SEASON 2, October-December, 2020

Episode 1 (October 4, 2020)

He Sun

California Institute of Technology

Juner Zhu

MIT

Sid Kumar

ETH Zurich

Learning a probabilistic strategy for computational imaging sensor selection

Abstract:

Optimized sensing is important for computational imaging in low-resource environments, when images must be recovered from severely limited measurements. In this paper, we propose a physics-constrained, fully differentiable, autoencoder that learns a probabilistic sensor-sampling strategy for optimized sensor design. The proposed method learns a system's preferred sampling distribution that characterizes the correlations between different sensor selections as a binary, fully-connected Ising model. The learned probabilistic model is achieved by using a Markov Chain Monte Carlo (MCMC) sampling inspired network architecture, and is trained end-to-end with a reconstruction network for efficient co-design. The proposed framework is applicable to sensor selection problems in a variety of computational imaging applications. In this paper, we demonstrate the approach in the context of a very-long-baseline-interferometry (VLBI) array design task, where sensor correlations and atmospheric noise present unique challenges. We demonstrate results broadly consistent with expectation, and draw attention to particular structures preferred in the telescope array geometry that can be leveraged to plan future observations and design array expansions.

A physic-guided machine learning framework for elastic plates and shells

Abstract:

Machine learning recently enjoyed remarkable attentions and developments in different branches of engineering sciences. One of the most fundamental challenges of its potential applications is the request for a large and good-quality database that “drives” the models. To overcome this issue, the concept of the physics-guided machine learning method was recently proposed, which incorporates the already-known physical laws into the training process to get a reasonable prediction with only a small observed dataset. In this study, we apply this tool to investigate the finite elastic deformation of plates and shells that is theoretically understood to be governed by the Föppl–von Kármán equations, a set of in-plane and out-of-plane equations that are notoriously difficult to solve by conventional theoretical or numerical methods. In particular, we will discuss different ways of defining the loss function and compare the predictions with numerical solutions in various stress conditions.

Anisotropy by design: metamaterials meet machine learning

Abstract:

After a decade of periodic truss-, plate-, and shell-based architectures having dominated the design of metamaterials, we introduce the new non-periodic class of spinodoid topologies. Inspired by natural self-assembly processes, spinodoid metamaterials are a close approximation of microstructures observed during spinodal phase separation. Their theoretical parametrization is so intriguingly simple that one can bypass costly phase-field simulations and obtain a rich and seamlessly tunable property space as demonstrated, e.g., by their tailorable anisotropic elastic moduli. Counter-intuitively, breaking with the periodicity of classical metamaterials is the enabling factor to the large property space and the ability to introduce seamless functional grading.

Towards the creation of materials with as-designed properties, we address the inverse design question, i.e., how can we systematically and efficiently find a microstructural topology from the nearly infinite design space to achieve a sought combination of macroscale properties. We introduce an efficient and robust machine learning technique for the inverse design of (meta-)materials which, when applied to spinodoid topologies, enables us to generate uniform and functionally graded cellular mechanical metamaterials with tailored direction-dependent (anisotropic) stiffness and density. Despite the inverse problem being ill-posed (e.g., significantly different designs may yield the same desired stiffness), our algorithm, based on the integration of two neural networks for the forward and inverse structure- property maps, renders this challenge well-posed. We specifically present inverse-designed and biomimetic artificial bone architectures based on spinodoid topologies that not only reproduce the properties of trabecular bone accurately but also even geometrically resemble natural bone. With possible integration into multiscale topology optimization or as a standalone framework to explore the design space, this machine learning framework accelerates the design process of (meta-)materials with a wide range of tunable mechanical response (anisotropic stiffness only being the tip of the iceberg).

Episode 2 (October 11, 2020)

Charles Yang

UC Berkeley

Jin Yang

University of Wisconsin - Madison

Yifan Wang

California Institute of Technology

Applying Deep Learning to Composite Design

Abstract:

The rise of additive manufacturing has opened up an enormous, previously unexplored design space. Finding new designs efficiently with desireable mechanical properties is a difficult computational and experimental problem. I will present my work on using deep learning to serve as an emulator for finite element simulations in order to more efficiently explore the design space for binary composites. I will also explore some interpretability methods and explain how we incorporated deep learning into our research problem.

