Penn Bioengineering Alumnus Joshua Doloff Seeks a Pain-free Treatment for Diabetes

Person taking a finger stick blood test.
Credit: Darryl Leja, NHGRI Flickr

Joshua C. Doloff, Assistant Professor of Biomedical Engineering and Materials Science & Engineering at Johns Hopkins University, featured in The Jewish News Syndicate for his work on “Hope,” a new technology which offers pain- and injection-free treatment to people with Type 1 or “juvenile” diabetes. Doloff is an alumnus of Penn Bioengineering, Class of 2004:

“Doloff received his bachelor’s degree from the University of Pennsylvania and his graduate degrees from Boston University. In addition to his post in Johns Hopkins’ Department of Biomedical Engineering, he is a member of the Translational Tissue Engineering Center at Johns Hopkins University School of Medicine. His lab is interested in systems biology with an emphasis on engineering improved therapies in the fields of cancer, autoimmunity, transplantation medicine, including Type 1 diabetes and ophthalmology.”

Read “Technion researchers offer ‘Hope’ for treating diabetes, minus the painful jabs” in the Jewish News Syndicate.

Student Summer Research Spotlight: Dahin Song

Dahin Song
Dahin Song (BE 2024)

Dahin Song, a third year undergraduate student in Bioengineering, penned a guest blog post for Penn Career Services as part of their ongoing series of posts by recipients of the 2022 Career Services Summer Funding Grant. In this post, Song talks about her opportunity to conduct research in the SMART Lab of Daeyeon Lee, Professor and Evan C. Thompson Term Chair for Excellence in Teaching in the Department of Chemical and Biomolecular Engineering and member of the Penn Bioengineering Graduate Group. During her summer research, Song worked on increasing the stability of the monolayer in microbubbles, gas particles which have been put to therapeutic use. She writes:

“My project was on increasing the stability of the monolayer using cholesterol; theoretically, this would decrease the permeability while maintaining the fluidity of the monolayer. Being given my own project at the get-go was initially intimidating; initial learning curve was overwhelming – along with new wet lab techniques and protocols, I learned a whole new topic well enough to ask meaningful questions. But in retrospect, throwing myself headlong into a project was the best method to immerse me in the research environment, especially as a first-time researcher. I learned how to read papers efficiently, troubleshoot research problems, navigate in a laboratory environment, and be comfortable with working independently but more importantly, with others.”

Read “The Itsy Bitsy Bubble” in the Career Services blog.

ASSET Center Inaugural Seed Grants Will Fund Trustworthy AI Research in Healthcare

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Illustration credit: Melissa Pappas

Penn Engineering’s newly established ASSET Center aims to make AI-enabled systems more “safe, explainable and trustworthy” by studying the fundamentals of the artificial neural networks that organize and interpret data to solve problems.

ASSET’s first funding collaboration is with Penn’s Perelman School of Medicine (PSOM) and the Penn Institute for Biomedical Informatics (IBI). Together, they have launched a series of seed grants that will fund research at the intersection of AI and healthcare.

Teams featuring faculty members from Penn Engineering, Penn Medicine and the Wharton School applied for these grants, to be funded annually at $100,000. A committee consisting of faculty from both Penn Engineering and PSOM evaluated 18 applications and  judged the proposals based on clinical relevance, AI foundations and potential for impact.

Artificial intelligence and machine learning promise to revolutionize nearly every field, sifting through massive amounts of data to find insights that humans would miss, making faster and more accurate decisions and predictions as a result.

Applying those insights to healthcare could yield life-saving benefits. For example, AI-enabled systems could analyze medical imaging for hard-to-spot tumors, collate multiple streams of disparate patient information for faster diagnoses or more accurately predict the course of disease.

Given the stakes, however, understanding exactly how these technologies arrive at their conclusions is critical. Doctors, nurses and other healthcare providers won’t use such technologies if they don’t trust that their internal logic is sound.

“We are developing techniques that will allow AI-based decision systems to provide both quantifiable guarantees and explanations of their predictions,” says Rajeev Alur, Zisman Family Professor in Computer and Information Science and Director of the ASSET Center. “Transparency and accuracy are key.”

“Development of explainable and trustworthy AI is critical for adoption in the practice of medicine,” adds Marylyn Ritchie, Professor of Genetics and Director of the Penn Institute for Biomedical Informatics. “We are thrilled about this partnership between ASSET and IBI to fund these innovative and exciting projects.”

