中大新測量法 準確評估納米發電機輸出

納米發電機( Nanogenerator )可向小型電子設備持續穩定地供電,中文大學機械與自動化工程學系助理教授訾雲龍及研究團隊,最近研發了一種評估納米發電機輸出能力的通用標準化方法。與傳統方法相比,這種方法能夠更準確反映發電機實際輸出能力,為納米發電機技術的標準化應用和普及定下基礎。

Date: 
Tuesday, October 15, 2019
Media: 
Ming Pao

A Universal Standardized Method for Output Capability Assessment of Nanogenerators Laying the Foundation for Nanogenerator Technology Development

Date: 
2019-10-14
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Nanogenerator is a type of new technology that converts thermal and mechanical energy as produced by small-scale physical change into electricity. Its presence secures a stable and sustainable source of electricity that powers a wide range of small electronic devices equipped with a variety of features. A research team led by Prof. ZI Yunlong, Assistant Professor in the Department of Mechanical and Automation Engineering has recently developed a universal standardized method for evaluating the output capacity of nanogenerators. Compared with the conventional one, the new method can reflect the practical output capacity of the nanogenerator more accurately. This research will set an important foundation for the practical application and commercialisation of nanogenerators as an emerging energy harvesting technology. This research was published recently in the prestigious scientific journal Nature Communications (www.nature.com/articles/s41467-019-12465-2).

A nanogenerator has three typical approaches: piezoelectric, triboelectric, and pyroelectric nanogenerators. Triboelectric nanogenerators (TENG), which harvest energy from triboelectric effect, can provide high energy output and high energy conversion efficiency. They have caught a lot of attention because they can acquire electricity by rubbing commonly-used materials such as clothes fabric and papers. However, the unique capacitive output characteristics of the nanogenerator make the traditional characterisation method not applicable. To solve this problem, the Figure-of-Merit (FOM) defined by a maximized energy output cycle has become a standard for quantitative evaluation of output performance. However, the development of TENG is still hindered since the current FOM definition does not consider the breakdown effect, and the corresponding standardized performance assessment and well- standardized experimental evaluation methods have not been developed yet, limiting the wide application of this FOM as the evaluation standard.

Prof. Zi and his team members have discovered that a specific measuring circuit can solve the most difficult part, which is measuring the breakdown limit. Based on the designed process flow, the breakdown areas of contact separation (CS) mode and contact freestanding (CFT) mode TENG were determined and the results were consistent with the theoretical calculations. The team redefined FOM based on the experimentally measured maximized effective energy output to reflect the actual output capacity of the TENG. The team also applied this method to a piezoelectric nanogenerator based on polyvinylidene fluoride (PVDF) thin film, further proving the wide applicability of the method. This study provides a standardized method for evaluating output capacity, which is advantageous due to the standardized process flow for experimental operation and considerations of the breakdown effect. It can be widely applied to various types of nanogenerators and will make an important contribution to the standardized application and commercialisation of the nanogenerator technology.

This project was funded by the Innovation and Technology Fund of the Innovation and Technology Commission of the Hong Kong SAR, Shun Hing Institute of Advanced Engineering and CUHK.

 

Prof. Zi (5th left) and his research team.

Air breakdown of arc which can be seen in CS mode.

 

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Prof. Darwin Lau Awarded 2019 UGC Teaching Award

Date: 
2019-10-11
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Professor Darwin Tat-ming Lau, Assistant Professor of the Department of Mechanical and Automation Engineeringhas been awarded the 2019 UGC Teaching Award (Early Career Faculty Members), in recognition of his dedication and achievements in his learner-centred and experience-based learning ideology.

Professor Rocky S. Tuan, Vice-Chancellor and President of CUHK, said, “My sincere congratulations to Professor Darwin Lau. Professor Lau is an outstanding young scholar. By introducing hands-on experience to the robotics programme, he not only tremendously improves the students’ learning interest but also enriches their learning experience. Through collaboration with medical professionals, Professor Lau helps transfer the academic research results into social services which benefits patients in need. The University is proud of his achievements.”

