Feasibility Study of Extended-Gate-Type Silicon Nanowire Field-Effect Transistors for Neural Recording.

In this research, a high performance silicon nanowire field-effect transistor (transconductance as high as 34 µS and sensitivity as 84 nS/mV) is extensively studied and directly compared with planar passive microelectrode arrays for neural recording application. Electrical and electrochemical characteristics are carefully characterized in a very well-controlled manner. We especially focused on the signal amplification capability and intrinsic noise of the transistors. A neural recording system using both silicon nanowire field-effect transistor-based active-type microelectrode array and platinum black microelectrode-based passive-type microelectrode array are implemented and compared. An artificial neural spike signal is supplied as input to both arrays through a buffer solution and recorded simultaneously. Recorded signal intensity by the silicon nanowire transistor was precisely determined by an electrical characteristic of the transistor, transconductance. Signal-to-noise ratio was found to be strongly dependent upon the intrinsic 1/f noise of the silicon nanowire transistor. We found how signal strength is determined and how intrinsic noise of the transistor determines signal-to-noise ratio of the recorded neural signals. This study provides in-depth understanding of the overall neural recording mechanism using silicon nanowire transistors and solid design guideline for further improvement and development.

Laser-Induced and MOF-Derived Metal Oxide/Carbon Composite for Synergistically Improved Ethanol Sensing at Room temperature.

Advancements in sensor technology have significantly enhanced atmospheric monitoring. Notably, metal oxide and carbon (MOx/C) hybrids have gained attention for their exceptional sensitivity and room-temperature sensing performance. However, previous methods of synthesizing MOx/C composites suffer from problems, including inhomogeneity, aggregation, and challenges in micropatterning. Herein, we introduce a refined method that employs a metal-organic framework (MOF) as a precursor combined with direct laser writing. The inherent structure of MOFs ensures a uniform distribution of metal ions and organic linkers, yielding homogeneous MOx/C structures. The laser processing facilitates precise micropatterning (< 2 µm, comparable to typical photolithography) of the MOx/C crystals. The optimized MOF-derived MOx/C sensor rapidly detected ethanol gas even at room temperature (105 and 18 s for response and recovery, respectively), with a broad range of sensing performance from 170 to 3,400 ppm and a high response value of up to 3,500%. Additionally, this sensor exhibited enhanced stability and thermal resilience compared to previous MOF-based counterparts. This research opens up promising avenues for practical applications in MOF-derived sensing devices.

Machine learning-based high-frequency neuronal spike reconstruction from low-frequency and low-sampling-rate recordings.

Recording neuronal activity using multiple electrodes has been widely used to understand the functional mechanisms of the brain. Increasing the number of electrodes allows us to decode more variety of functionalities. However, handling massive amounts of multichannel electrophysiological data is still challenging due to the limited hardware resources and unavoidable thermal tissue damage. Here, we present machine learning (ML)-based reconstruction of high-frequency neuronal spikes from subsampled low-frequency band signals. Inspired by the equivalence between high-frequency restoration and super-resolution in image processing, we applied a transformer ML model to neuronal data recorded from both in vitro cultures and in vivo male mouse brains. Even with the x8 downsampled datasets, our trained model reasonably estimated high-frequency information of spiking activity, including spike timing, waveform, and network connectivity. With our ML-based data reduction applicable to existing multichannel recording hardware while achieving neuronal signals of broad bandwidths, we expect to enable more comprehensive analysis and control of brain functions.

Semiconducting MOFs on ultraviolet laser-induced graphene with a hierarchical pore architecture for NO2 monitoring.

Due to rapid urbanization worldwide, monitoring the concentration of nitrogen dioxide (NO2), which causes cardiovascular and respiratory diseases, has attracted considerable attention. Developing real-time sensors to detect parts-per-billion (ppb)-level NO2 remains challenging due to limited sensitivity, response, and recovery characteristics. Herein, we report a hybrid structure of Cu3HHTP2, 2D semiconducting metal-organic frameworks (MOFs), and laser-induced graphene (LIG) for high-performance NO2 sensing. The unique hierarchical pore architecture of LIG@Cu3HHTP2 promotes mass transport of gas molecules and takes full advantage of the large surface area and porosity of MOFs, enabling highly rapid and sensitive responses to NO2. Consequently, LIG@Cu3HHTP2 shows one of the fastest responses and lowest limit of detection at room temperature compared with state-of-the-art NO2 sensors. Additionally, by employing LIG as a growth platform, flexibility and patterning strategies are achieved, which are the main challenges for MOF-based electronic devices. These results provide key insight into applying MOFtronics as high-performance healthcare devices.

