A blog managed by the communications team at the UC San Diego Jacobs School of Engineering. Are you a member of the Jacobs School community? Have ideas for a blog post? Let us know! Email dbkane AT ucsd DOT edu or let us know via our Facebook page: http://www.facebook.com/UCSDJacobs
Thursday, March 31, 2022
Shaochen Chen receives NSF BRITE Award to develop 3D printed microscale human organs-on-a-chip
Friday, January 29, 2021
FAQs about UC San Diego’s wearable mask sensor for COVID-19
Friday, May 1, 2020
Discovery of High-Entropy Ceramics via Machine Learning
Materials are an essential part of our world; they have enabled us to build cities, treat disease, and communicate across the world in real time. For centuries, material scientists have been working to build our material library and to discover new materials with greater performance and better property trade-offs. Over the past few decades, however, the rate at which new materials are being discovered has been slowing continuously. This is due to several factors including increasingly stricter regulations, more challenging performance metrics, and increasingly more expensive empirical development strategies.
The reduced rate of material discovery is also in part because many of the simplest combinations have been investigated, and the number of remaining possible combinations is quite extensive. For example, if random combinations of five elements from the periodic table are combined in equal amounts, there would be 1078 possible combinations to choose from. This example ignores the fact that different numbers of elements can be combined, not just five, and that they do not have to be combined in equal ratios. For perspective, there are estimated to be 1066 atoms in the Milky Way galaxy. So, in terms of a “big data” challenge, materials development of complex composition alloys represents perhaps the biggest big data paradigm. There is a clear need for a method to narrow the search space to only the most promising candidates for a given application. Intuition and expensive trial and error strategies will not be sufficient for investigating this immense chemical space, and more informed computational methods must be developed and employed.
Our team of nanoengineers in Professor Kenneth Vecchio’s lab at UC San Diego is developing tools for screening large numbers of materials in a rapid fashion. The first step in our work is creating unique identifiers for each material, akin to a fingerprint of the material. In the same way no two fingerprints are alike, every individual material possible can be reduced to a simple but unique set of attributes. These identifiers describe the material composition in a way that supports computation work leveraging a subset of artificial intelligence called machine learning. The machine learning tools learn the underlying science that relates these attributes to various material properties. Typically, machine learning requires enormous initial datasets to learn from before it becomes a useful tool.
However, the method that our team developed is designed around the fact that material development problems frequently have less than 100 data points at the outset. After learning about the initial dataset, the machine learning algorithm suggests new materials with the goal of maximizing performance. Each time the materials suggested by the algorithm are fabricated and tested, this new information is made available to the algorithm, creating a learning loop.
The data-driven method that our team has developed was recently demonstrated for predicting the synthesizability of single crystal structure (e.g. rock-salt structured) carbide ceramic materials containing five metal cations, also known as high entropy carbides. High entropy carbides constitute a subset of the complex concentrated alloys class of materials described previously, as they have the added uniqueness of becoming more stable at increasing temperatures, which is unlike most engineering materials. The researchers focused their study on what are called non-intuitive compositions, in which three of the five metal cations are chromium, molybdenum, and tungsten, none of which form a rock-salt structure at room temperature in a one metal atom to one carbon atom ratio.
The initial dataset contained all available data: 56 high entropy carbide materials with synthesizability calculated by computationally expensive density functional theory (DFT). None of the 56 known compositions contained chromium, one of the three metal cations of interest. While DFT can compute a few compositions per month, the machine learning model was able to learn from the 56 materials and make predictions on 70 new materials in less than one day.
Seven materials, four predicted to succeed and three predicted to fail, were experimentally fabricated and analyzed to assess the validity of the predictions. Rather surprisingly, several five-cation metal carbide compositions were discovered, wherein three of the five cations were chromium, molybdenum, and tungsten—the elements that don’t form the rocksalt monocarbide structure—and yet these compositions were experimentally shown to successfully form the rock-salt structure. Furthermore, all seven experimentally studied compositions resulted in single or multi-crystal structure materials in exact agreement with the machine learning predictions. The ability for the machine learning model to perform exceedingly well in such a non-intuitive chemical space, a composition space which contained no prior data to learn from, further demonstrates the unique strength of this approach. Our team expects the machine learning framework to be a useful tool in the development of other materials such as alloys, battery components, or pharmaceuticals.
