She employed brand new methods to set the world record for efficiency of the perovskite solar cell. For the first time, this low cost and high performance PV technology showed its potential of industrialization and large scale manufacturing by further taking part in the competition of commercial power generation.
Among the various clean energy technologies, solar power is one of the most widely used and cheapest energy sources available today. Around 90% percent of prevailing solar cells are based on crystalline silicon materials. Starting from the 1970s, crystalline silicon PV took 50 years to bring its energy conversion efficiency from 10% to 25%, which is highly competitive in the market. However, constrained by many factors, the efficiency of crystalline silicon PV has almost reached its theoretical upper limit.
Recently, a new type of solar technology, the perovskite solar cell, is getting more and more popular. It took only 5 years for the efficiency of perovskite solar cell to leap forward from 3.8% to near 20% in 2014 - much faster than crystalline silicon PV. This remarkable achievement is accomplished by Dr Huanping Zhou, Assistant Professor of material science and engineering at Peking University. By inventing a new method, she made it possible for the perovskite solar cell to step out of the lab and be ready for the market.
After obtaining her PhD degree from Peking University, Zhou went to UCLA for post-doc research. Under the guidance of Professor Yang Yang, she invented a new method called “vapor assisted solution process," which involves inorganic component deposition from solution within situ conversion to perovskite by a vapor-phase reaction. Through delicate control over the flow of carriers throughout the entire device and optimization of the perovskite layer, she demonstrated a conversion efficiency of 19.3%, the highest at the time. Moreover, the method is also suitable for mass production in an ambient environment. This encouraged the whole solar cell research community to “set a new standard for future research, in terms of both mechanistic understanding and scientific engineering optimization.”