You Should Know These 20 Technology Leaders Driving China's A.I. Revolution

China’s leading technology companies are on fire, heavily investing in artificial intelligence and building true global presences. McKinsey recently reported that academic and research institutions in the country publish more cited research papers than the US, UK, or any other global leader in AI, producing nearly 10,000 papers in 2015 alone.

Backed by strong government mandates and billions of dollars of both private and public investments, China is challenging the US for position of global AI leader. Fearful of competition, the US government is considering placing restrictions on Chinese investments in AI and technology in the United States. In many sectors, such as healthcare, China may already be ahead of America in applying AI to critical public issues.

You might recognize names like Andrew Ng, Sebastian Thrun, Geoffrey Hinton, or Yann LeCun as important figures in AI, but few Westerners can name the key leaders driving AI innovation in China and at Chinese companies globally. These executives, entrepreneurs, professors, and researchers helm the most important Chinese tech companies and research labs and are respected widely for their technical expertise and accomplishments.

We’ve researched and curated 20 of the most important figures in the Chinese AI landscape that you should know: 

1. KAI-FU LEE

Co-Founder of Sinovation Ventures, Former President of Google China

Kai-Fu Lee is a globally recognized technology leader with executive experience at Apple, Microsoft, and Google. He got his BS in Computer Science from Columbia University and his PhD from Carnegie Mellon. Lee established Google China prior to co-founding Sinovation Ventures, a venture capital firm actively funding technology and AI startups in the US and China.

With celebrity status in China and over 50 million followers on Chinese social networks, Lee has become an oracle in predicting trends in Chinese tech. Lee told CNBC recently that artificial intelligence is the “singular thing that will be larger than all of human tech revolutions added together, including electricity, the industrial revolution, internet, and mobile internet.”

2. QI LU

Group President & COO, Baidu

Qi Lu was hired by Baidu to lead the company’s strategic efforts in AI and push forward integration and collaboration within the company. Every Baidu business unit, including AI teams working on autonomous driving, reports to Lu. A spokesperson from Baidu stated: “With Dr. Lu on board, we are confident that our strategy will be executed smoothly and Baidu will become a world-class technology company and global leader in AI.”

Prior to joining Baidu, Lu was personally recruited by Steve Ballmer to join Microsoft where he eventually became EVP of the Applications & Services Group. Lu started his professional career in IBM’s research labs, before joining Yahoo and rising to EVP of the Search & Advertising Group. He completed a BS in Computer Science at Fudan University and was invited by Carnegie Mellon professor Edmund M. Clarke to pursue his PhD at CMU.

3. HAIFENG WANG

Head of AI Group, Baidu

After Andrew Ng’s departure from Baidu, Haifeng Wang took over as leader of the expanded AI Group (AIG), consisting of

• Baidu’s Institute of Deep Learning, 
• Big Data Lab, 
• Silicon Valley AI Lab, 
• Augmented Reality Lab, 
• Natural Language Unit, 
• AI Platform Unit, and 
• a few other departments.

Wang’s technical specialty is natural language processing (NLP) and machine translation and he has authored over 100 academic papers in AI. He applies his expertise to Baidu’s efforts in

• NLP, 
• computer vision, 
• speech recognition, 
• knowledge graphs, 
• personalized recommendations, and 
• deep learning. 

Wang is also an adjunct professor at Harbin Institute of Technology where he received his BS, MS, and PhD degrees in Computer Science.

4. TONG ZHANG

Executive Director of AI Lab, Tencent

The battle for top AI talent is incredibly fierce. Tong Zhang was poached from Baidu by Tencent last year to lead Tencent’s newly established AI lab. Formerly he was head of Baidu’s Big Data Lab, worked at IBM and Yahoo, and was a professor at Rutgers University.

With a team of over 200 engineers, Zhang is focused on developing Tencent’s capabilities in machine learning, computer vision, speech recognition, and natural language processing and applying new AI technologies to the company’s vast array of popular consumer products like WeChat.

5. JINGREN ZHOU

Chief Scientist and Vice President of Alibaba Cloud, Alibaba

Alibaba Cloud launched in 2009 and is now Alibaba’s fastest growing business unit. Similar to Amazon Web Services (AWS), Alibaba Cloud, also called Aliyun, emerged out of the company’s need for enormous computing power to handle millions of online shopping transactions.