 Seven projects were selected in the inaugural class, including projects from Dani S. Bassett, J. Peter Skirkanich Professor in the Departments of Bioengineering, Electrical and Systems Engineering, Physics & Astronomy, Neurology, and Psychiatry, and several members of the Penn Bioengineering Graduate Group: Despina Kontos, Matthew J. Wilson Professor of Research Radiology II, Department of Radiology, Penn Medicine and Lyle Ungar, Professor, Department of Computer and Information Science, Penn Engineering; Spyridon Bakas, Assistant Professor, Departments of Pathology and Laboratory Medicine and Radiology, Penn Medicine; and Walter R. Witschey, Associate Professor, Department of Radiology, Penn Medicine.

Optimizing clinical monitoring for delivery room resuscitation using novel interpretable AI

Elizabeth Foglia, Associate Professor, Department of Pediatrics, Penn Medicine and the Children’s Hospital of Philadelphia

Dani S. Bassett, J. Peter Skirkanich Professor, Departments of Bioengineering and Electrical and Systems Engineering, Penn Engineering

 This project will apply a novel interpretable machine learning approach, known as the Distributed Information Bottleneck, to solve pressing problems in identifying and displaying critical information during time-sensitive clinical encounters. This project will develop a framework for the optimal integration of information from multiple physiologic measures that are continuously monitored during delivery room resuscitation. The team’s immediate goal is to detect and display key target respiratory parameters during delivery room resuscitation to prevent acute and chronic lung injury for preterm infants. Because this approach is generalizable to any setting in which complex relations between information-rich variables are predictive of health outcomes, the project will lay the groundwork for future applications to other clinical scenarios.

Read the full list of projects and abstracts in Penn Engineering Today.

Defining Neural “Representation”

by Marilyn Perkins

Neuroscientists frequently say that neural activity ‘represents’ certain phenomena, PIK Professor Konrad Kording and postdoc Ben Baker led a study that took a philosophical approach to tease out what the term means.

Monitors Show EEG Reading and Graphical Brain Model. In the Background Laboratory Man Wearing Brainwave Scanning Headset Sits in a Chair with Closed Eyes. In the Modern Brain Study Research Laboratory
Neuroscientists use the word “represent” to encompass multifaceted relationships between brain activity, behavior, and the environment.

One of neuroscience’s greatest challenges is to bridge the gaps between the external environment, the brain’s internal electrical activity, and the abstract workings of behavior and cognition. Many neuroscientists rely on the word “representation” to connect these phenomena: A burst of neural activity in the visual cortex may represent the face of a friend or neurons in the brain’s memory centers may represent a childhood memory.

But with the many complex relationships between mind, brain, and environment, it’s not always clear what neuroscientists mean when they say neural activity “represents” something. Lack of clarity around this concept can lead to miscommunication, flawed conclusions, and unnecessary disagreements.

To tackle this issue, an interdisciplinary paper takes a philosophical approach to delineating the many aspects of the word “representation” in neuroscience. The work, published in Trends in Cognitive Sciences, comes from the lab of Konrad Kording, a Penn Integrates Knowledge University Professor and senior author on the study whose research lies at the intersection of neuroscience and machine learning.

“The term ‘representation’ is probably one of the most common words in all of neuroscience,” says Kording, who has appointments in the Perelman School of Medicine and School of Engineering and Applied Science. “But it might mean something very different from one professor to another.”

Read the full story in Penn Today.

Konrad Kording is a Penn Integrates Knowledge University Professor with joint appointments in the Department of Neuroscience the Perelman School of Medicine and in the Department of Bioengineering in the School of Engineering and Applied Science.

Ben Baker is a postdoctoral researcher in the Kording lab and a Provost Postdoctoral Fellow. Baker received his Ph.D. in philosophy from Penn.

Also coauthor on the paper is Benjamin Lansdell, a data scientist in the Department of Developmental Neurobiology at St. Jude Children’s Hospital and former postdoctoral researcher in the Kording lab.

Funding for this study came from the National Institutes of Health (awards 1-R01-EB028162-01 and R01EY021579) and the University of Pennsylvania Office of the Vice Provost for Research.

Training the Next Generation of Scientists on Soft Materials, Machine Learning and Science Policy

by Melissa Pappas

Developing new soft materials requires new data-driven research techniques, such as autonomous experimentation. Data regarding nanometer-scale material structure, taken by X-ray measurements at a synchrotron, can be fed into an algorithm that identifies the most relevant features, represented here as red dots. The algorithm then determines the optimum conditions for the next set of measurements and directs their execution without human intervention. Brookhaven National Laboratory’s Kevin Yager, who helped develop this technique, will co-teach a course on it as part of a new Penn project on Data Driven Soft Materials Research.

