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Philip LeDuc

Philip LeDuc

· William J. Brown Professor, Director, Center for the Mechanics and Engineering of Cellular SystemsVerified

Carnegie Mellon University · Mechanical Engineering

Active 1967–2026

h-index50
Citations8.3k
Papers42986 last 5y
Funding$4.5M
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About

Philip LeDuc is the William J. Brown Professor in the Department of Mechanical Engineering at Carnegie Mellon University. His research operates at the intersection of mechanical engineering and biology, where he investigates cells and molecules as systems that can be analyzed using principles similar to those applied to machines such as planes and automobiles. His work encompasses a broad range of biological systems, from mammalian cells and microorganisms to developmental biology systems, applying mechanical engineering concepts like solid mechanics, fluid mechanics, and control theory to understand diverse nature-based systems. In addition to his fundamental research, LeDuc focuses on energy-related applications, particularly algae and bacterial fuel cells, conducting both basic science and applied research in these areas. LeDuc has received numerous awards, including the National Science Foundation CAREER award, George Tallman Ladd Research Award, and the Beckman Foundation Young Investigator Award. He is a Fellow of several professional societies, including the Biomedical Engineering Society, American Society of Mechanical Engineers, and the American Institute for Medical & Biological Engineering. His contributions extend to leadership roles in research initiatives such as the Center for the Mechanics and Engineering of Cellular Systems and the Bioengineered Organs Initiative. His work has been recognized for its innovative approach to understanding cellular and molecular mechanics, contributing significantly to the fields of bioengineering, biomechanics, and biomedical manufacturing.

Research topics

  • Computer Science
  • Engineering
  • Biology
  • Artificial Intelligence
  • Medicine
  • Computational biology
  • Engineering drawing
  • Data science
  • Cancer research
  • Electrical engineering
  • Materials science
  • Composite material
  • Internal medicine
  • Nanotechnology
  • Radiology
  • Biochemical engineering
  • Obstetrics
  • Pathology
  • Bioinformatics
  • Chemistry

Selected publications

  • Automated Discovery of Multicellular Behavior for Optimized Plant Growth and Climate Resilience

    Advanced Intelligent Systems · 2026-02-04

    articleOpen accessCorresponding

    Developing resilience against climate change and establishing food security will require significant research into the responses of multicellular organisms to their environment. New approaches, such as lab automation, can substantially increase the rate of data collection for organism‐level behavior. This report describes an automated robotic system for studying multicellular organisms to accelerate scientific experimentation. The robot can simultaneously image and deliver chemicals to each organism during multiday experiments, and uses a deep learning model to automatically obtain phenotypic data. This system's abilities are demonstrated by creating a plant growth strategy for food security applications that increases biomass while decreasing nutrient utilization. Furthermore, plant growth is characterized under high salt concentrations to better understand the effects of climate change on freshwater ecosystems. This robotic approach improves lab automation for studying multicellular organisms by increasing experimental throughput, and will enable researchers to improve crop yields under uncertain climates and predict the response of organisms in changing environments.

  • Fast Image Segmentation Toward Automation of 3D Ice Printing

    Chemical & Biomedical Imaging · 2026-01-13

    articleOpen accessSenior authorCorresponding

    Freeform 3D ice printing is emerging as a promising additive manufacturing method with potential applications in engineering, medicine, science, and art. Printing ice at the micrometer–millimeter scale is a challenging, high-frequency additive manufacturing process. Freeform ice 3D printing though is an early stage manufacturing process where complex geometries require significant time to design manually through an empirical trial-and-error approach, due to the nonlinear nature of droplet deposition and solidification along with unavoidable uncertainties and noise. This process would be tremendously improved with better understanding and harnessing the ability to visualize, analyze and adjust the printing process in real time. For this automation, using approaches such as closed loop control that have allowed tremendous advances in other fields like self-driving cars, plane autopilot, etc. would be very useful. In order to use closed loop control for this process, ice position and shape must be determined and transformed into in situ actionable data, which is complicated further by the transparency of ice and speed required for the phase transition from water to ice. We implemented vision techniques to build a data set to train a machine learning algorithm though an ice segmentation approach using a convolutional filter. We also implemented a hybrid optical flow algorithm (Farneback-FAST) to create a segmented video frame data set for training a neural network, Icenet. This approach was faster than the Farneback-FAST, segmenting frames in 25 ms, which allows for single and low multi droplet control. Our approaches will enable future closed loop control of the printing process and will be useful in a variety of areas including additive manufacturing, organ on a chip systems, and biomanufacturing.