Jingren Zhou leads big data and AI research at Alibaba Cloud’s Institute of Data Science Technology (iDST). In this role, he drives Alibaba’s AI technologies in speech, natural language, image and video processing, and large-scale machine learning.

Prior to joining Alibaba, Zhou was an engineering manager at Microsoft in charge of developing the big data computation platform supporting Windows, Office, and Bing. He received his BS from the University of Science and Technology of China and his PhD in Computer Science from Columbia University.

6. XIAOFE HE

President, DiDi Research

DiDi Chuxing is the “Uber of China”, with over 50TB of real-time data and over 9 billion routes driven per day. DiDi Research, the “brains of Didi Chuxing”, is a machine learning research institute set up by the company to predict demand, reduce surge impact, and also develop self-driving car technology.

President Xiaofe He got his BS in Computer Science from Zhejiang University and PhD from University of Chicago. Prior to helming DiDi Research, he worked as a research scientist and President of Yahoo Research Labs and joined Zhejiang University as a professor focused on applying mathematics and data analysis to solve important problems in pattern recognition, multimedia, and computer vision.

7. YUANQING LIN

Head of Baidu Research, Baidu

As Head of Baidu Research, Yuanqin Lin manages Baidu’s research labs, which include the

• Silicon Valley AI Lab (SVAIL), 
• Big Data Lab (BDL), 
• Augmented Reality Lab (ARL), and the 
• Institute of Deep Learning Lab (IDL). 

Along with Wei Xu, he will be leading Baidu’s contributions to China’s government-funded National Engineering Laboratory of Deep Learning Technology that is co-helmed by Tsinghua & Beihang University.

Prior to Baidu, Lin was the head of Media Analytics at NEC Labs America where he led teams focusing on computer vision research for mobile search and driverless cars. Lin received his MS degree in Optical Engineering from Tsinghua University and his PhD in Electrical Engineering from University of Pennsylvania.

8. PINPIN ZHU

President & CTO, Xiaoi

Xiaoi is China’s leading platform for conversational AI, powering the majority of the country’s bot and virtual assistant experiences. Established in Shanghai in 2001, the company’s technologies are used by hundreds of medium to large enterprises, government entities, and over 500 million users collectively.

Pinpin Zhu’s numerous patents in the space – including ones for “Chatting Robot System” and “SMS Robot System” – drove Xiaoi’s technical dominance in conversational interfaces. In addition to running Xiaoi, Zhu is also a Doctor of Science at the Chinese Academy of Sciences, has been appointed to China National Information Technology Standardization Committee, and has received numerous awards and accolades for his contributions to the field.

9. WEI XU

Distinguished Scientist, Baidu

In a company full of highly credentialed scientists, researchers, and engineers, Wei Xu is the only one with the title “Distinguished Scientist”. He is highly respected for his technical chops within the company due to his work on PaddlePaddle, a deep learning toolkit which was open sourced in late 2016. In development for over three years, PaddlePaddle is used to power search rankings, targeted advertising, image classification, translation, and self-driving cars.

Xu received his Bachelor’s degree at Tsinghua University, his MS from Carnegie Mellon, and was previously a researcher at NEC Labs and Facebook before joining Baidu.

10. WANLI MIN

Principal Data Scientist, Alibaba

Wanli Min led the research and development of Alibaba Cloud’s (Aliyun) artificial intelligence system, named Little Ai. Ai has been deployed by Alibaba internally to support customer service and traffic pattern predictions for the company’s flagship e-commerce business. Min also used machine learning to predict the winner of a top-rated Chinese reality TV show called “I Am Singer” and helped city planners in Guangdong province optimize traffic lights in real-time to reduce congestion.

Min entered college at the age of 14 and received his Bachelors from the University of Science & Technology of China and a PhD in Statistics from the University of Chicago.

11. KUN JING

General Manager of Duer, Baidu

Duer is Baidu’s answer to Apple’s Siri, Amazon’s Alexa, Microsoft’s Cortana, and Google’s Assistant. The conversational AI platform powers virtual assistant capabilities in a number of devices, ranging from XiaoYu, China’s version of the Amazon Echo, to voice-activated smart televisions.

Kun Jing leads the Duer business unit. Prior to joining Baidu, Jing was Microsoft’s R&D Director and created Xiaoice, a popular chatbot that went viral on Tencent’s WeChat and Sina’s Weibo. Xiaoice has over 20 million registered users who interact with the bot an average of 60 times a month, earning it the rank of Weibo’s top influencer.

