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.”