  • Contact Detection and Manipulation With a Shape-Memory Alloy Based Soft Gripper

    IEEE Robotics and Automation Letters · 2025-06-06 · 2 citations

    article

    Soft robotics offers the opportunity to create dexterous machines that can safely handle delicate objects. Grippers made from deformable actuators and compliant materials can deform around the objects with which they come in contact. The continuum mechanics of flexible manipulators can be leveraged for safe manipulation tasks such as twisting and grasping during manufacturing. However, to achieve this goal, contact sensing and controls for manipulators in these soft systems still remain a challenge in the field. This paper demonstrates a shape-memory alloy actuated soft gripper, with each finger able to bend about multiple axes. This enables the soft gripper to perform twisting tasks and handle various and fragile objects. Using capacitive bend sensors, we also demonstrate that the measured impedance of motion can be used as a proxy for contact, greatly increasing performance in a delicate manipulation task

  • Analysis of TCC in p-n Short Silicon Diodes at 300–400 K

    IEEE Transactions on Electron Devices · 2024-06-11 · 2 citations

    articleOpen accessSenior author

    This work presents a study of the thermal sensitivity of p-n short silicon diodes represented by the temperature coefficient of current (TCC) for thermal sensing applications. It proposes an analytical model (AM) of the TCC of p-n short silicon diodes under low-level injections and in the temperature range of 300–400 K. First, the TCC is studied at diffusion and recombination regimes and it is discriminated between different physical contributions. Then, it is followed by a discussion on the origins and influences of these contributions to provide a usable and simplified analytical expression of the TCC. Finally, the proposed AM is compared to technology computer-aided design (TCAD) simulations and experimental results at 300–400 K. It shows a strong correlation for different designs of p-n short diodes.

  • Fly Me to the Micron: Microtechnologies for Drosophila Research

    Annual Review of Biomedical Engineering · 2024-07-03 · 3 citations

    articleOpen access

    Multicellular model organisms, such as Drosophila melanogaster (fruit fly), are frequently used in a myriad of biological research studies due to their biological significance and global standardization. However, traditional tools used in these studies generally require manual handling, subjective phenotyping, and bulk treatment of the organisms, resulting in laborious experimental protocols with limited accuracy. Advancements in microtechnology over the course of the last two decades have allowed researchers to develop automated, high-throughput, and multifunctional experimental tools that enable novel experimental paradigms that would not be possible otherwise. We discuss recent advances in microtechnological systems developed for small model organisms using D. melanogaster as an example. We critically analyze the state of the field by comparing the systems produced for different applications. Additionally, we suggest design guidelines, operational tips, and new research directions based on the technical and knowledge gaps in the literature. This review aims to foster interdisciplinary work by helping engineers to familiarize themselves with model organisms while presenting the most recent advances in microengineering strategies to biologists.

