Date:
Wednesday, March 22, 2023
Location:
Hilton San Diego Bayfront Hotel, Sapphire Level, Ballroom D
Sponsored by:
TMS Materials Processing & Manufacturing Division, TMS Nanomechanical Materials Behavior Committee
Organizers:
Wendelin Wright, Bucknell University; Gang Feng, Villanova University
Bioinspiration and biomimetics are concerned with unraveling the fascinating workings of biological evolution: the resulting robust materials and “device” solutions, arrived at by blind trial and error, usually carry an impressive simplicity and elegance. What’s more, their built-in resource efficiency and sustainability are additional benefits vital for the continued existence of our environment. This symposium will highlight some outstanding examples of lessons learned from nature, e.g., for contact, robotics, and medicine. It will focus on the science behind them and on how their applications are beginning to make a difference in everyday life.
This award symposium was established to honor Professor William D. Nix and the tremendous legacy that he has developed and shared with the minerals, metals, and materials community and to highlight and promote continued progress and innovation relevant to research into the underlying mechanisms and mechanical behavior of macro-, micro-, and nanoscale materials. This symposium recognizes Nix’s hallmark of combining model-driven insight with predictive capabilities for achieving elegant materials solutions.
William D. Nix Award Lecturer
Speaker: Eduard Arzt, INM – Leibniz Institute for New Materials and Saarland University
Lecture Title: "From Bioinspiration to Machine Learning—a New Concept for Object Manipulation"
Date: Wednesday, March 22, 2023
About the Presentation
Evolution has evolved fascinating resource-efficient and sustainable materials architectures to ensure survival. Inspired by nature, micropatterning of polymeric surfaces has become a powerful paradigm. Celebrated examples range, e.g., from controlled wetting and anti-icing to coloration and switchable adhesion. Fundamental adhesion studies have not only demonstrated the benefit of microfibrillar architectures but have also inspired innovative pick-and-place systems or delicate adhesives for skin and body organs. But several problems remain: how do we release micro-objects with negligible mass? And how can we ensure reliability of gripping, also in demanding conditions such as in space? We have proposed a machine-learning-based optical monitoring system that images the individual fibrillar contacts in operando. Several classifiers predict successful handling with high accuracy, indicating, e.g., incomplete or off-center gripping. The improved reliability of this technology will impact everyday life as eco-friendly solutions will be increasingly essential for our own survival.
About the Speaker
Eduard Arzt is professor for new materials and scientific director of INM – Leibniz Institute for New Materials in Saarbrücken, a leading German research laboratory. Previously, he co-directed the Max Planck Institute for Metals Research in Stuttgart for almost two decades. Following a physics Ph.D. from the University of Vienna, Austria, he performed research at Cambridge University, Stanford University, MIT, and the University of California. He is the recipient, e.g., of the Leibniz Award, the TMS Fellow Award, the TMS Morris Cohen Award, and several competitive European Research Council grants. He is a member of several academies including the U.S. National Academy of Engineering. Arzt is editor-in-chief of the review journal Progress in Materials Science and co-founder of a deep tech start-up.
Featured Speakers
Subra Suresh, Nanyang Technological University, Singapore
"Deep Learning from Nature and Machines for Engineered and Biological Materials"
About the Presentation
Rapid advances in computing and machine learning, along with developments in materials processing that mimic unique features and characteristics found in natural systems, offer unprecedented opportunities to design and deploy a new generation of engineered and biological materials. We demonstrate specific examples of materials design, analysis, or characterization using machine learning and biomimetics from the vantage point of three different disciplines: materials science, plant science, and biomedical science. The examples chosen here cover a spectrum of topics that include: modulating the bandgap of natural and engineered materials for applications in microelectronics, optoelectronics and energy systems; characterization of material properties at multiple length scales using multi-fidelity approaches in machine learning; design of new classes of plant-based materials with unique properties for environmental sustainability, soft robotics, and flexible electronics; and machine-learning approaches combined with microfluidics and computational simulations to assess, monitor, and guide clinical outcomes in such diseases as diabetic retinopathy.
Ulrike Wegst, Department of Physics, Northeastern University
"From Ice-Crystal Growth to Freeze-Cast Scaffolds for Biomedical Applications"
About the Presentation
Anisotropic, partially faceted crystal growth, which determines the rich diversity of snowflake morphologies, also defines the component self-assembly and pattern formation that we observe during freeze casting, a manufacturing technique applicable to all classes of materials based on the directional solidification of aqueous solutions and slurries. What makes the resulting ice-templated materials so attractive is that, after freeze drying, they possess complex hierarchical architectures and porosities, which can span dimensions from the nano- to the macroscale, just like natural materials. This is the reason why freeze casting is highly attractive for the manufacture of biomaterials, which frequently are required to mimic several of the structural and functional characteristics of their natural counterparts. Illustrated will be how different mechanisms that drive structure formation during processing can be employed in the material’s structural and property optimization for biomedical applications, such as peripheral nerve repair.
Xuan Zhang, INM–Leibniz Institute for New Materials
"Bioinspired Designs for Micro-Object Releasing"
About the Presentation
Microstructured surfaces have become an innovative and sustainable strategy for robotic gripping and handling. One crucial problem appears in micro robotic handling: the release and precise placement of superlight micro-objects which, for dimensional reasons, tend to stick tenaciously to other surfaces. As the objects shrink in size, their gravitation will be too small to allow detachment by conventional mechanisms. Here, we have proposed several bioinspired designs for controlled release mechanisms of micro-objects. Following theory, numerical simulations, and demonstration experiments, fibirils with geometry modifications arranged in regular pattern, and a metastructure involving a snap-action were developed. These innovative designs proposed, due to the purely mechanical trigger for realizing the release and unprecedented high switching ratio ~104, have the potential to create a newly energy-efficient paradigm for handling and placing superlight objects.
Christoph Keplinger, Max Planck Institute for Intelligent Systems
"Artificial Muscles for the Lifelike Robots of the Future"
About the Presentation
Robots today rely on rigid components and electric motors, making them heavy, unsafe near humans, expensive, and ill-suited for unpredictable environments. Nature, in contrast, uses soft materials like muscle and skin, and has produced organisms that drastically outperform robots in terms of agility, dexterity, and adaptability. To create a new generation of lifelike robots that match the vast capabilities of biological systems, we need to develop actuators that replicate the astonishing all-around actuation performance of muscle. Hydraulically Amplified Self-healing ELectrostatic (HASEL) transducers are a new class of self-sensing, high-performance muscle-mimetic actuators, which are electrically driven and match or exceed most performance metrics of biological muscle; modeling results reveal rich underlying materials science to be further explored, and they lay out a roadmap towards HASELs with drastically improved performance, far surpassing both biological muscle and traditional electromagnetic motors. This talk gives an overview of the latest research results and commercialization efforts.