High temporal resolution transparent thermoelectric temperature sensors for photothermal effect sensing.

We propose inkjet-printed high-speed and transparent temperature sensors based on the thermoelectric effect for direct monitoring of the photothermal effect. They consist of highly transparent organic thermoelectric materials that allow excellent biocompatibility and sub-ms temporal resolution, simultaneously. Our transparent thermoelectric temperature sensors can be used to advance various photothermal biomedical applications.

ReplaceNet: real-time replacement of a biological neural circuit with a hardware-assisted spiking neural network.

Recent developments in artificial neural networks and their learning algorithms have enabled new research directions in computer vision, language modeling, and neuroscience. Among various neural network algorithms, spiking neural networks (SNNs) are well-suited for understanding the behavior of biological neural circuits. In this work, we propose to guide the training of a sparse SNN in order to replace a sub-region of a cultured hippocampal network with limited hardware resources. To verify our approach with a realistic experimental setup, we record spikes of cultured hippocampal neurons with a microelectrode array (in vitro). The main focus of this work is to dynamically cut unimportant synapses during SNN training on the fly so that the model can be realized on resource-constrained hardware, e.g., implantable devices. To do so, we adopt a simple STDP learning rule to easily select important synapses that impact the quality of spike timing learning. By combining the STDP rule with online supervised learning, we can precisely predict the spike pattern of the cultured network in real-time. The reduction in the model complexity, i.e., the reduced number of connections, significantly reduces the required hardware resources, which is crucial in developing an implantable chip for the treatment of neurological disorders. In addition to the new learning algorithm, we prototype a sparse SNN hardware on a small FPGA with pipelined execution and parallel computing to verify the possibility of real-time replacement. As a result, we can replace a sub-region of the biological neural circuit within 22 µs using 2.5 × fewer hardware resources, i.e., by allowing 80% sparsity in the SNN model, compared to the fully-connected SNN model. With energy-efficient algorithms and hardware, this work presents an essential step toward real-time neuroprosthetic computation.

Inkjet-Printed Polyelectrolyte Seed Layer-Based, Customizable, Transparent, Ultrathin Gold Electrodes and Facile Implementation of Photothermal Effect.

Recently, interest in transparent electrodes has been increasing in biomedical engineering applications for such as electro-optical hybrid neuro-technologies. However, conventional photolithography-based electrode fabrication methods have limited design customization and large-area applicability. For biomedical engineering applications, it is crucial that we can easily customize the electrode design for different patients over a large body area. In this paper, we propose a novel method to fabricate customization-friendly, transparent, ultrathin, gold microelectrodes using inkjet printing technology. Unlike with typical direct printing of conductive inks, we inkjet-printed a polymer nucleation-inducing seed layer, followed by mask-less vacuum deposition of ultrathin gold (<6 nm) to produce selectively, high-transparency electrodes in the predefined shapes of the inkjet-printed polymer. Owing to the design flexibility of inkjet printing, the transparent ultrathin gold electrodes can be highly efficient in design customization over a large area. Simultaneously, a layer of nonconductive gold islands is formed in the nonprinted region, and this nanostructured layer can implement a photothermal effect that offers versatility for novel biomedical applications. As a demonstration of the effectiveness of these transparent electrodes, and the facile implementation of the photothermal effect for biomedical applications, we successfully fabricated transparent resistive temperature detectors. We used these to directly sense the photothermal effect and to demonstrate their bioimaging capabilities.

Hydrostatic optimization of inkjet-printed films.

In this work, we study the optimization of the geometry of inkjet-printed polymer films and develop a simple analytic framework to understand our results and establish limitations on inkjet-printed patterns. We show how drop spacing and ink concentration affect the thickness of a printed film and how hydrostatic conditions with contact angle hysteresis have to be considered to print optimized rectangular features. If advancing and receding contact angle are not taken into account, printed features will either bulge or break up into smaller beads. Thus, we provide a comprehensive analysis of the limits of film formation using regular assemblies of droplets.