12. DONG YU

Deputy Director of AI Lab, Tencent

Hired as deputy head of Tencent’s AI Lab, Dong Yu co-runs the new lab with Tong Zhang and spearheads research in speech recognition and natural language understanding. Prior to joining Tencent, Yu was the principal researcher at Microsoft Research Institute’s Speech and Dialog Group, an adjunct professor at Zhejiang University, a visiting professor at University of Science and Technology of China, and a visiting researcher at Shanghai Jiao Tong University. He received a Bachelor’s in Electrical Engineering from Zhejiang University and a PhD in Computer Science from Idaho University.

“I’m excited to join AI Lab,” Yu shares. “Over the past decade, Tencent has accumulated abundant experience in application scenarios, developed a massive data bank, established powerful computing capabilities, and built an outstanding team of technology experts; all which have helped form the foundation of in-depth research and AI application at Tencent today.”

13. ADAM COATES

Director of Silicon Valley AI Lab, Baidu

Coates received his BS, MS, and PhD degrees in Computer Science from Stanford University and has worked on everything from computer vision for autonomous cars, deep learning for speech recognition, and machine learning for helicopter acrobatics. At Baidu, he worked on DeepSpeech, a speech recognition and transcription engine that performs as well as native Mandarin speakers, and DeepVoice, a text-to-speech synthesis engine that generates believable human-like audio.

Coates is particularly excited about putting AI in the hands of real-world consumers. When he was selected by MIT Technology Review as one of 35 Innovators Under 35 in 2015, he explained that “in rapidly developing economies like in China, there are many people who will be connecting to the Internet for the first time through a mobile phone. Having a way to interact with a device or get the answer to a question as easily as talking to a person is even more powerful to them. I think of Baidu’s customers as having a greater need for artificial intelligence than myself.”

14. KAI YU

Founder & CEO, Horizon Robotics

Formerly head of Baidu’s Institute of Deep Learning, Kai Yu left Baidu to start Beijing-based startup Horizon Robotics. Funded by leading investors like Yuri Milner and Sequoia Capital, Yu’s mission is to become the “Android of Robotics,” a pervasive AI system that powers all of our smart devices. Unlike other Chinese tech giants which dominate in the cloud, Horizon aims to adapt AI to every piece of hardware in the physical world.

Horizon has launched two platforms to date: 

• Anderson for smart homes and 
• Hugo for smart driving. 

Anderson imbues home appliances with capabilities such as facial recognition and automatic ordering, while Hugo is an advanced driver assistance system that performs real-time pedestrian and object detection even in adverse weather conditions.

Yu received his BS and MS degrees in Electrical Engineering from Nanjing University and his PhD in Computer Science from Ludwig-Maximilians Universitat Munchen in Germany.

15. JING WANG

Former Senior Vice President of Engineering, Baidu

While at Baidu, Jing Wang managed over 5,000 engineers in numerous business units, including the ones he founded:

• Mobile, 
• Cloud Computing, 
• Big Data, 
• Cybersecurity, 
• Baidu Research, and 
• Autonomous Driving. 

He left the company shortly after Andrew Ng’s resignation to start his own self-driving car company, and is widely credited with driving forward Baidu’s progress in the space.

Prior to joining Baidu, Wang was Deputy Head of Google’s Shanghai engineering office as well as eBay China’s CTO and R&D general manager. He received his Bachelor’s from the University of Science & Technology of China and his Master’s in Computer Science from the Chinese Academy of Sciences.

16. BO ZHANG

Professor of Computer Science and Technology, Tsinghua University

As a professor at Tsinghua University, Bo Zhang’s research interests include AI, machine learning, pattern recognition, knowledge engineering, and robotics. His notable academic achievements include advances in robotic task and motion planning, probabilistic logic neural networks (PLN), and machine learning algorithms for image retrieval and classification and webpage structure mining.

Along with Baidu and Wei Li of Beihang University, Tsinghua was selected to co-lead the government-funded National Engineering Laboratory of Deep Learning. He is a member of the Chinese Academy of Sciences and received his Bachelor’s in Automatic Control from Tsinghua University.