The National Science Foundation’s Research Traineeship Program aims to support graduate students, educate the STEM leaders of tomorrow and strengthen the national research infrastructure. The program’s latest series of grants are going toward university programs focused on artificial intelligence and quantum information science and engineering – two areas of high priority in academia, industry and government.

Chinedum Osuji, Eduardo D. Glandt Presidential Professor and Chair of the Department of Chemical and Biomolecular Engineering (CBE), has received one of these grants to apply data science and machine learning to the field of soft materials. The grant will provide five years of support and a total of $3 million for a new Penn project on Data Driven Soft Materials Research.

Osuji will work with co-PIs Russell Composto, Professor and Howell Family Faculty Fellow in Materials Science and Engineering, Bioengineering, and in CBE, Zahra Fakhraai, Associate Professor of Chemistry in Penn’s School of Arts & Sciences (SAS) with a secondary appointment in CBE, Paris Perdikaris, Assistant Professor in Mechanical Engineering and Applied Mechanics, and Andrea Liu, Hepburn Professor of Physics and Astronomy in SAS, all of whom will help run the program and provide the connections between the multiple fields of study where its students will train.

These and other affiliated faculty members will work closely with co-PI Kristin Field, who will serve as Program Coordinator and Director of Education.

Read the full story in Penn Engineering Today.

The Penn Center for Precision Engineering for Health Announces First Round of Seed Funding

by Melissa Pappas

CPE4H is one of the focal points of Penn Engineering signature initiative on Engineering Health.

The Penn Center for Precision Engineering for Health (CPE4H) was established late last year to accelerate engineering solutions to significant problems in healthcare. The center is one of the signature initiatives for Penn’s School of Engineering and Applied Science and is supported by a $100 million commitment to hire faculty and support new research on innovative approaches to those problems.

Acting on that commitment, CPE4H solicited proposals during the spring of 2022 for seed grants of $80K per year for two years for research projects that address healthcare challenges in several key areas of strategic importance to Penn: synthetic biology and tissue engineering, diagnosis and drug delivery, and the development of innovative devices. While the primary investigators (PIs) for the proposed projects were required to have a primary faculty appointment within Penn Engineering, teams involving co-PIs and collaborators from other schools were eligible for support. The seed program is expected to continue for the next four years.

“It was a delight to read so many novel and creative proposals,” says Daniel A. Hammer, Alfred G. and Meta A. Ennis Professor in Bioengineering and the Inaugural Director of CPE4H. “It was very hard to make the final selection from a pool of such promising projects.”

Judged on technical innovation, potential to attract future resources, and ability to address a significant medical problem, the following research projects were selected to receive funding.

Evolving and Engineering Thermal Control of Mammalian Cells

Led by Lukasz Bugaj, Assistant Professor in Bioengineering, this project will engineer molecular switches that can be toggled on and off inside mammalian cells at near-physiological temperatures. Successful development of these switches will provide new ways to communicate with cells, an advance that could be used to make safer and more effective cellular therapies.  The project will use directed evolution to generate and find candidate molecular tools with the desired properties. Separately, the research will also develop new technology for manipulating cellular temperature in a rapid and programmable way. Such devices will enhance the speed and sophistication of studies of biological temperature regulation.

A Quantum Sensing Platform for Rapid and Accurate Point-of-Care Detection of Respiratory Viral Infections

Combining microfluidics and quantum photonics, PI Liang Feng, Professor in Materials Science and Engineering and Electrical and Systems Engineering, Ritesh Agarwal, Professor in Materials Science Engineering, and Shu Yang, Joseph Bordogna Professor in Materials Science and Engineering and Chemical and Biomolecular Engineering, are teaming up with Ping Wang, Professor of Pathology and Laboratory Medicine in Penn’s Perelman School of Medicine, to design, build and test an ultrasensitive point-of-care detector for respiratory pathogens. In light of the COVID-19 pandemic, a generalizable platform for rapid and accurate detection of viral pathogenesis would be extremely important and timely.