Adaptive Augmented Lagrangian Digital Image/Volume Correlation

Abstract:

Digital image/volume correlation (DIC/DVC) is a powerful, non-invasive experimental method for extracting 2D and 3D volumetric full-field deformation information. The basic idea of this method is to compare images of an object painted with a speckle pattern before and after deformation, and thereby to compute displacements and strains. Most current DIC/DVC algorithms can be categorized into either local or finite element based global methods. However, there are some drawbacks with either of these methods. In the local method, since all of the local subset deformations are estimated independently, the computed displacement field may not be compatible, and the deformation gradients can be noisy, especially for small subsets. Although the global method can incorporate kinematic compatibility, it is generally much more computational expensive than its local counterpart. Here we present a new hybrid algorithm, the augmented Lagrangian digital image/volume correlation (AL-DIC/DVC), that combines the advantages of both the local (fast computation times) and global (compatible displacement field) methods. I will show that the AL-DIC/DVC has higher accuracy and behaves more robustly compared to both current local and global DIC/DVC methods. Finally, I will demonstrate that this new AL-DIC/DVC technique can be implemented with adaptive meshing capability, which can further save computation time one order of magnitude.

Adaptive and Active Lattices for Dynamic Applications

Abstract:

Architected lattices are materials that derive their properties from the selection of both their constitutive materials and the geometry of their micro-and meso-structure. Most existing architected lattices are intrinsically passive, with properties fixed once fabricated. This limits their applications in areas where material adaptivity and tunability are required. In this talk, I will present the development of architected lattices whose mechanical properties can be actively controlled and can adapt to different dynamic conditions. I will first demonstrate an architected lattice filled with granular particles whose damping properties can be controlled to achieve optimal energy absorption, over a range of impact energies. Then, I will discuss actively modulated phononic lattices that allow non-reciprocal wave propagation and unidirectional vibration mitigation. These works open routes towards creating the next generation of structured materials which adapt to varying environmental conditions.

Episode 3 (October 18, 2020)

Donghan Ma

Purdue University

Qing Tu

Texas A&M University

Three-dimensional nanoscopy of whole cells and tissues with in situ point spread function retrieval

Mechanics of two-dimensional halide perovskites: structure-property relationship

Abstract:

Single-molecule localization microscopy is a powerful tool for visualizing subcellular structures, interactions and protein functions in biological research. However, the resolution is degraded with increasing depth due to sample-induced aberrations. In this talk, I will introduce our proposed method that enables the construction of an in situ 3D response of single emitters directly from single-molecule blinking datasets, and therefore allows their locations to be pinpointed with precision that achieves the Cramér-Rao lower bound and uncompromised fidelity.

Abstract:

Two-dimensional (2D) metal halide perovskites (MHP) are emerging members of 2D family with great promises in optoelectronics applications. Mechanical strain is ubiquitous in these materials during device operation, which could induce stability issues and/or impact the device performance. This calls for a comprehensive understanding of the mechanical performance of 2D MHPs in the first place. In this talk, I will present a series studies by scanning probe techniques to unveil the influence of each structural components on the mechanical behaviors of MHPs along both in-plane and out-of-plane. I will conclude my talk by briefly discussing new opportunities in mechanical induced phenomena in 2D MHPs and the influence of the materials’ structures.

Episode 4 (October 25, 2020)

Wei Yan

MIT

Doris Danninger

Johannes Kepler University

Advanced multi-material optoelectronic and electronic fiber devices

Dielectric separators for a new generation of stretchable batteries

Abstract:

Electronic systems that can offer performances of planar, rigid wafer-based devices but with the ability to be flexible, soft, stretchable, biocompatible and wearable are opening a breadth of unique applications in our everyday lives. The integration of a variety of electronic materials within thermal-drawn fibers has emerged as a versatile platform for the fabrication of advanced functional fiber electronic devices. This approach exploits the thermal drawing – the same technology used to fabricate optical fibers –of a macroscopic preform, where functional materials or prefabricated devices are arranged at a prescribed

position, yielding kilometers of electronic fibers with a sophisticated architecture and complex functionalities in a very simple and scalable manner. A single strand of fiber that incorporates materials with disparate electronic, optoelectronics, thermomechanical, rheological and acoustic properties can see objects, hear sound, sense stimuli, communicate, store and convert energy, modulate temperature, monitor health and dissect brains. Integrating these electronic fibers into fabrics, ancient yet largely underdeveloped forms, is setting a stage for fabrics to be the next frontier in computation and Artificial Intelligence. In this presentation, I will present the development of thermally drawn fiber electronics and highlight their unique opportunities in communications, sensing, energy, artificial muscles, 3-D printing, healthcare, smart wearables, robotics, neuroscience as well as in-fiber materials fundamental research in materials science and physics. I will conclude some perspectives for realizing an analogue of “Moore’s law” in fibers and fabrics and the remaining challenges for future research.