Professor Lau is deeply honoured to receive the award. He said, “Teaching is a job as challenging as it is meaningful. My goal is to ensure that students can learn effectively through the Student-Teacher-Experience-Peer modality and I try to make my lectures enjoyable and memorable. I would like to extend my heartfelt thanks to my teaching assistants for their support in executing the mixed mode teaching and to the students for their feedback and encouragement.”  
 

Learning Experience-Based and Improve Students’ Learning Motivation 
Joining CUHK in October 2015, Professor Lau was awarded the CUHK Vice-Chancellor’s Exemplary Teaching Award 2018 and the University Education Award 2019. He is an expert in robotics and has been responsible for teaching and supervising both undergraduate and postgraduate students in this area. He is dedicated to bringing about meaningful hands-on experiences both within and outside the classroom to improve students’ learning interest and outcomes. In the classroom, he has introduced a new form of lectures, known as “hands-on lectures”, where students learn robotics fundamentals in groups with a physical robot arm in front of them. With a tailor made tablet application, these learning tools aid students in better understanding abstract concepts while making learning more fun and relevant to the practical world, which increases student motivation. Professor Lau has also been working with colleagues in his Department to implement this novel teaching approach in other courses, sharing his teaching innovation through seminars and publications. He anticipates that the pedagogy can be beneficial to students from other disciplines as well.

Beyond the classroom, Professor Lau has been active in supervising a range of student activities, such as robotics team competitions, internship programmes and final year projects. Further, in collaboration with Prince of Wales Hospital, he has established a student prosthetics development team where his students have the opportunity to apply their engineering skills to help amputee patients by developing prosthetic devices that can change their lives. These experiences significantly enrich students’ quality of learning and motivation. Professor Lau is committed to helping students into the society, and his teaching philosophy and dedication set examples for good teachers.
 
Launching of the Hong Kong Teaching Excellence Alliance
The Hong Kong Teaching Excellence Alliance (HKTEA), a formal community for UGC Teaching Award fellows and others, is established today. HKTEA aims to collectively make an impact on promoting teaching excellence in and beyond the UGC sector. Professor Isabella Wai-yin Poon, Pro-Vice-Chancellor / Vice-President of CUHK, is the Chair of HKTEA for the first term.
 

The Annual Award for Teaching Excellence
The annual UGC Teaching Award was introduced in 2011 to honour those who excel in teaching in the UGC sector and their leadership in and scholarly contribution to teaching and learning within and across institutions. Past awardees from CUHK include Professor Isabella Wai-yin Poon, Pro-Vice-Chancellor / Vice-President and Professor in the Department of Statistics, Professor Shekhar Madhukar Kumta, Assistant Dean (Education), Faculty of Medicine, and Professor in the Department of Orthopaedics and Traumatology, Professor Leung Mei-yee, Director of University General Education, Dr. Julie Chiu Chu-lee, Deputy Director of the General Education Foundation Programme, Dr. Wong Wing-hung, Associate Director of the General Education Foundation Programme, Professor Emily Chan Ying-yang, Assistant Dean (External Affairs), Faculty of Medicine, and Professor in the Jockey Club School of Public Health and Primary Care, and Professor Suzanne So Ho-wai, Associate Professor of the Department of Psychology.

This article was originally published on CUHK Communications and Public Relations Office website.

 

Prof. Darwin Lau, Assistant Professor of the Department of Mechanical and Automation Engineering, CUHK receives the 2019 UGC Teaching Award (Early career Faculty Members)

CUHK members join Prof. Benjamin W. Wah, Provost (2nd from right) , Prof. Fanny Cheung, Pro-Vice-Chancellor / Vice-President (2nd from left), Prof. Isabella Wai-yin Poon, Pro-Vice-Chancellor / Vice-President (3rd from right), congratulating Prof. Darwin Lau (3rd from left).