Versatile Coacervating Peptides as Carriers and Synthetic Organelles for Cell Engineering

PI Amish Patel, Associate Professor in Chemical and Biomolecular Engineering, and Matthew C. Good, Associate Professor of Cell and Developmental Biology in the Perelman School of Medicine and in Bioengineering, will design and create small proteins that self-assemble into droplet-like structures known as coacervates, which can then pass through the membranes of biological cells. Upon cellular entry, these protein coacervates can disassemble to deliver cargo that modulates cell behavior or be maintained as synthetic membraneless organelles. The team will design new chemistries that will facilitate passage across cell membranes, and molecular switches to sequester and release protein therapeutics. If successful, this approach could be used to deliver a wide range of macromolecule drugs to cells.

Towards an Artificial Muscle Replacement for Facial Reanimation

Cynthia Sung, Gabel Family Term Assistant Professor in Mechanical Engineering and Applied Mechanics and Computer Information Science, will lead a research team including Flavia Vitale, Assistant Professor of Neurology and Bioengineering, and Niv Milbar, Assistant Instructor in Surgery in the Perelman School of Medicine. The team will develop and validate an electrically driven actuator to restore basic muscle responses in patients with partial facial paralysis, which can occur after a stroke or injury. The research will combine elements of robotics and biology, and aims to produce a device that can be clinically tested.

“These novel ideas are a great way to kick off the activities of the center,” says Hammer. “We look forward to soliciting other exciting seed proposals over the next several years.”

This article originally appeared in Penn Engineering Today.

Konrad Kording’s CENTER is Part of a New NIH Education Initiative on Scientific Rigor

by Melissa Pappas

Konrad Kording (Photo by Eric Sucar)

In 2005, John Ioannidis published a bombshell paper titled “Why Most Published Research Findings Are False.” In it, Ioannidis argued that a lack of scientific rigor in biomedical research — such as poor study design, small sample sizes and improper assessment of the significance of data— meant that a large percentage of experiments would not return the same results if they were conducted again.

Since then, researchers’ awareness of this “replication crisis” has grown, especially in fields that directly impact the health and wellbeing of people, where lapses in rigor can have life-or-death consequences. Despite this attention and motivation, however, little progress has been made in addressing the roots of the problem. Formal training in rigorous research practices remains rare; while mentors advise their students on how to properly construct and conduct experiments to produce the most reliable evidence, few educational resources exist to support them.

To address this discrepancy, the National Institute of Neurological Disorders and Stroke (NINDS), part of the National Institutes of Health (NIH), has launched the Initiative to Improve Education in the Principles of Rigorous Research.

Konrad Kording, a Penn Integrates Knowledge Professor with appointments in the Departments of Bioengineering and Computer and Information Science in Penn Engineering and the Department of Neuroscience in Penn’s Perelman School of Medicine, has been awarded one of the initiative’s first five grants.

“The replication crisis is real,” says Kording. “I’ve tried to replicate the research of others and failed. I’ve reanalyzed my own data and found major mistakes that needed to be corrected. I was never properly taught how to do rigorous science, and I want to improve that for the next generation.”

Read the full story in Penn Engineering Today.

Jenny Jiang on T Cell Diversity and Cancer Immunotherapy

by Melissa Pappas

Jenny Jiang, Ph.D.

Our body’s natural line of defense against infection and disease, as well as cancer, is our immune system equipped with T cells, a type of white blood cell that determines how we react to foreign substances, or antigens, in the body. While we have an arsenal of T cells to protect us from these various infections, some people lack certain T cells or simply do not have enough to fight off infections, such as the flu or HIV, or defend against the body’s own mutated cancer cells.

Understanding the diversity of T cells and which antigens they target can provide insight into developing personalized immunotherapy to help those patients with weak spots or gaps in their T cell community. Jenny Jiang, Peter and Geri Skirkanich Associate Professor of Innovation in Bioengineering, is characterizing this diversity.

Jiang recently received a Cancer Research Institute’s (CRI) Lloyd J. Old STAR grant to support her research on this topic. The CRI STAR grant identifies mid-career “Scientists TAking Risks” in innovative cancer immunotherapy research areas, providing freedom and flexibility to pursue high-risk, high-reward research with financial support of $1.25 Million over the course of five years.

Jiang spoke with CRI science writer Arthur Brodsky about her research and how the STAR grant will support it.

“In our studies of healthy individuals, who have some natural immune protection against commonly encountered viruses like the flu, we noticed that not everyone has T cells that cover all the possible antigens,” says Jiang. “There are differences in the number and types of flu-targeting T cells that each individual has. For some “exotic” antigens, like those of HIV for example, although the general population doesn’t actually have exposure to them, they should still have a very low level of minimum T cells that can offer some protection from possible future infection. So that part of our T cell arsenal acts as a safety net. But some individuals may completely lack those T cells. In those cases, as you can imagine, those people will have a hard time overcoming a future infection.”