Abstract:

Powering soft and elastic forms of robots, machines, and electronic skins is a key issue that promotes the ongoing soft revolution in several fields, from consumer electronics and robotics to biomedical systems, sports and healthcare [1]. A battery as energy storage system is an obvious choice but must be rendered stretchable and soft to be fully compliant and imperceptible to soft robots and human beings, with a first cell configuration developed by us in 2010 [2]. To meet the performance of its rigid counterpart, soft batteries must improve in terms of energy density, capacity, and recharge-ability.

Seeking full compliance with soft bodies, imminent development includes extreme deformability and biocompatibility, when used as energy source for smart healthcare electronics on the human skin. Our focus lies at one key part of such an energy source, namely the separator. Its first and foremost function is to keep positive and negative electrodes apart to prevent electrical short circuits, yet at the same time it has to allow rapid transport of ionic charge carriers. Instead of the widely used hydrogels, we incorporate a porous polymer synthesized by UV-polymerization of a high-internal-phase emulsion (HIPE), with the internal phase being the electrolyte solution needed for the battery. Such a polyHIPE, a continuous polymer envelope surrounding the dispersed droplets of the internal phase, constituting up more than 74% of the volume, forms if only the continuous, external phase contains monomers [3]. The tunability of porosity and thus of conductivity as well is a key feature allowing optimization of the resulting battery characteristics.

Results and Discussion

We study the ion mobility as a function of porosity using electrochemical impedance spectroscopy over a wide frequency range (from mHz to MHz). With high-porosity polyHIPEs we managed to achieve free-electrolyte to polyHIPE conductivity ratios of below 2, whilst still retaining enough mechanical stability to allow use as a battery separator. With this new configuration of the battery cell we managed to achieve unprecedented low internal resistance of the primary cell [4].

Conclusions

With the polyHIPE separators we found a material featuring high stretchability, tunable porosity and fast ion transport, allowing a new configuration of stretchable batteries (Fig. 1). The careful study of the effects of varying porosity on the conductivity and system performance have been rendered possible by electrochemical impedance spectroscopy using a setup designed specially for our needs.

References

[1] S. Bauer, S. Bauer-Gogonea, I. Graz, M. Kaltenbrunner, C. Keplinger, R. Schwödiauer, „25th anniversary article: a soft future: from robots and sensor skin to energy harvesters”, Advanced Materials 26(1), 149-162, 2014

[2] M. Kaltenbrunner, G. Kettlgruber, C. Siket, R. Schwödiauer, S. Bauer, “Arrays of Ultracompliant Electrochemical Dry Gel Cells for Stretchable Electronics”, Advanced Materials, 22:2065-2067, 2010

[3] M.S. Silverstein and N.R. Cameron, „PolyHIPEs — Porous Polymers from High Internal Phase Emulsions“, Encyclopedia of Polymer Science and Technology, 2002

[4] D. Wirthl, R. Pichler, M. Drack, G. Kettlgruber, R. Moser, R. Gerstmayr, F. Hartmann, E. Bradt, R. Kaltseis, C. M. Siket, S. E. Schausberger, S. Hild, S. Bauer, M. Kaltenbrunner, „Instant tough bonding of hydrogels for soft machines and electronics”, Science Advances, 3(6), e1700053, 2017

Episode 5 (November 1, 2020)

Sheng Yin

University of California, Berkeley

Amir Hossein Salahshoor

California Institute of Technology

Ab initio modeling of the role of local chemical short-range order on the energy landscape of screw dislocations in body-centered cubic high-entropy alloys

Transcranial focused ultrasound generates skull-conducted shear waves: computational model and implications for neuromodulation

Abstract:

In traditional body-centered cubic (bcc) metals, the core properties of screw dislocations play a critical role in plastic deformation at low temperatures. Recently, much attention has been focused on refractory high-entropy alloys (RHEAs), which also possess bcc crystal structures. However, unlike face-centered cubic high-entropy alloys (HEAs), there have been far fewer investigations on bcc HEAs, specifically on the possible effects of chemical short-range order (SRO) in these multiple principal element alloys on dislocation mobility. Here, using density functional theory, we investigate the distribution of dislocation core properties in MoNbTaW RHEAs alloys, and how they are influenced by SRO. The average values of the core energies in the RHEA are found to be larger than those in the corresponding pure constituent bcc metals, and are relatively insensitive to the degree of SRO. However, the presence of SRO is shown to have a large effect on narrowing the distribution of dislocation core energies and decreasing the spatial heterogeneity of dislocation core energies in the RHEA. It is argued that the consequences for the mechanical behavior of HEAs is a change in the energy landscape of the dislocations which would likely heterogeneously inhibit their motion.

Abstract:

Low intensity modality of focused ultrasound (fUS) have recently attracted a lot of attention primarily for neuromodulation applications. While longitudinal waves induced by fUS have been extensively studied, the transverse waves are often overlooked, due to the low shear resistance of soft tissues for the most part. Yet, if fUS is imposed in the vicinity of a bone, shear waves with magnitudes comparable to pressure waves will propagate through the bone. We investigate wave propagations in human head through a realistic computational model with a region in the frontal lobe subjected to fUS. We demonstrate that the skull guides the shear waves towards cochlea. This, in turn, explains the off-target auditory responses observed in neuromodulation experiments [1, 2]. We further validate the idea of bone as a waveguide for shear waves by looking into a mouse model. We subject the mouse tail to fUS and demonstrate that the spine serves as a waveguide and carries the transverse waves to the mouse skull.

Episode 6 (November 8, 2020)

Lei Shi

The Chinese University of Hong Kong, Shenzhen

Fei Tong

University of California, Riverside

Electrolysis suppression of ionic conductors under high voltage

Engineering the shapes of photomechanical molecular crystals for soft robot systems

Abstract:

The decomposition voltage of ionic conductors (electrolytes) is very low (usually <5 V), electrochemical reactions are inevitable happen when applying a higher voltage through the electrolytes, therefore, high-power ionics are hard to obtain. The electrode/electrolyte interface is where electrochemical reactions take place, the decomposition process experience Electric-double-layered-capacitor (EDLC) formation and breakdown (electron transfer). We propose a simple method to realize electrolysis suppression of ionic conductors under high voltage, the power of KW level was obtained without obvious electrochemical reactions.

Abstract:

Photomechanical materials that can transform light or photons directly into mechanical work and motions are promising candidates for applications in actuators, switches, waveguide devices, and soft robot systems. Instead of incorporating photochromic molecules in the polymer matrix, molecular crystals composed solely of photochromic molecules that are powered by a variety of photochemical reactions can also execute various photoinduced mechanical motions such as bending, twisting, rotation, crawling, peeling, and hopping. However, controlling the size and shape of molecular crystals to produce desirable mechanical motions remains a challenge because the weak van der Waals intermolecular forces between organic molecules undermine their ability to lock in a specific shape during crystallization. Besides the overall crystal shape, the orientation of the molecules within that shape should also play an important role in determining the photomechanical response. In this talk, I will present some of our recent research work on how we control the size and shape of photomechanical molecular crystals by different methods and techniques to generate different mechanical motions for potential soft robot devices and systems.

Episode 7 (November 15, 2020)

Raj Kumar Pal

Kansas State University

Paul Plucinsky

University of Southern California

Meta-structures and the quest for defect immune wave propagation

A design framework for deployable origami structures

Abstract:

Meta-structures are artificially engineered structures designed to exhibit properties not found in conventional materials. By careful design, one can obtain unprecedented control over various physical properties. Examples in mechanics includes structures having unique static and dynamic properties like negative Poisson’s ratio, zero shear modulus and non-reciprocal wave propagation.

Waveguides transporting energy and information are widely used in bulk and surface acoustic wave devices. They suffer from losses due to localization and scattering at defects and imperfections. In this talk, I will illustrate how such losses can be overcome by a new class of meta-structures: topologically protected waveguides. Inspired by recent developments in quantum condensed matter physics, such waveguides allow for one-way wave propagation along a boundary, immune to the presence of defects in the structure. Such waveguides have potential applications in acoustic signal processing, imaging and vibration isolation.