 

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建跨文化交流平台 浸大教授獲傑出教學獎

大學教育資助委員會昨頒發本年度傑出教學獎,遴選委員會從19組大學提名名單中選出3組得獎者,其中獲獎的香港浸會大學政治及國際關係學系副系主任TusharChaudhuri開展線上遠程計劃,利用網上平台連繫德國、俄羅斯、沙地阿拉伯等16間大學的學生,讓他們運用外語討論跨文化議題。他把項目延展至21所歐洲和本地中學,讓中學生透過交流提高全球意識。今後他計劃利用獎金,與大灣區的學者交流,探討共同開發其他平台的可能。

Date: 
Friday, October 11, 2019
Media: 
Ming Pao Daily

3組學者傑出教學 獲教資會嘉獎

大學是本港學術、科研發展及人才培訓的搖籃,大學教育資助委員會每年會頒發傑出教學獎項鼓勵業者提升水平,今年有三組隊伍獲獎,當中有在港教授德文的印度學者,亦有教授「機械人入門」課程的年輕學者獲獎。每組得獎者或團隊可獲得五十萬元的獎金,當中四十五萬元是供得獎者進行提升教與學質素的計劃或活動,另外五萬元鼓勵其傑出教學表現及成就。

 

Date: 
Friday, October 11, 2019
Media: 
Oriental Daily

中大教授以機械臂授課 增學習趣味 3團隊獲傑出教學獎

大學教育資助委員會昨舉行傑出教學獎,表揚3組優秀教學表現的大學學者,當中分別有得獎教授以機械手臂融入大學課程,或透過建立電子交流平台,增加學生學習興趣及提升語文能力。

Date: 
Friday, October 11, 2019
Media: 
Sky post

中大引「機械臂」 學生邊玩邊學

「體驗課堂」提升學習效能 助理教授奪傑出教學獎
 
香港文匯報訊(記者 詹漢基)STEM(科學、科技、工程、數學)教育風氣盛行,但要透徹理解背後的抽象數學概念進而學以致用,其實並不容易。中文大學機械與自動化工程學系助理教授劉達銘另闢蹊徑,摒棄傳統授課方式,引入「體驗課堂」,讓學生邊玩「機械臂」邊學習,大大提升學習效能,因而昨晚獲頒2019年度教資會的新晉教學人員組別傑出教學獎。
Date: 
Friday, October 11, 2019
Media: 
Wen Wei Po

中大機械工程助教引機械手臂 解數學概念奪獎

今年教資會傑出教學獎得獎者名單今日(10日)出爐,當中新晉教學人員組別獎由,香港中文大學機械與自動化工程學系助理教授劉達銘奪得。他將「機械手臂」引入課堂,讓學生能即時用數學知識控制機械人,有助學生理解艱深、抽象的數學概念。

Date: 
Friday, October 11, 2019
Media: 
HK01

中大學者創新教學模式 獲教資會傑出教學獎

大學教育資助委員會每年均會頒發教資會「傑出教學獎」,以表揚資助大學學者的優秀教學表現及成就。中文大學機械與自動化工程學系助理教授劉達銘,擺脫傳統講授模式,以分組形式教授課程,令成績中等至下游的學生成績都有明顯改善,新的教學模式讓他成為「傑出教學獎」得主之一,可獲五十萬元獎金,用作提升教與學質素。

Date: 
Friday, October 11, 2019
Media: 
Sing Tao

World’s First AI-enabled Portable Quantitative Phase Microscope for Blood Testing at the Hong Kong Electronics Fair

Date: 
2019-10-11
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The world’s first “AI-enabled Portable Quantitative Phase Microscope for Blood Testing” is one of the five innovative projects to be showcased in the coming Hong Kong Electronics Fair (Autumn Edition) 2019 at the Hong Kong Convention and Exhibition Centre from 13 to 16 October. This project is able to provide low-cost, fast and high efficiency blood testing technology in general clinics and underdeveloped areas.

In general, a regular body check must include blood testing, which reveals the health condition, especially the immune-functioning leukocyte / white blood cell. Unlike the red blood cell, there are many types of leukocyte, including monocytes, granulocytes and lymphocytes. Through the classification or counting of the number of leukocytes to see if they have increased or decreased, different diseases can also be reflected, such as inflammation, infectious diseases and leukemia.
 
