Month: April 2026

Farhad Imani Wins NSF CAREER Award to Build Manufacturing Systems That Think

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Automation dominates modern factories, but much of it still breaks when parts vary, damage is uncertain, and expert judgement is required. Farhad Imani’s project targets this failure by developing robotic manufacturing systems that can sense change and adapt in real time.

 

Professor Imani and 3rd year Ph.D. student, Zhiling Chen, working with robotic arms in his lab. (UConn Photo/Chris LaRosa)

A critical challenge is emerging in manufacturing: how to repair and restore high-value components when current systems can’t handle deviation. Factories are full of automation systems that perform well when processes are repetitive. The moment geometry shifts, the process changes, or defects evolve, they struggle.  

NSF CAREER Award recipient Farhad Imani, an assistant professor in mechanical engineering at the University of Connecticut, is tackling this challenge head-on through the development of a new class of intelligent robotic manufacturing systems that can inspect parts, interpret multimodal sensor data, and reason through uncertainty. 

 

 

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Embracing Uncertainty For Stronger Engineering Systems

Many real-world systems—from materials to infrastructure—contain a mix of order and randomness, a concept known as stochasticity

 

Students and faculty involved in the stochasticity research (Contributed photo).

A few years after receiving the National Science Foundation Early CAREER Award, UConn College of Engineering Assistant Professor Hongyi Xu is demonstrating how embracing uncertainty can lead to stronger, smarter engineering systems. 

Xu’s research focuses on a simple, but challenging, fact, which is that not everything in engineering is perfectly uniform. Many real-world materials contain a mix of order and randomness, a concept known as stochasticity. Rather than designing around that uncertainty, Xu has developed new computational tools that allow engineers to use it intentionally, and combine it seamlessly with ordered materials. 

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04.17.26 Dr. Daniele Vivona

Understanding Atomistic Transport and Interfacial Evolution to Design Electrochemical Devices

Date: April 17, 2026; Time: 2:30 PM Location: PWEB 175

 

Abstract: Electrochemical devices rely on coupled transport within materials and charge transfer across interfaces involving both ions and electrons. Their performance and durability are often limited by interfacial reaction mechanisms, where sluggish charge transfer, parasitic reactions, and defect formation drive energy conversion and degradation and ultimately determine device efficiency and lifetime. Despite significant advances in materials and interface design, fundamental questions remain regarding how local chemistry and defects control reaction kinetics and the failure mechanisms that emerge under operating conditions. In this talk, the speaker will introduce the fundamental operating principles of electrochemical devices, with an emphasis on atomic-scale transport and interfacial processes that govern performance and degradation in lithium-ion battery cathode/electrolyte systems and proton-exchange membrane electrolyzers. The presentation will highlight research efforts from the speaker’s recently established group on identifying atomic-scale mechanisms of defect formation and electrochemical dissolution, and on designing improved electrochemical interfaces for enhanced stability and performance. Two Examples include protective coatings for battery materials and strategies to tune electronic structure of catalysts through chemical interactions with supports. Finally, the talk will discuss how a combined understanding of transport and interfacial chemistry enables the identification of physically grounded descriptors, opening pathways for the discovery of new materials and design strategies for next-generation electrochemical devices.

Biographical Sketch: Daniele Vivona is an Assistant Professor in the School of Mechanical, Aerospace, and Manufacturing Engineering at the University of Connecticut. He received his Ph.D. in Mechanical Engineering from the Massachusetts Institute of Technology (MIT), where he was a MathWorks Mechanical Engineering Fellow, Rohsenow Graduate Fellow, and member of the MIT Society of Energy Fellows. He holds B.Sc. and M.S. degrees in Energy Engineering from the Polytechnic University of Milan and an M.S. in Mechanical Engineering from the University of Connecticut.

His research focuses on the mechanisms governing degradation, dissolution, and interfacial reactivity in electrochemical energy systems, including batteries and catalysts. His group combines first-principles simulations, atomistic modeling, and electrochemical experiments to establish quantitative links between surface chemistry, reaction environments, and material stability. By integrating physics-based models with data-driven approaches, his work aims to develop predictive frameworks, and digital and experimental “twins” for the design and lifetime control of electrochemical materials and devices.