17. HUA WU

Technical Chief of NLP Group, Baidu

Hua Wu contributed a number of technical breakthroughs in 

• natural language processing (NLP), 
• dialogue systems, and 
• neural machine translation (NMT) 21

in her seven year tenure at Baidu. The New York Times hailed her research work in multi-task learning as “pathbreaking” and she was able to successfully deploy her invention at scale to hundreds of millions of users of Baidu’s translation products. Wu is also responsible for the technology behind Baidu’s conversational AI, Duer.

Wu received her PhD from the Chinese Academy of Sciences and co-chairs leading academic AI conferences such as ACL and IJCAI.

18. WEI LI

President and Professor of Computer Science, Beihang University

Along with Bo Zhang of Tsinghua University and senior executives from Baidu, Wei Li was selected to co-lead China’s National Engineering Laboratory of Deep Learning. He is a member of the Chinese Academy of Sciences and also president of Beihang University. Li has won numerous accolades and prizes for his technical contributions in artificial intelligence and network computing.

Li graduated from the Department of Mathematics and Mechanics of Beijing University and received his PhD in Computer Science from the University of Edinburgh.

19. HONGBIN ZHA

Professor of Machine Learning, Peking University 

“China hopes to leap-frog the US and other Western countries by vast and fast investment in the AI industry,” says Hongbin Zha, AI researcher and professor at Beijing’s Peking University. Zha directs the Key Lab of Machine Perception at Peking University and collaborates with Microsoft Research Asia alongside other AI leaders across the continent. His research interests include computer vision theory, virtual reality, and robotics.

He received his Bachelor’s degree in Electrical Engineering from Hefei University of Technology in China and his MS and PhD degrees in Electrical Engineering from Kyushu University in Japan.

20. YUNJI CHEN

Professor at Institute of Computing Technology, Chinese Academy of Sciences

In 2015, Yunji Chen was selected by MIT Technology Review as one of their top 35 Innovators Under 35. Described as “iconoclastic and cosmopolitan”, he was chosen for his work in designing specialized deep-learning processors which dramatically reduce the computational costs of large-scale machine learning. His dream is to enable even common cell phones to be “as powerful as Google Brain”.

Chen entered college at age 14 and completed his PhD with lightning speed by the age of 24. He’s now chief architect of the Godson-3C, a microprocessing chip that reduces energy requirements for computers to recognize objects and translate languages and is developing the Cambricon, a brain-inspired processor chip that models human nerve cells and synapses to facilitate deep learning. The research team is led by Chen and his younger brother, Tianshi Chen, two of the youngest professors at the Chinese Academy of Sciences.

ABOUT THE AUTHOR

Adelyn Zhou

Adelyn is the Head of Marketing at TOPBOTS. She's got a decade of experience growing billion-dollar companies like Eventbrite, NextDoor, and Amazon. Follow her on Twitter at @adelynzhou to learn how to accelerate your growth with AI.

ORIGINAL: TopBots

by Adelyn Zhou

Jun 18, 2017

Bringing Silicon to Life

Scientists persuade nature to make silicon-carbon bonds

A new study is the first to show that living organisms can be persuaded to make silicon-carbon bonds—something only chemists had done before. Scientists at Caltech "bred" a bacterial protein to have the ability to make the man-made bonds, a finding that has applications in several industries.

Molecules with silicon-carbon, or organosilicon, compounds are found in pharmaceuticals as well as in many other products, including agricultural chemicals, paints, semiconductors, and computer and TV screens. Currently, these products are made synthetically, since the silicon-carbon bonds are not found in nature.

The new research, which recently won Caltech's Dow Sustainability Innovation Student Challenge Award (SISCA) grand prize, demonstrates that biology can instead be used to manufacture these bonds in ways that are more environmentally friendly and potentially much less expensive.

"We decided to get nature to do what only chemists could do—only better," says Frances Arnold, Caltech's Dick and Barbara Dickinson Professor of Chemical Engineering, Bioengineering and Biochemistry, and principal investigator of the new research, published in the Nov. 24 issue of the journal Science.

The study is also the first to show that nature can adapt to incorporate silicon into carbon-based molecules, the building blocks of life. Scientists have long wondered if life on Earth could have evolved to be based on silicon instead of carbon. Science-fiction authors likewise have imagined alien worlds with silicon-based life, like the lumpy Horta creatures portrayed in an episode of the 1960s TV series Star Trek. Carbon and silicon are chemically very similar. They both can form bonds to four atoms simultaneously, making them well suited to form the long chains of molecules found in life, such as proteins and DNA.