Abstract:

Shape-morphing finds widespread utility, from the deployment of small stents and large solar sails to actuation and propulsion in soft robotics. Origami structures provide a template for shape-morphing, but rules for designing and folding the structures are challenging to integrate into a broad and versatile design tool. Here, we address this challenge in the context of rigidly and flat-foldable quadrilateral mesh origami (RFFQM). First, we develop an efficient algorithm that explicitly characterizes the designs and deformations of all possible RFFQM. Then, we employ this algorithm in an inverse design framework to approximate a general surface by this family of origami. The structures produced by our framework are "deployable": they can be easily manufactured on a flat reference sheet, deployed to their target state by a controlled folding motion, then to a compact folded state in applications involving storage and portability. We demonstrate the accuracy, versatility and efficiency of our framework through a rich series of examples.

Episode 8 (November 22, 2020)

Yueting Sun

University of Birmingham

Yi Zhang

University of Connecticut

Engineering Metal-organic Frameworks for Mechanical Energy Absorption

Soft bioelectronics and microfluidics for the interrogation of neural function

Abstract:

High-performance mechanical energy absorption has been pursued to protect personnel and important infrastructures and devices. This talk will introduce our recent work on the mechanical energy absorption leveraging the liquid intrusion of Metal-Organic-Frameworks (MOFs). It is found that during the intrusion of non-wetting liquids into the nanoscale pores under mechanical pressure, substantial mechanical energy can be absorbed by generating huge liquid-solid interfaces. This talk will present some latest research on its physical mechanism and potential engineering applications.

Abstract:

Neuroscience studies using optogenetics have greatly improved our understanding of brain circuits. Advances in the combined use of optogenetics and pharmacology to further probe important neurochemical signals has lagged, however, in large part due to the inconvenience of conventional cannulated approaches, as well as the difficulty in controlling, powering, and manufacturing optofluidic devices that are reliable and scalable for distribution to the neuroscience community. In this talk, I will present a battery-free, wireless,

lightweight optofluidic device that allows adjustable infusion rates, hands-free operation, and unlimited power supply, and is compatible with existing near-field communication (NFC) technology. I will also present a wireless, battery-free device that integrates a microscale inorganic light-emitting diode and an ultralow-power microfluidic system with an electrochemical pumping mechanism in a soft platform that can be mounted onto target peripheral nerves for programmed delivery of light and/or pharmacological agents in freely moving animals. The developed technology has potential for large-scale manufacturing and broad distribution to the neuroscience community, with capabilities in targeting specific neuronal populations in freely moving animals. In addition, the same platform can easily be adapted for a wide range of other types of passive or active electronic functions, including electrical stimulation.

Episode 9 (November 29, 2020)

Tian Yu

Princeton University

Yupeng Zhang

Texas A&M University

Destroy bistability in folded thin sheets by removing the singularity

Influence of assumed strain hardening relation on stress-strain response identification from indentation

Abstract:

Creased thin sheets exhibit bistability, with a pressed-through state possessing a localized elastic singularity. We experimentally explore the loss of bistability upon excision of the singularity and a surrounding region of material, varying the thickness and hole geometry. We examine numerical solutions of an inextensible strip model, varying hole geometry, crease angle and stiffness, and other factors, and find reasonable qualitative agreement with experimental bistability boundaries.

These phenomena are consequential to the mechanics and design of crumpled elastic sheets, developable surfaces, origami and kirigami, and other deployable and compliant structures.

Abstract:

Instrumented indentation tests provide an attractive means for obtaining data to characterize the plastic response of engineering materials. One difficulty in doing this is that the relation between the measured indentation force versus indentation depth response (P-h data) and the plastic stress-strain response is not unique. This talk will present the characterization of plastic stress-strain response using a Bayesian statistical approach by taking account of both P-h data and the surface profile after unloading. A variety of power law expressions have been used to characterize the uniaxial plastic stress-strain response of engineering materials, but the form that gives the best fit for a material is not known a priori. The influence of assumed strain hardening relation on the stress-strain response identification will also be discussed.

Episode 10 (December 6, 2020)

Seyed Mirvakili

MIT

Morteza Amjadi

Heriot-Watt University

From Nano to Macro: Actuators for Real-World Applications

Functional Nanomaterial Composites for Soft Sensing and Actuation

Abstract:

Actuators, also known as artificial muscles, are an integral part of daily life. From transportation means to biomedical devices, they all utilize actuators for one or more vital tasks. Cycle life, cost, output force, strain, energy density, power density, and efficiency are the key performance metrics that are used to evaluate the suitability of actuators for a specific application. The emerging field of soft actuators has been introducing new classes of stimuli-responsive materials that can mimic muscle’s properties (i.e., generating strain, changing stiffness). While these materials outperform the performance of the human muscle in one or more of the mentioned attributes, there is still no stimuli-responsive material that can beat the human muscle in all of them. In this talk, an overview of the field will be given and the current challenges and possible directions will be discussed.