Jiang describes how this is similar to how our bodies prevent cancerous tumor growth.

Read the full story in Penn Engineering Today.

Penn’s 2021 iGEM Team Takes Home Multiple Prizes

Four of Penn’s 2021 iGEM team (left to right): Juliette Hooper, Grace Qian, Saachi Datta, and Gloria Lee.

The University of Pennsylvania’s 2021 iGEM team has been awarded several distinctions in this year’s highly competitive iGEM Competition. The International Genetically Engineered Machine Competition is the largest synthetic biology community and the premiere synthetic biology competition for both university and high school level students from around the world. Each year, hundreds of interdisciplinary teams of students combine molecular biology techniques and engineering concepts to create novel biological systems and compete for prizes and awards through oral presentations and poster sessions.

The Penn team’s project, “OptoReader,” is a combined light-simulation device and plate reader, which makes optogenetic experiments more powerful and accessible. The abstract reads:

“Metabolic engineering has the potential to change the world, and optogenetic tools can make metabolic engineering research easier by providing spatiotemporal control over cells. However, current optogenetic experiments are low-throughput, expensive, and laborious, which makes them inaccessible to many. To tackle this problem, we combined a light-stimulation device with a plate reader, creating our OptoReader. This device allows us to automate ~100 complex optogenetic experiments at the same time. Because it is open source and inexpensive, our device would make optogenetic experiments more efficient and available to all.”

Watch the team’s presentation on OptoReader here.

This year’s Penn team was mentored by Lukasz Bugaj, Assistant Professor in Bioengineering. In addition, the team was supported by Brian Chow, Associate Professor in Bioengineering. Chow has supported previous undergraduate iGEM teams at Penn, and was involved in the creation of the iGEM program during his time as a graduate student at MIT.

OptoReader took home the top prizes in three of the four categories in which it was nominated. These prizes include:

  • Best Foundational Advance (best in track)
  • Best Hardware (best from all undergraduate teams)
  • Best Presentation (best from all undergraduate teams)

They were also awarded a Gold Medal Distinction and were included in the Top 10 Overall (from all undergraduate teams, and the only team from the United States to make the top 10) and Top 10 Websites (from all undergraduate teams).

The awards were announced during iGEM’s online Jamboree Award Ceremony on November 14, 2021 (watch the full award ceremony here).

In addition to the outstanding awards recognition, OptoReader was also selected for an iGEM Impact Grant which awards teams $2,500 to continue development of their projects. This new initiative from the iGEM Foundation was announced earlier this year, and with the support of the Frederick Gardner Cottrell Foundation, is distributing a total of $225,000 in grant funds to 90 iGEM teams during the 2021 competition season. Learn more about the Impact Grant and read the full list of winning teams here.

Penn’s 2021 iGEM team was made up of an interdisciplinary group of women undergraduates from the School of Engineering and Applied Science (SEAS) and the School of Arts and Sciences (SAS):

  • Saachi Datta (B.A. in Biology and Religious Studies 2021)
  • Juliette Hooper (B.S.E. and M.S.E. in Bioengineering 2022)
  • Gabrielle Leavitt (B.S.E. in Bioengineering 2021 and current Master’s student in Bioengineering)
  • Gloria Lee (B.A. in Physics and B.S.E. in Bioengineering 2023)
  • Grace Qian (B.S.E. in Bioengineering 2023)
  • Lana Salloum (B.A. in Neuroscience 2022)

They were mentored by three doctoral students in Bioengineering: Will Benman (Bugaj Lab), David Gonzalez Martinez (Bugaj Lab), Gabrielle Ho (Chow Lab). Saurabh Malani, a graduate student in the Avalos Lab at Prince University, was also very involved in mentoring the team.

OptoReader

The graduate mentors were instrumental in quickly bringing the undergraduates up to speed on a diverse array of skills needed to accomplish this project including circuit design, optics, optogenetics, programming, and additive manufacturing. They then coached the team through building and testing prototypes, as well as accomplishing other objectives required for success at iGEM. These other objectives included establishing collaborations with other iGEM teams, performing outreach, and effectively communicating their project through a website and online presentations.