"No living organism is known to put silicon-carbon bonds together, even though silicon is so abundant, all around us, in rocks and all over the beach," says Jennifer Kan, a postdoctoral scholar in Arnold's lab and lead author of the new study. Silicon is the second most abundant element in Earth's crust.

The researchers used a method called directed evolution, pioneered by Arnold in the early 1990s, in which new and better enzymes are created in labs by artificial selection, similar to the way that breeders modify corn, cows, or cats. Enzymes are a class of proteins that catalyze, or facilitate, chemical reactions. The directed evolution process begins with an enzyme that scientists want to enhance. The DNA coding for the enzyme is mutated in more-or-less random ways, and the resulting enzymes are tested for a desired trait. The top-performing enzyme is then mutated again, and the process is repeated until an enzyme that performs much better than the original is created.

Directed evolution has been used for years to make enzymes for household products, like detergents; and for "green" sustainable routes to making pharmaceuticals, agricultural chemicals, and fuels.

In the new study, the goal was not just to improve an enzyme's biological function but to actually persuade it to do something that it had not done before. The researchers' first step was to find a suitable candidate, an enzyme showing potential for making the silicon-carbon bonds.

Bringing Silicon to Life: Scientists Persuade Nature to Make Silicon-Carbon Bonds

Researchers in Frances Arnold’s lab at Caltech have persuaded living organisms to make chemical bonds not found in nature. The finding may change how medicines and other chemicals are made in the future.

Credit: Caltech

"It's like breeding a racehorse," says Arnold, who is also the director of the Donna and Benjamin M. Rosen Bioengineering Center at Caltech. "A good breeder recognizes the inherent ability of a horse to become a racer and has to bring that out in successive generations. We just do it with proteins."

The ideal candidate turned out to be a protein from a bacterium that grows in hot springs in Iceland. That protein, called cytochrome c, normally shuttles electrons to other proteins, but the researchers found that it also happens to act like an enzyme to create silicon-carbon bonds at low levels. The scientists then mutated the DNA coding for that protein within a region that specifies an iron-containing portion of the protein thought to be responsible for its silicon-carbon bond-forming activity. Next, they tested these mutant enzymes for their ability to make organosilicon compounds better than the original.

After only three rounds, they had created an enzyme that can selectively make silicon-carbon bonds 15 times more efficiently than the best catalyst invented by chemists. Furthermore, the enzyme is highly selective, which means that it makes fewer unwanted byproducts that have to be chemically separated out.

"This iron-based, genetically encoded catalyst is nontoxic, cheaper, and easier to modify compared to other catalysts used in chemical synthesis," says Kan. "The new reaction can also be done at room temperature and in water."

The synthetic process for making silicon-carbon bonds often uses precious metals and toxic solvents, and requires extra processing to remove unwanted byproducts, all of which add to the cost of making these compounds.

As to the question of whether life can evolve to use silicon on its own, Arnold says that is up to nature. "This study shows how quickly nature can adapt to new challenges," she says. "The DNA-encoded catalytic machinery of the cell can rapidly learn to promote new chemical reactions when we provide new reagents and the appropriate incentive in the form of artificial selection. Nature could have done this herself if she cared to."

The Science paper, titled "Directed Evolution of Cytochrome c for Carbon-Silicon Bond Formation: Bringing Silicon to Life," is also authored by Russell Lewis and Kai Chen of Caltech. The research is funded by the National Science Foundation, the Caltech Innovation Initiative program, and the Jacobs Institute for Molecular Engineering for Medicine at Caltech.

ORIGINAL: CALTECH

Written by Whitney Clavin

11/24/2016

Contact: Whitney Clavin

(626) 395-1856

wclavin@caltech.edu

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Site content Copyright © 2016 California Institute of Technology

Bloom Box: The Alternative Energy

What is an Energy Server?

Built with our patented solid oxide fuel cell technology, Bloom's Energy Server® is a new class of distributed power generator, producing clean, reliable, affordable electricity at the customer site.

Fuel cells are devices that convert fuel into electricity through a clean electro-chemical process rather than dirty combustion. They are like batteries except that they always run.

