computing. Thus, his team of over 35 researchers melds the excitement of discovery with the opportunity to make a difference in society. Success thus far has been clearly supported by their accelerated high-performance computing and machine-learning based approach to materials discovery where they can deliver a promising material in as little as a year per application which includes the development of solar cells made of plastic, energy storage, and new displays and lighting technologies.

Current research includes:

• The Harvard Clean Energy Project: In collaboration with IBM, Alán’s team uses people globally to engage the community in empowering cutting-edge research in finding new materials. This is the largest quantum chemistry experiment ever done in terms of computer time. (http://www.worldcommunitygrid.org)

• Materials Genomics: The use of the ever-growing computational time, machine learning and big data techniques, in combination with a close interaction with experimental teams leads to accelerated discovery. Recently, in collaboration with the Aziz and Gordon Groups at Harvard, he and his team predicted a new class of energy storage materials for flow batteries. Flow batteries are used to store energy in large quantities. Flow batteries will be very relevant as renewables are introduced into the electricity grid. The organic molecules they proposed do not use metals and hence have many technical advantages, most importantly, their cost. Recently, Alán and his team have engaged in the accelerated discovery of the next generation of molecules for organic light-emitting diodes that could be employed in efficient lighting with novel form factors.

• Quantum computers for simulating chemistry: Alán and his research group are pioneers in the development of algorithms for the use of quantum computers for the simulation of chemicals and materials. Unlike classical computers, quantum computers promise a numerically-exact simulation approach. This can help unleash the power of quantum simulation abilities and allow them to design materials much faster. He and his team have carried out, in collaboration with many experimental groups around the world, early demonstrations of these algorithms using prototype quantum computers. With the rapid advancement of quantum computer technology, this approach could disrupt the current paradigm of materials design. It would provide routine predictive rather than explanatory computational abilities.

• Understanding of the quantum mechanics photosynthesis: Since 2007, Dr. Aspuru-Guzik and his team have been studying how the initial light-harvesting process of photosynthesis works in bacteria, algae, and plants. These quantum mechanical studies shed light on the fundamental mechanisms behind how these organisms work and hence provide inspiration for creating novel devices.

• Metabolism and the origins of life: Dr. Aspuru-Guzik has recently begun work in understanding both the molecular origins of life and metabolism from a computational chemistry and high-throughput computational approach.