This work is published in Nature Partner Journals (npj) Computational Materials, May 1, 2020.
Read the paper here: https://rdcu.be/b3UdG
DOI: 10.1038/s41524-020-0317-6
Wednesday, February 13, 2019
Seeing at a different scale
When he was in high school and building robots, Marquez Balingit couldn't help but wonder: How do these parts work and how do circuits communicate with each other?
He realized is questions could be answered in one word: nanoengineering. So when it came time to pick a college major, that's what he chose. He wanted to understand what things at the nanoscale or submicron level look like.
Now an undergraduate the Jacobs School, Balingit tackles this question at the Nano3 lab. In the future, Balingit sees himself creating a nonprofit company specializing in a form of energy conversion, battery or generator that is efficient in every aspect: cost, power conversion and practicality. He hopes that it can be free and practical for developing countries, giving them more autonomy so that they can power themselves.
Balingit says he is inspired by the works of Nikola Tesla. From his perspective, Tesla's main desire was to create free energy by harnessing and manipulating existing energy on earth and within the air so that everyone can access it.
Balingit teaches users unfamiliar with the scanning electron microscope, or SEM, how to use it independently. Unlike regular optical microscopes, SEM does not use photons. Instead, it uses electrons, which allows the device to capture smaller features at the 1 micron scale, approximately ⅕ the size of a human red blood cell.
"I like the idea of being the bridge of information by gathering some knowledge, filtering out the details and explaining it to someone clearly," Balingit said. "I learn how to use high tech equipment and understand the standard operating procedures to be able to articulate that to other people so that they can use it on their own."
Outside of training users, Balingit also works on service measurements of sample materials, in order to to figure out the features that users want. He says he feels challenged to get a clear, high resolution images and excited to see something he's never seen before.
"Sometimes things I see in textbooks, I end up actually imaging which is pretty amazing because I never thought I'd be able to. In my textbooks, a lot of things are in the 10 microns and 5 microns and I wondered how they even get these images. Now, years later, I'm getting images that are roughly similar to that," Balingit said.
The Nano3 lab is also looking to increase outreach with the SEM by remotely connecting with high schools and community colleges to show them the SEM's full capabilities of the and what it can provide from an educational standpoint. Balingit feels like this will help bridge the gap between college and high school curricula in nanotechnology by bringing this information to them. By magnifying everyday objects like pennies and ballpoint pens, Balingit also hopes that using SEM will inspire young students to pursue an education/career in a STEM field.
Thursday, August 23, 2018
Clip from NanoXpo 2018: Rory Runser
Runser describes his project in this video, taken at NanoXpo 2018 this past May:
Poster title: "Interfacial drawing of ultra-thin polymer films for solar tarps"
Thursday, July 26, 2018
Clip from NanoXpo 2018: Yao Jiang
Jiang describes her project in this video, taken at NanoXpo 2018 this past May:
Poster title: "Cancer cell membrane-coated nanoparticles for anticancer vaccination"
NanoXpo is an annual event held by the Graduate Society of Nanoengineers to showcase graduate research in the UC San Diego Department of NanoEngineering.
Friday, July 13, 2018
Clip from NanoXpo 2018: Rishi Kumar
Kumar describes his project in this video, taken at NanoXpo 2018 this past May:
Poster title: "Understanding & Overcoming Water-Induced Interfacial Degradation in Si Modules"
NanoXpo is an annual event held by the Graduate Society of Nanoengineers to showcase graduate research in the UC San Diego Department of NanoEngineering.
Thursday, July 5, 2018
Clip from NanoXpo 2018: Hui Zheng
Zheng describes her project in this video, taken at NanoXpo 2018:
Poster title: "Role of Zr in Strengthening MoSi2 Grain Boundaries from DFT Calculations"
NanoXpo is an annual event held by the Graduate Society of Nanoengineers to showcase graduate research in the UC San Diego Department of NanoEngineering.