Our particular type of fuel cell technology is different than legacy "hydrogen" fuel cells in three main ways:

1. Low cost materials – our cells use a common sand-like powder instead of precious metals like platinum or corrosive materials like acids.
2. High electrical efficiency – we can convert fuel into electricity at nearly twice the rate of some legacy technologies
3. Fuel flexibility – our systems are capable of using either renewable or fossil fuels

Each Bloom Energy Server provides 200kW of power, enough to meet the baseload needs of 160 average homes or an office building... day and night, in roughly the footprint of a standard parking space. For more power simply add more energy servers.

Energy Server Architecture

At the heart of every Energy Server® is Bloom's patented solid oxide fuel cell technology.

Each Energy Server consists of thousands of Bloom's fuel cells. Each cell is a flat solid ceramic square made from a common sand-like "powder."

Each Bloom Energy fuel cell is capable of producing about 25W... enough to power a light bulb. For more power, the cells are sandwiched, along with metal interconnect plates into a fuel cell "stack". A few stacks, together about the size of a loaf of bread, is enough to power an average home.

In an Energy Server, multiple stacks are aggregated together into a "power module", and then multiple power modules, along with a common fuel input and electrical output are assembled as a complete system.

For more power, multiple Energy Server systems can be deployed side by side.

In addition to Bloom's unmatched performance, this modular architecture offers...

• easy and fast deployment
• inherent redundancy for fault tolerance
• high availability (one power module can be serviced while all others continue to operate)
• mobility

Solid Oxide Fuel Cells

Fuel cells were invented over a century ago and have been used in practically every NASA mission since the 1960's, but until now, they have not gained widespread adoption because of their inherently high costs.

Legacy fuel cell technologies like

• proton exchange membranes (PEMs), 
• phosphoric acid fuel cells (PAFCs), and 
• molten carbonate fuel cells (MCFCs), 

have all required expensive precious metals, corrosive acids, or hard to contain molten materials. Combined with performance that has been only marginally better than alternatives, they have not been able to deliver a strong enough economic value proposition to overcome the status quo.

Some makers of legacy fuel cell technologies have tried to overcome these limitations by offering combined heat and power (CHP) schemes to take advantage of their wasted heat. While CHP does improve the economic value proposition, it only really does so in environments with exactly the right ratios of heat and power requirements on a 24/7/365 basis. Everywhere else the cost, complexity, and customization of CHP tends to outweigh the benefits.

For decades, experts have agreed that solid oxide fuel cells (SOFCs) hold the greatest potential of any fuel cell technology. With low cost ceramic materials, and extremely high electrical efficiencies, SOFCs can deliver attractive economics without relying on CHP. But until now, there were significant technical challenges inhibiting the commercialization of this promising new technology. SOFCs operate at extremely high temperature (typically above 800°C). This high temperature gives them extremely high electrical efficiencies, and fuel flexibility, both of which contribute to better economics, but it also creates engineering challenges.

Bloom has solved these engineering challenges. With breakthroughs in materials science, and revolutionary new design, Bloom's SOFC technology is a cost effective, all-electric solution.

Over a century in the making, fuel cells are finally clean, reliable, and most importantly, affordable.

How a Solid Oxide Fuel Cell Works

ORIGINAL: Bloom Energy

New ‘Pomegranate-inspired’ Design Solves Problems for Lithium-Ion Batteries

Menlo Park, Calif. — An electrode designed like a pomegranate – with silicon nanoparticles clustered like seeds in a tough carbon rind – overcomes several remaining obstacles to using silicon for a new generation of lithium-ion batteries, say its inventors at Stanford University and the Department of Energy’s SLAC National Accelerator Laboratory.

"While a couple of challenges remain, this design brings us closer to using silicon anodes in smaller, lighter and more powerful batteries for products like cell phones, tablets and electric cars,” said Yi Cui, an associate professor at Stanford and SLAC who led the research, reported today in Nature Nanotechnology.