Traditional blood testing methods include manual observation of stained smears and fluorescence detection via flow cytometry, but the staining and fluorescent labeling process is time consuming and labour intensive. Quantitative Phase Microscopy (QPM) is a label-free imaging technology that has high imaging sensitivity and speed, but the instruments based on it are bulky and expensive and cannot be moved easily to different laboratories, especially in remote areas. Moreover, all of the above methods need to be handled by professionals, and the test results can take hours or even days. Therefore, in addition to the high costs of instruments and reagents, the labour and time costs should also be taken into consideration. Even though, currently, there are newer automated instruments, they still have the problems of bulk and expense, and may kill the cells and affect the morphology of the cells through staining or labeling. Such cells cannot be reused in other tests which may be able to reflect the health condition. Thus, a blood testing method that can be performed quickly, efficiently and can preserve cell morphology is needed.
 
In order to provide low-cost and high efficiency blood testing technology in general clinics and underdeveloped areas, the CUHK team led by Professor Zhou Renjie, Department of Biomedical Engineering, developed the “AI-enabled Portable Quantitative Phase Microscope for Blood Testing” to identify different types of human leukocytes based on quantitative phase imaging and deep learning.
 
The QPM technology has become an important modality for quantifying live cell morphology and precision material (e.g. semiconductor) metrology. Professor Zhou's research team has successfully developed a new portable and versatile QPM system. By combining both reflection mode and transmission mode into one system, and using a special interferometry technique to greatly eliminate noise influence, the system is not only compact and portable, but also high precision and low cost.
 
Professor Zhou said, “In the past, researchers have tried to combine artificial intelligence with traditional blood testing methods but in vain, because it is difficult to distinguish cell images. Through our high-precision QPM technology, we can effectively combine it with the deep learning technology of artificial intelligence. By learning the morphological features from thousands of cells in two-dimensional quantitative phase images, our learning model can automatically distinguish monocytes, granulocytes, T-cells and B-cells in lymphocytes from healthy volunteers’ blood samples.”
 
The low-cost “AI-enabled Portable Quantitative Phase Microscope for Blood Testing” developed by CUHK weighs less than five kilograms and is a size similar to a briefcase that can be carried to use everywhere. In addition, its label-free feature not only saves the use of reagents, but can also avoid the staining and fluorescent labeling process by the professional, and the classification and counting of cells by clinical experts. The analysis process is completed by the computer automatically, so it can quickly obtain the result, in a matter of minutes, with over 90% accuracy.
 
The CUHK team has just completed the proof-of-concept study. The researchers are planning to get clinical certification by working with hospitals starting in 2020. They expect the low-cost “AI-enabled Portable Quantitative Phase Microscope for Blood Testing” will be commercialised after three to five years. In future, the researchers will develop other artificial intelligence models of this portable quantitative phase microscopy technique that can be used to distinguish red blood cells and all other blood cell types. They are also working on using such invention for differentiating bacteria and stem cells. Eventually, the team hopes to detect cancer cells in peripheral blood.
 
Comparisons of blood testing instruments
 
Key FeaturesCurrent blood testing method [1,2]CUHK blood testing method
Marker TypeChemical type: Scattered light, impedance and conductivityPhysical type: Optical path length difference
Invasiveness of cellYesNo
Throughput100 samples/hour>10,000 cells/second
Accuracy>90%>90%
Cost>US$80,000>US$30,000
Consumable ExpenseYesNo
Weight>100kg 
Size>60X80X70cm 

Reference:
[1] https://www.beckmancoulter.com/en/products/hematology/dxh-600?index=0#/d...
[2] Meintker, Lisa, et al. "Comparison of automated differential blood cell counts from Abbott Sapphire, Siemens Advia 120, Beckman Coulter DxH 800, and Sysmex XE-2100 in normal and pathologic samples." American journal of clinical pathology 139.5 (2013): 641-650.

To know more about the aforementioned technology and other recent technological projects, please visit the booth of CUHK at the Hong Kong Electronics Fair (Autumn Edition).

Hong Kong Electronics Fair (Autumn Edition)

Date: 13-16 October 2019
Time: 9:30 am – 6:30 pm (Closes at 5:00 pm on 16 October)
Venue: Hong Kong Convention and Exhibition Centre Hall 1A Concourse (CUHK Booth No.: 1CON-050).

This article was originally published on CUHK Communications and Public Relations Office website.

Professor Zhou Renjie, Department of Biomedical Engineering, CUHK

The prototype of the AI-enabled Portable Quantitative Phase Microscope

 

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