Monday, November 27, 2017
Joseph Wang named Honorary Doctor in Europe
On Monday, Nov. 20, Charles University in Prague awarded Wang an honorary doctorate in Natural Sciences for his "outstanding academic achievements in the field of Analytical Chemistry."
And on Friday, Nov. 24, the Senate of the Iuliu Haţieganu University of Medicine and Pharmacy in Cluj-Napoca, Romania, also conferred an honorary doctorate on Wang in recognition of his "prodigious merits in the field of Electrochemistry."
Here are photos from the ceremony at Charles University in Prague:
Thursday, November 16, 2017
Engineering Art Contest Winner: Let It Snow Crystalline Dendrites
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| Crystalline dendrite imaged by transmission-mode Scanning Electron Microscopy. Image credit: Kevin Kaufmann |
Thursday, July 27, 2017
Smart Glove Converts Sign Language Letters Into Text
Tuesday, July 18, 2017
One Imaging Agent to Rule Them All

Monday, June 5, 2017
South 8 Technologies wins Clean Tech prize at UC San Diego Entrepreneur Challenge
Tuesday, September 13, 2016
These fish weren't just made for swimming
The nanofish are made of gold and magnetic nickel segments, which enable the fish to move and be guided by an external magnet.
"We believe they could be useful for medicine delivery, non-invasive surgery and single cell manipulation," said Jinxing Li, a PhD student in the lab of nanoengineering professor Joseph Wang who led the research.
See a video of the nanofish featured in New Scientist:
Monday, September 12, 2016
UC San Diego nanoengineer makes Popular Science’s ‘Brilliant 10’ list
Friday, August 26, 2016
Jacobs School alumnus named to MIT Tech Review 35 list
Gao, 31, is currently a postdoctoral fellow at UC Berkeley. There he continues to work on technologies similar to those developed by the Center for Wearable Sensors, led by Wang here at the Jacobs School.
In January 2016, he was first author on a Nature paper titled "Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis." The study received broad media coverage, including in The New York Times, The Wall Street Journal, Scientific American, IEEE Spectrum, Wired and many other outlets.
Essentially, Gao and colleagues built a sweatband that combines sensors with electronic processors and a Bluetooth transmitter on a flexible printed circuit board. The device wirelessly transmits data about what's in your sweat to an app on your cell phone.
Gao told MIT Tech Review:
“I grew up in a small village in Xuzhou, China. When I was a child I saw a lot of people around me dying of different diseases. Many people don’t realize there’s a problem until it’s too late. I thought, in the future I should design a wearable electronic device to monitor health and tell us what’s going on and what’s going wrong before it gets bad.“Our body is generating data all the time. There are so many wearable devices now—the Apple watch, the Fitbit—but they mainly track physical activities or vital signs. They can’t provide information at the molecular level.“It came into my mind: what about sweat?”
Thursday, August 11, 2016
Caleb Christianson, a JPL intern and NanoEngineering Ph.D. student, takes over the Jacobs School's Instagram for a day
Nanoengineering Ph.D. student Caleb Christianson took over the Jacobs School Instagram account (@ucsandiegoengineering) yesterday, August 10, to give us a preview of what it's like to be a NASA Jet Propulsion Laboratory intern designing and robot that can hover above asteroids! In case you missed it, here's a recap:
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Here is more about the project Caleb worked on this summer, via JPL's newsletter:
Glide, don't land, to study an asteroidThere's intense interest in studying asteroids, but the challenge is getting near them. There isn't enough gravity or atmosphere to allow a spacecraft to touch down without ricocheting off the surface.But why land when you can glide? JPLer Marco Quadrelli's Electrostatic Glider (E-Glider) was inspired by the idea of dust fountains visible on our moon's surface: when warmed by the sun, these dust particles gain an electrostatic charge. The same principle turns every asteroid or comet's dust into a weak but usable power supply.Quadrelli's glider would be a low-cost craft attached to foil-like streamers. These streamers would inflate and lift based on the electrostatic energy around them. The glider could then be steered around an asteroid and perform basic science readings on its composition
Caleb Christianson, a JPL intern and NanoEngineering PhD student, takes over the Jacobs School's Instagram for a day
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UCSD JPL interns represent! #SelfieStyle #JPLInternTakeover
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