A novel battery electrode features silicon nanoparticles clustered like pomegranate seeds in a tough carbon rind. (Illustration by Greg Stewart/SLAC)

Top: Silicon nanoparticles are encased in carbon “yolk shells” and clustered like seeds in a pomegranate. Each cluster has a carbon rind that holds it together, conducts electricity and minimizes reactions with the battery’s electrolyte that can degrade performance. Bottom: Silicon nanoparticles swell during battery charging to completely fill their yolk shells; no space is wasted, and the shells stay intact. (Nian Liu, Zhenda Lu and Yi Cui/Stanford)

By precisely controlling the process used to make them, Stanford and SLAC researchers can produce pomegranate clusters of a specific size for silicon battery anodes. Left: Microscopic clusters form a fine black powder that can be coated on foil to create an anode. Middle: A single cluster. Right: In this close-up of a cluster, a silicon nanoparticle can be seen inside its yolk shell, with space to swell during battery charging. (Nian Liu, Zhenda Lu and Yi Cui/Stanford)

“Experiments showed our pomegranate-inspired anode operates at 97 percent capacity even after 1,000 cycles of charging and discharging, which puts it well within the desired range for commercial operation.”

The anode, or negative electrode, is where energy is stored when a battery charges. Silicon anodes could store 10 times more charge than the graphite anodes in today’s rechargeable lithium-ion batteries, but they also have major drawbacks: The brittle silicon swells and falls apart during battery charging, and it reacts with the battery’s electrolyte to form gunk that coats the anode and degrades its performance.

Over the past eight years, Cui’s team has tackled the breakage problem by using silicon nanowires or nanoparticles that are too small to break into even smaller bits and encasing the nanoparticles in carbon “yolk shells” that give them room to swell and shrink during charging.

The new study builds on that work. Graduate student Nian Liu and postdoctoral researcher Zhenda Lu used a microemulsion technique common in the oil, paint and cosmetic industries to gather silicon yolk shells into clusters, and coated each cluster with a second, thicker layer of carbon. These carbon rinds hold the pomegranate clusters together and provide a sturdy highway for electrical currents.

And since each pomegranate cluster has just one-tenth the surface area of the individual particles inside it, a much smaller area is exposed to the electrolyte, thereby reducing the amount of gunk that forms to a manageable level.

Although the clusters are too small to see individually, together they form a fine black powder that can be used to coat a piece of foil and form an anode. Lab tests showed that pomegranate anodes worked well when made in the thickness required for commercial battery performance.

While these experiments show the technique works, Cui said, the team will have to solve two more problems to make it viable on a commercial scale: They need to simplify the process and find a cheaper source of silicon nanoparticles. One possible source is rice husks: They’re unfit for human food, produced by the millions of tons and 20 percent silicon dioxide by weight. According to Liu, they could be transformed into pure silicon nanoparticles relatively easily, as his team recently described in Scientific Reports.

“To me it’s very exciting to see how much progress we’ve made in the last seven or eight years,” Cui said, “and how we have solved the problems one by one.”

The research team also included Jie Zhao, Matthew T. McDowell, Hyun-Wook Lee and Wenting Zhao of Stanford. Cui is a member of the Stanford Institute for Materials and Energy Sciences, a joint SLAC/Stanford institute. The research was funded by the DOE Office of Energy Efficiency and Renewable Energy.

SLAC is a multi-program laboratory exploring frontier questions in photon science, astrophysics, particle physics and accelerator research. Located in Menlo Park, California, SLAC is operated by Stanford University for the U.S. Department of Energy Office of Science. To learn more, please visit www.slac.stanford.edu.

The Stanford Institute for Materials and Energy Sciences (SIMES) is a joint institute of SLAC National Accelerator Laboratory and Stanford University. SIMES studies the nature, properties and synthesis of complex and novel materials in the effort to create clean, renewable energy technologies. For more information, please visit simes.slac.stanford.edu.

The DOE Office of Energy Efficiency and Renewable Energy accelerates development and facilitates deployment of energy efficiency and renewable energy technologies and market-based solutions that strengthen U.S. energy security, environmental quality, and economic vitality. For more information, please visithttp://energy.gov/eere/about-us.

Citation: N. Liu, Z. Lu et al., Nature Nanotechnology, 16 February 2014 (10.1038/nnano.2014.6)

Press Office Contact: 

Andy Freeberg, SLAC National Accelerator Laboratory: afreeberg@slac.stanford.edu, (650) 926-4359

Scientist Contact:

Yi Cui, SLAC/Stanford University: yicui@stanford.edu, (650) 723-4613

Also on the Web:

The Yi Cui Lab home page

The Stanford Institute for Materials & Energy Sciences (SIMES) home page

ORIGINAL: SLAC
February 16, 2014