Liwei Lin (Advisor)

Research Advised by Professor Liwei Lin

Lin Group:  List of Projects | List of Researchers

Designing Weakly Coupled MEMS Resonators with Machine Learning-Based Method

Fanping Sui
Wei Yue
Ruiqi Guo
Kamyar Behrouzi
Liwei Lin

We demonstrate a design scheme for weakly coupled resonators (WCRs) by integrating the supervised learning (SL) with the genetic algorithm (GA). In this work, three distinctive achievements have been accomplished: 1) the precise prediction of coupling characteristics of WCRs with an accuracy of 98.7% via SL; 2) the stepwise evolutionary optimization of WCR geometries while maintaining their geometric connectivity via GA; and 3) the highly efficient generation of WCR designs with a mean coupling factor down to 0.0056, which outperforms 98% of random designs. The coupling behavior analysis...

BSAC's Best: Fall 2021 Oral Presentation Winners Announced

September 30, 2021

BSAC would like to thank all of the researchers who presented their research during BSAC's Fall 2021 Research Review, September 22 & 23.

BSAC Industrial Members voted for their favorite oral presentations and the results are in. Please join us in congratulating the winners of the Fall 2021 Best of BSAC honors, Johannes Henriksson and Yande Peng!

Watch the Fall 2021 Oral Presentations


Subcutaneous and Continuous Blood Pressure Monitoring by PMUTS in an Ambulatory Sheep

Yande Peng
Sedat Pala
Zhichun Shao
Hong Ding
Jin Xie
Liwei Lin

This paper reports a subcutaneous blood pressure (BP) monitoring system with AlN-based,piezoelectric micromachined ultrasonic transducers (PMUTs) on an ambulatory sheep. Comparedto the state-of-art, three distinctive achievements have been demonstrated: (1) precision andcontinuous measurements of the blood pressure from the diameter changes of blood vessels assmall as 2.3 μm by means of ultrasonic detections; (2) experimental validations in both in vitroartery models and an acute animal study; and (3) the ...

Data-Driven Freeform MEMS Energy Harvester Design Enabled by Machine Learning

Kunying Li
Ruiqi Guo
Fanping Sui
Liwei Lin

This paper reports a computational method for the design of freeform piezoelectric energyharvesters (PEHs) fabricated by micromachining processes based on the machine learning (ML)scheme. The geometry of candidate designs is first converted to pixelated images and assignedwith specific properties and analyzed by the finite element method (FEM). The resulting neuralnetwork machine learning algorithm is trained using the above dataset to identify the propertiesof similar freef...

Moisture-Induced Autonomous Surface Potential Oscillations for Energy Harvesting

Yu Long
Peisheng He
Zhichun Shao
Han Kim
Mingze Yao
Yande Peng
Renxiao Xu
Christine Heera Ahn
Zhaoyang Li
Seung-Wuk Lee
Junwen Zhong
Liwei Lin

A variety of autonomous oscillations in nature such as heartbeats and some biochemical reactions have been widely studied and utilized for applications in the fields of bioscience and engineering. Here, we report a unique phenomenon of moisture-induced electrical potential oscillations on polymers, poly([2-(methacryloyloxy)ethyl] dimethyl-(3-sulfopropyl) ammonium hydroxide-co-acrylic acid), during the diffusion of water molecules. Chemical reactions are modelled by kinetic simulations while system dynamic equations and the stability matrix are analyzed to show the chaotic nature of...

Lin Lab: With a Damp TV, Berkeley Engineers Demonstrate the Potential of a Green Energy Harvester

September 6, 2021

Watching television in the shower might not rank terribly high on the scale of today’s available personal-tech indulgences. But imagine if the TV — or other small electronic device — was powered by water vapor billowing up from the marble floor tiles.

Such moisture-induced energy harvesting is what UC Berkeley researchers, led by mechanical engineering professor Liwei Lin, report in a study published today in Nature Communications They say it is a potential new source of green energy, particularly in...

Lin Lab: Slicing the Way to Wearable Sensor Prototypes

February 11, 2022

Engineers at UC Berkeley have developed a new technique for making wearable sensors that enables medical researchers to prototype test new designs much faster and at a far lower cost than existing methods.

The new technique replaces photolithography — a multistep process used to make computer chips in clean rooms — with a $200 vinyl cutter. The novel approach slashes the time to make small batches of sensors by nearly 90% while cutting costs by almost 75%, said Renxiao Xu (Ph.D.’20 ME), who developed the...

BSAC's Best: Fall 2009 Winners Announced

September 18, 2009

BSAC would like to thank the 150 researchers who presented their work in poster or plenary sessions at the Fall 2009 BSAC Research Review on September 16-18.

60 attending industrial members from 39 member organizations voted for the best presentations and posters, resulting in Best Paper and Best Poster awards (certificate and cash).

 Zhiyong Fan
Best Paper...

BSAC's Best: Spring 2011 Winners Announced

March 11, 2011

BSAC would like to thank the 150 researchers who presented their work in poster or plenary sessions at the Spring 2011 BSAC Research Review on March 9-11.

60 attending industrial members from 32 member organizations voted for the best presentations and posters, resulting in Best Paper and Best Poster awards (certificate and cash).

 Adrienne Higa
Best Paper...