Abstract:

Soft machines have many applications, ranging from multifunctional wearable medical devices for feedback therapy to prosthetics, non-invasive surgical tools, and soft robots for safe human-robot interaction. High-performance flexible sensors and actuators are the key components of soft machines. In this seminar, I will cover our latest research activities on the development of functional nanocomposites based wearable strain sensors for human motion detection and soft robotics. I will demonstrate how bioinspired structures can help to improve the sensing and skin-adhesion performance of wearable sensors. The next part of my talk will focus on the development of programmable soft actuators based on composite materials. Finally, I will address challenges associated with the design of integrated soft machines capable of multimodal sensing and controlled stimulation.

Episode 11 (December 13, 2020)

Hongri Gu

ETH Zurich

Amirreza Aghakhani

Max Planck Institute for intelligent systems

Soft robotic structures with complex magnetizations

Acoustic bubble-based microrobots

Abstract:

Small-scale soft magnetic robots can navigate through confined and unconstructed environments using external magnetic fields, that are promising for biomedical applications including targeted drug delivery and minimally invasive surgeries. Developing these multi-functional soft robots imposes unique challenges in design, fabrication, and control of soft magnetic material and structures. In this talk, I will introduce some unique properties of soft roots that are enabled by complex magnetizations. I will also show different methods to program the magnetization patterns for millimeter soft robotic systems. Soft robotic structures with complex magnetizations can facilitate the fundamental studies of active matter system, construct metamaterials, and design novel biomedical devices.

Abstract:

Untethered microrobots have significant applications in medical interventions such as targeted drug delivery and minimally invasive surgery. However, their locomotion on curved 3D spaces at high speeds is limited. Here, I present acoustically powered microrobots that use a fast and unidirectional locomotion strategy, termed as surface slipping, and can navigate on both flat and curved surfaces. The 3D-microprinted robots contain a spherical air bubble with which they harness acoustic waves for propulsion at incredibly high speeds, up to 90 body lengths per second with a body length of about 25 µm. The proposed microrobots have the thrust force of about two to three orders of magnitude higher than that of microorganisms, such as algae and bacteria, which is enough for navigation inside the vascular capillaries with blood flow. Such nonconventional acoustic microrobot designs could lay the groundwork for fast and efficient swimming in Stokes flows.

Episode 12 (December 20, 2020)

Canhui Yang

Southern University of Science and Technology

Jue Deng

MIT

Ionotronic Luminescence: Principle, Materials and Fabrication

Electrical Bioadhesive Interface for Robust Tissue-Electronics integration

Abstract:

Electroluminescence for many decades have been widely used for displays and solid-state lighting. Advances in stretchable and transparent electrodes bring enormous new opportunities for electroluminescence. Recently, ionic conductors have been employed to activate phosphors that can luminesce in response to alternating electric field, achieving ionotronic luminescence of exceptionally high stretchability. In this talk, I will firstly introduce the working principles of ionotronic luminescence by exemplifying one of the first-generation ionotronic luminescent devices. Then the physical and chemical properties of constituent materials, i.e. hydrogel and hydrophobic elastomer, will be discussed. Finally, a process of multistep dip coat will be delineated to meet the fundamental challenge that persists in integrating hydrogels and hydrophobic elastomers-in various manufacturing processes-with strong, stretchable, and transparent adhesion.

Abstract:

Reliable functions of bioelectronic devices require conformal, stable, and conductive interfaces with biological tissues. Integrating bioelectronic devices with tissues usually relies on physical attachment or surgical suturing, yet these methods face challenges such as non-conformal contact, unstable fixation, tissue damage, and/or scar formation. In this talk, I will present our new e-bioadhesive technology to achieve rapid, robust, and on-demand detachable integration of bioelectronic devices on diverse wet dynamic tissues. I will discuss the design of the e-bioadhesive interface in the aspects of mechanical and electrical properties, biocompatibility, applicability, and functionalities. I will conclude my talk by briefly discussing some perspectives for enhancing tissue-device integration and the remaining challenges and opportunities.

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