“This team and their work is outstanding,” said William Benman. “Not only did they sweep several awards, but they did it all with a small team and while working with technology they had no prior experience with. They created a device that not only increases accessibility to optogenetics but also allows optogenetic systems to interface directly with computer programs, allowing for completely new research avenues within the field. They are truly a remarkable group.”

Due to the COVID pandemic, the team operated virtually through the summer of 2020, and then continued in person in the summer of 2021 as the project progressed and more students returned to Penn’s campus. Upon return to campus, the work was conducted in both the Bugaj lab in the Stephenson Foundation Educational Laboratory & Bio-MakerSpace, the primary teaching laboratory in Penn Bioengineering and an interdisciplinary makerspace open to anyone at Penn. The team also collaborated with the Avalos Lab at Princeton University, which conducts research in the application of optogenetics to optimize production of valuable  chemicals in microbes.

“I’m beyond excited about this phenomenal showing from team Penn at the iGEM Jamboree awards ceremony,” said faculty mentor Lukasz Bugaj. “This is truly outstanding recognition for what the team has accomplished, and it wouldn’t have happened without essential contributions from everyone on the team.”

Brian Chow added that this achievement is “no small feat,” especially for a hardware project. “The iGEM competition leans toward genetic strain engineering, but the advances in the field made by these incredible students were undeniable,” he said.

Going forward, the team plans to publish a scientific article and file a patent application describing their device. “It’s clear that there is excitement in the scientific community for what our students created, and we’re excited to share the details and designs of their work,” said Bugaj.

Congratulations to all the team members and mentors of OptoReader on this incredible achievement! Check out the OptoReader project website and Instagram to learn more about their project.

This project was supported by the Department of Bioengineering, the School of Engineering and Applied Science, and the Office of the Vice Provost for Research (OVPR). 

NSF Grant Will Support Research into Sustainable Manufacturing of 3D Solid-state Sodium-ion Batteries and Battery Workforce Training

by Melissa Pappas

The Department of Materials Science and Engineering’s Eric Detsi will lead a team of researchers, including MSE’s Eric Stach and Russell Composto, to develop more eco-friendly batteries that are based on sodium, rather than lithium.

Rechargeable lithium-ion batteries are becoming more ubiquitous, thanks to their use in emerging applications such as battery electric vehicles and grid-scale energy storage, however, these batteries are inefficiently manufactured and unsustainably sourced.

The typical battery cell consists of a separator membrane filled with liquid electrolyte, sandwiched between the negative anode and positive cathode. This design has several drawbacks, including a complex and energy-intensive manufacturing process, inefficient recycling, and increased safety risks as the liquid electrolyte is flammable and crystallization between the electrodes can lead to explosions. Finally, there are substantial geopolitical and environmental risks associated with the global supply chain for lithium-ion battery materials, such as cobalt and lithium.

The solid-state battery design addresses these issues. In solid-state batteries, the flammable liquid electrolyte is replaced by a solid electrolyte, making them safer and more energy efficient. Sodium-ion batteries address the issue of sustainable material sourcing as sodium is more abundant than lithium and cobalt, the materials used in lithium-ion batteries. Both solid-state lithium-ion batteries and sodium-ion batteries are very attractive for battery electric vehicles and grid-scale energy storage applications.

However, current solid-state battery designs also suffer from two major drawbacks: a low capacity for power storage and a resistance to charge transfer.

 To tackle the unsustainability in battery materials and the inefficiency of the current solid-state design, the National Science Foundation has awarded a team of Penn Engineers $2.7 Million in funding through its Future Manufacturing program. The team will be led by Eric Detsi, Stephenson Term Assistant Professor in the Department of Materials Science and Engineering (MSE), and will include Eric Stach, Professor in MSE and Director of the Laboratory for Research on the Structure of Matter, and Russell Composto, Howell Family Faculty Fellow and Professor in MSE with appointments in the Departments of Bioengineering and Chemical and Biomolecular Engineering.

“Our team will investigate a novel ‘Eco Manufacturing’ route to a 3D solid-state sodium-ion battery based on polymer solid-electrolytes,” says Detsi. “Our Eco Manufacturing approach will enable us to create batteries from only abundant elements, achieve ultralong battery cycle life, prevent sodium-dendrite-induced short-circuiting by using a ‘self-healing’ metal anode that can transform into liquid when the battery is operating, and efficiently recycle the battery’s anode and cathode. We will also improve the manufacturing process by using time- and energy-efficient processes including direct ink writing, solid-state conversion, and infiltration.”

Read the full story in Penn Engineering Today.