  • Image segmentation and control of freeform 3D ice printing with computer vision

    Biophysical Journal · 2024-02-01 · 1 citations

    articleSenior author
  • 3D freeform ice printing for fabricating biomimetic vascular networks in engineered tissue

    Biophysical Journal · 2024-02-01

    articleSenior author
  • Author Correction: Characterization of neural mechanotransduction response in human traumatic brain injury organoid model

    Scientific Reports · 2024-01-25 · 1 citations

    erratumOpen access
  • Physics of microscale freeform 3D printing of ice

    Proceedings of the National Academy of Sciences · 2024-07-15 · 6 citations

    articleOpen accessSenior authorCorresponding

    Ice is emerging as a promising sacrificial material in the rapidly expanding area of advanced manufacturing for creating precise 3D internal geometries. Freeform 3D printing of ice (3D-ICE) can produce microscale ice structures with smooth walls, hierarchical transitions, and curved and overhang features. However, controlling 3D-ICE is challenging due to an incomplete understanding of its complex physics involving heat transfer, fluid dynamics, and phase changes. This work aims to advance our understanding of 3D-ICE physics by combining numerical modeling and experimentation. We developed a 2D thermo-fluidic model to analyze the transition from layered to continuous printing and a 3D thermo-fluidic model for the oblique deposition, which enables curved and overhang geometries. Experiments are conducted and compared with model simulations. We found that high droplet deposition rates enable the continuous deposition mode with a sustained liquid cap on top of the ice, facilitating smooth geometries. The diameter of ice structures is controlled by the droplet deposition frequency. Oblique deposition causes unidirectional spillover of the liquid cap and asymmetric heat transfer at the freeze front, rotating the freeze front. These results provide valuable insights for reproducible 3D-ICE printing that could be applied across various fields, including tissue engineering, microfluidics, and soft robotics.

  • Plant Movement Response to Environmental Mechanical Stimulation Toward Understanding Predator Defense

    Advanced Science · 2024-08-29 · 7 citations

    articleOpen accessSenior authorCorresponding

    Plants are fascinating living systems, possessing starkly different morphology to mammals, yet they have still evolved ways to defend themselves, consume prey, communicate, and in the case of plants like Mimosa pudica even move in response to a variety of stimuli. The complex physiological pathways driving this are of great interest, though many questions remain. In this work, a known responsive plant, M. pudica is mechanically stimulated, in terms of wounding via removal of pinnae, nonwounding mechanical poking, and nonwounding pulses of air through a designed small nozzle approach. Removal of clusters called pinnae resulted in rapid, asymmetric response in the adjacent pinnae, while mechanical poking and air pulse responses are slower and more localized. Additionally, while the response from poking propagated across the plant, wind stimuli consistently resulted in the actuation of only the leaflets directly stimulated, suggesting unique sensing mechanisms. Mechanical damage may imply a potential predator, while mechanical stimulation from airflow may be processed as wind, which is of little danger. These findings demonstrate an intricate, stimulant-dependent mechanical sensing process, which is important in plant physiology, mechanobiology, and future biohybrid soft robotic designs.

Recent grants

Frequent coauthors

  • C. Bermond

    Institut polytechnique de Grenoble

    101 shared
  • T. Lacrevaz

    Institut polytechnique de Grenoble

    88 shared
  • L. Cadix

    STMicroelectronics (Switzerland)

    81 shared
  • N. Sillon

    CEA Grenoble

    77 shared
  • B. Fléchet

    Institut de Microélectronique, Electromagnétisme et Photonique

    73 shared
  • A. Farcy

    STMicroelectronics (Czechia)

    62 shared
  • Chao‐Min Cheng

    National Tsing Hua University

    60 shared
  • S. Chéramy

    Commissariat à l'Énergie Atomique et aux Énergies Alternatives

    60 shared

Labs

  • The LeDuc LabPI

    The LeDuc Lab focuses on the intersection of biology and engineering, with research interests including artificial cardiac tissue, renewable energies, biomimicry, regenerative medicine, robotics, additive manufacturing, and more.

Awards & honors

  • National Science Foundation CAREER award
  • George Tallman Ladd Research Award
  • Russell V. Trader Career Faculty Fellow
  • Benjamin Richard Teare Teaching Award
  • Professor of the Year as voted by the senior class
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