Methodology for inkjet printing of partially wetting films.

Inkjet printing of precisely defined structures is critical for the realization of a range of printed electronics applications. We develop and demonstrate a methodology to optimize the inkjet printing of two-dimensional, partially wetting films. When printed inks have a positive retreating contact angle, we show that any fixed spacing is ineffective for printing two-dimensional features. With fixed spacing, the bead contact angle begins large, leading to a bulging overflow of its intended footprint. Each additional line reduces the bead contact angle, eventually leading to separation of the bead. We propose a printing scheme that adjusts the line-to-line spacing to maintain a bead's contact angle between its advancing and retreating values as it is printed. Implementing this approach requires an understanding of the two-dimensional bead surface and compensation for evaporation during the print. We derive an analytic equation for the bead's surface with pinned contact lines and use an empirical fit for mass loss due to evaporation. Finally, we demonstrate that enhanced contact angle hysteresis, achieved by preprinting a feature's border, leads to better corner definition.

Compact 256-channel multi-well microelectrode array system for in vitro neuropharmacology test.

Microelectrode arrays (MEAs) have been extensively used to measure extracellular spike activity from cultured neurons using multiple electrodes embedded in a planar glass substrate. This system has been implemented to investigate drug effects by detecting pharmacological perturbation reflected in spontaneous network activity. By configuring multiple wells in an MEA, a high-throughput electrophysiological assay has become available, speeding up drug tests. Despite its merits in acquiring massive amounts of electrophysiological data, the high cost and the bulky size of commercial multi-well MEA systems and most importantly its lack of customizability prevent potential users from fully implementing the system in drug experiments. In this work, we have developed a microelectrode array based drug testing platform by incorporating a custom-made compact 256-channel multi-well MEA in a standard microscope slide and commercial application-specific integrated circuit (ASIC) chip based recording system. We arranged 256 electrodes in 16 wells to maximize data collection from a single chip. The multi-well MEA in this work has a more compact design with reduced chip size compared to previously reported multi-well MEAs. Four synaptic modulators (NMDA, AMPA, bicuculline (BIC) and ATP) were applied to a multi-well MEA and neural spike activity was analyzed to study their neurophysiological effects on cultured neurons. Analyzing various neuropharmacological compounds has become much more accessible by utilizing commercially available digital amplifier chips and customizing a user-preferred analog-front-end interface design with additional benefits in reduced platform size and cost.

Thermoplasmonic Optical Fiber for Localized Neural Stimulation.

Thermoplasmonic effect-based neural stimulation has been suggested as an alternative optical neural stimulation technology without genetic modification. Integration of near-infrared light with plasmonic gold nanoparticles has been demonstrated as a neuromodulation tool on in vitro neuronal network models. In order to further test the validity of the thermoplasmonic neural stimulation across multiple biological models (in vitro, ex vivo, and in vivo) avoiding genetic modification in optical neuromodulation, versatile engineering approaches to apply the thermoplasmonic effect would be required. In this work, we developed a gold nanorod attached optical fiber technology for the localized neural stimulation based on a thermoplasmonic effect. A simple fabrication process was developed for efficient nanoparticle coating on commercial optical fibers. The thermoplasmonic optical fiber proved that it can locally modulate the neural activity in vitro. Lastly, we simulated the spatiotemporal temperature change by the thermoplasmonic optical fiber and analyzed its applicability to in vivo animal models.

Inkjet-Printed Multiwavelength Thermoplasmonic Images for Anticounterfeiting Applications.

Inkjet printing of thermoplasmonic nanoparticles enables instantaneous, large-area heat pattern generation upon light illumination from distance. By printing multiple metal nanoparticles of different shapes overlaid, we can fabricate multiwavelength thermoplasmonic images, which generate different heat patterns from a single printed image depending on the wavelength choice of light. In this work, we propose a novel multiwavelength thermoplasmonic image printing process that can be used for anticounterfeit technology. With this technology, "printed thermoplasmonic labels" allow fully secured anticounterfeit inspection procedure. Input stimulus of near-infrared or infrared light illumination and output signal reading of thermal patterns can be both completely invisible. Wavelength selective photothermal effect also enables the encryption of the contained information, which adds more complexity and thus higher security.

