Soft flexion sensors integrating strechable metal conductors on a silicone substrate for smart glove applications

We design and implement a sensory skin that monitors in real time finger flexure (three sensors per finger) of a user's hand. Compared to current technologies, the electronic skin is made entirely of stretchable materials integrating silicone rubber, low resistivity liquid metal interconnects and high strain sensitivity, microstructured thin metal films. Microfabrication of the sensors combines traditional thin film process and additive manufacturing techniques. We incorporate the skin on a textile glove and demonstrate its function as an interface for finger motion and posture detection using a robotic test platform. © 2015 IEEE

Elastomeric substrates with embedded stiff platforms for stretchable electronics

Stretchable electronics typically integrate hard, functional materials on soft substrates. Here we report on engineered elastomeric substrates designed to host stretchable circuitry. Regions of a stiff material, patterned using photolithography, are embedded within a soft elastomer leaving a smooth surface. We present the associated design rules to produce stretchable circuits based on experimental as well as modeling data. We demonstrate our approach with thin-film electronic materials. The "customized" elastomeric substrates may also be used as a generic elastic substrate for stretchable circuits prepared with alternative technologies, such as transfer-printing of inorganic, thinned devices. (C) 2013 American Institute of Physics. [http://dx.doi.org/10.1063/1.4799653

Engineering reversible elasticity in ductile and brittle thin films supported by a plastic foil

Reversible deformation is a unique property of elastic materials. Here, we design and fabricate highly stretchable multilayered films by patterning Y-shaped motifs through films of non- elastic materials, e.g. plastics, metals, ceramics. By adjusting the geometry and density of the motif, as well as the thickness of the film(s), the effective spring constant of the engineered film(s) can be tuned. Three-dimensional bending of the patterned film(s) enables macroscopic stretchability and minimizes local film strain fields. The engineered films demonstrate no preferential direction of stretching and the proposed design is versatile. Furthermore our approach is compatible with thin-film processing. We demonstrate the Y-shaped motifs allow for the design of stretchable plastic foils coated with metallic and metal oxide conductors. We anticipate the patterned motifs can be scaled down to offer a wider range of elastic electronic materials to use in stretchable electronics and to create soft bioelectronics. (c) 2017 Elsevier Ltd. All rights reserved

Microscale liquid metal conductors for stretchable and transparent electronics

Integrated wearable electronics capable of transducing and transmitting biophysical information on complex and dynamic systems are attracting high interest across the consumer electronics, clinical, and research domains. Gallium and gallium-based liquid metals (LMs) emerge as promising conductor technology for wearables due to their excellent combination of electrical conductivity and mechanical compliance. However, LMs feature complex physical and chemical properties that pose significant manufacturability challenges. Herein, a microtechnology approach is presented to fabricate deformable, microscale LM conductors with high surface density and over large surface areas. Based on a combination of soft lithography, directional patterning, and thermal evaporation of gallium, this new technology enables a range of designs and geometries that can be used to form LM-based stretchable electronic conductors. The versatility of the technology enables a palette of circuit designs that can offer unrivaled transparency (T > 89%) or large metallization density (2/5 µm line/gap)

A 16-Channel Neural Recording System-on-Chip With CHT Feature Extraction Processor in 65-nm CMOS

Next-generation invasive neural interfaces require fully implantable wireless systems that can record from a large number of channels simultaneously. However, transferring the recorded data from the implant to an external receiver emerges as a significant challenge due to the high throughput. To address this challenge, this article presents a neural recording system-on-chip that achieves high resource and wireless bandwidth efficiency by employing on-chip feature extraction. Energy-area-efficient 10-bit 20-kS/s front end amplifies and digitizes the neural signals within the local field potential (LFP) and action potential (AP) bands. The raw data from each channel are decomposed into spectral features using a compressed Hadamard transform (CHT) processor. The selection of the features to be computed is tailored through a machine learning algorithm such that the overall data rate is reduced by 80% without compromising classification performance. Moreover, the CHT feature extractor allows waveform reconstruction on the receiver side for monitoring or additional post-processing. The proposed approach was validated through in vivo and off-line experiments. The prototype fabricated in 65-nm CMOS also includes wireless power and data receiver blocks to demonstrate the energy and area efficiency of the complete system. The overall signal chain consumes 2.6 μW and occupies 0.021 mm² per channel, pointing toward its feasibility for 1000-channel single-die neural recording systems

Matrix stiffness modulates formation and activity of neuronal networks of controlled architectures

The ability to construct easily in vitro networks of primary neurons organized with imposed topologies is required for neural tissue engineering as well as for the development of neuronal interfaces with desirable characteristics. However, accumulating evidence suggests that the mechanical properties of the culture matrix can modulate important neuronal functions such as growth, extension, branching and activity. Here we designed robust and reproducible laminin-polylysine grid micropatterns on cell culture substrates that have similar biochemical properties but a 100-fold difference in Young's modulus to investigate the role of the matrix rigidity on the formation and activity of cortical neuronal networks. We found that cell bodies of primary cortical neurons gradually accumulate in circular islands, whereas axonal extensions spread on linear tracks to connect circular islands. Our findings indicate that migration of cortical neurons is enhanced on soft substrates, leading to a faster formation of neuronal networks. Furthermore, the pre-synaptic density was two times higher on stiff substrates and consistently the number of action potentials and miniature synaptic currents was enhanced on stiff substrates. Taken together, our results provide compelling evidence to indicate that matrix stiffness is a key parameter to modulate the growth dynamics, synaptic density and electrophysiological activity of cortical neuronal networks, thus providing useful information on scaffold design for neural tissue engineering. (C) 2016 Elsevier Ltd. All rights reserved