Thermo-plasmonic gold nanofilms for simple and mass-producible photothermal neural interfaces.

In recent years, photothermal stimulation methods using plasmonic metal nanoparticles have emerged as non-genetic optical techniques in neuromodulation. Although nanoparticle-based photothermal stimulation shows great potential in the excitation and the inhibition of neural activity, the complex synthesis processes of the nanoparticles and the lack of large-area deposition methods can be limiting factors for the development of photothermal neural devices. In this paper, we propose a plasmonic gold nanofilm, fabricated by a standard thermal evaporation process, as a simple and mass-producible photothermal neural interface layer for microelectrode array (MEA) chips. The absorption of the gold nanofilm at near infrared wavelengths is optimized to maximize the photothermal effect by varying the thickness and microstructure of the gold nanofilm. With the optimized conditions, a significantly strong photothermal effect is applied on MEAs without affecting the neural signal recording capability. Finally, primary rat hippocampal neuronal cultures are used to show that the photothermal neural inhibition using the gold nanofilm is as effective as that using the plasmonic nanoparticles. Due to the greater simplicity and versatility of the fabrication process, the plasmonic gold nanofilm can provide a promising solution for the mass production of photothermal platforms.

Inkjet-Printed Biofunctional Thermo-Plasmonic Interfaces for Patterned Neuromodulation.

Localized heat generation by the thermo-plasmonic effect of metal nanoparticles has great potential in biomedical engineering research. Precise patterning of the nanoparticles using inkjet printing can enable the application of the thermo-plasmonic effect in a well-controlled way (shape and intensity). However, a universally applicable inkjet printing process that allows good control in patterning and assembly of nanoparticles with good biocompatibility is missing. Here we developed inkjet-printing-based biofunctional thermo-plasmonic interfaces that can modulate biological activities. We found that inkjet printing of plasmonic nanoparticles on a polyelectrolyte layer-by-layer substrate coating enables high-quality, biocompatible thermo-plasmonic interfaces across various substrates (rigid/flexible, hydrophobic/hydrophilic) by induced contact line pinning and electrostatically assisted nanoparticle assembly. We experimentally confirmed that the generated heat from the inkjet-printed thermo-plasmonic patterns can be applied in micrometer resolution over a large area. Lastly, we demonstrated that the patterned thermo-plasmonic effect from the inkjet-printed gold nanorods can selectively modulate neuronal network activities. This inkjet printing process therefore can be a universal method for biofunctional thermo-plasmonic interfaces in various bioengineering applications.

Digital micromirror based near-infrared illumination system for plasmonic photothermal neuromodulation.

Light-mediated neuromodulation techniques provide great advantages to investigate neuroscience due to its high spatial and temporal resolution. To generate a spatial pattern of neural activity, it is necessary to develop a system for patterned-light illumination to a specific area. Digital micromirror device (DMD) based patterned illumination system have been used for neuromodulation due to its simple configuration and design flexibility. In this paper, we developed a patterned near-infrared (NIR) illumination system for region specific photothermal manipulation of neural activity using NIR-sensitive plasmonic gold nanorods (GNRs). The proposed system had high power transmission efficiency for delivering power density up to 19 W/mm2. We used a GNR-coated microelectrode array (MEA) to perform biological experiments using E18 rat hippocampal neurons and showed that it was possible to inhibit neural spiking activity of specific area in neural circuits with the patterned NIR illumination. This patterned NIR illumination system can serve as a promising neuromodulation tool to investigate neuroscience in a wide range of physiological and clinical applications.

Transparent high-performance thin film transistors from solution-processed SnO2 /ZrO2 gel-like precursors.

This work employs novel SnO(2) gel-like precursors in conjunction with sol-gel deposited ZrO(2) gate dielectrics to realize high-performance transparent transistors. Representative devices show excellent performance and transparency, and deliver mobility of 103 cm(2) V(-1) s(-1) in saturation at operation voltages as low as 2 V, a sub-threshold swing of only 0.3 V/decade, and /(on) //(off) of 10(4) ~10(5) .