Spike timing-based coding in neuromimetic tactile system enables dynamic object classification.

Rapid processing of tactile information is essential to human haptic exploration and dexterous object manipulation. Conventional electronic skins generate frames of tactile signals upon interaction with objects. Unfortunately, they are generally ill-suited for efficient coding of temporal information and rapid feature extraction. In this work, we report a neuromorphic tactile system that uses spike timing, especially the first-spike timing, to code dynamic tactile information about touch and grasp. This strategy enables the system to seamlessly code highly dynamic information with millisecond temporal resolution on par with the biological nervous system, yielding dynamic extraction of tactile features. Upon interaction with objects, the system rapidly classifies them in the initial phase of touch and grasp, thus paving the way to fast tactile feedback desired for neuro-robotics and neuro-prosthetics.

Brownian Motion Paving the Way for Molecular Translocation in Nanopores.

Tracing fast nanopore-translocating analytes requires a high-frequency measurement system that warrants a temporal resolution better than 1 µs. This constraint may practically shift the challenge from increasing the sampling bandwidth to dealing with the rapidly growing noise with frequencies typically above 10 kHz, potentially making it still uncertain if all translocation events are unambiguously captured. Here, a numerical simulation model is presented as an alternative to discern translocation events with different experimental settings including pore dimension, bias voltage, the charge state of the analyte, salt concentration, and electrolyte viscosity. The model allows for simultaneous analysis of forces exerting on a large analyte cohort along their individual trajectories; these forces are responsible for the analyte movement leading eventually to the nanopore translocation. Through tracing the analyte trajectories, the Brownian force is found to dominate the analyte movement in electrolytes until the last moment at which the electroosmotic force determines the final translocation act. The mean dwell time of analytes mimicking streptavidin decreases from ≈6 to ≈1 µs with increasing the bias voltage from ±100 to ±500 mV. The simulated translocation events qualitatively agree with the experimental data with streptavidin. The simulation model is also helpful for the design of new solid-state nanopore sensors.

Plasmon-Enhanced Fluorescence of Single Quantum Dots Immobilized in Optically Coupled Aluminum Nanoholes.

Fluorescence-based optical sensing techniques have continually been explored for single-molecule detection targeting myriad biomedical applications. Improving signal-to-noise ratio remains a prioritized effort to enable unambiguous detection at single-molecule level. Here, we report a systematic simulation-assisted optimization of plasmon-enhanced fluorescence of single quantum dots based on nanohole arrays in ultrathin aluminum films. The simulation is first calibrated by referring to the measured transmittance in nanohole arrays and subsequently used for guiding their design. With an optimized combination of nanohole diameter and depth, the variation of the square of simulated average volumetric electric field enhancement agrees excellently with that of experimental photoluminescence enhancement over a large range of nanohole periods. A maximum 5-fold photoluminescence enhancement is statistically achieved experimentally for the single quantum dots immobilized at the bottom of simulation-optimized nanoholes in comparison to those cast-deposited on bare glass substrate. Hence, boosting photoluminescence with optimized nanohole arrays holds promises for single-fluorophore-based biosensing.

A Generalized Transformer-Based Pulse Detection Algorithm.

Pulse-like signals are ubiquitous in the field of single molecule analysis, e.g., electrical or optical pulses caused by analyte translocations in nanopores. The primary challenge in processing pulse-like signals is to capture the pulses in noisy backgrounds, but current methods are subjectively based on a user-defined threshold for pulse recognition. Here, we propose a generalized machine-learning based method, named pulse detection transformer (PETR), for pulse detection. PETR determines the start and end time points of individual pulses, thereby singling out pulse segments in a time-sequential trace. It is objective without needing to specify any threshold. It provides a generalized interface for downstream algorithms for specific application scenarios. PETR is validated using both simulated and experimental nanopore translocation data. It returns a competitive performance in detecting pulses through assessing them with several standard metrics. Finally, the generalization nature of the PETR output is demonstrated using two representative algorithms for feature extraction.

Docking and Activity of DNA Polymerase on Solid-State Nanopores.

Integration of motor enzymes with biological nanopores has enabled commercial DNA sequencing technology; yet studies of the similar principle applying to solid-state nanopores are limited. Here, we demonstrate the real-life monitoring of phi29 DNA polymerase (DNAP) docking onto truncated-pyramidal nanopore (TPP) arrays through both electrical and optical readout. To achieve effective docking, atomic layer deposition of hafnium oxide is employed to reduce the narrowest pore opening size of original silicon (Si) TPPs to sub-10 nm. On a single TPP with pore opening size comparable to DNAP, ionic current measurements show that a polymerase-DNA complex can temporally dock onto the TPP with a certain docking orientation, while the majority become translocation events. On 5-by-5 TPP arrays, a label-free optical detection method using Ca2+ sensitive dye, are employed to detect the docking dynamics of DNAP. The results show that this label-free detection strategy is capable of accessing the docking events of DNAP on TPP arrays. Finally, we examine the activity of docked DNAP by performing on-site rolling circle amplification to synthesize single-stranded DNA (ssDNA), which serves as a proof-of-concept demonstration of utilizing this docking scheme for emerging nanopore sensing applications.

Self-Limited Formation of Bowl-Shaped Nanopores for Directional DNA Translocation.

Solid-state nanopores of on-demand dimensions and shape can facilitate desired sensor functions. However, reproducible fabrication of arrayed nanopores of predefined dimensions remains challenging despite numerous techniques explored. Here, bowl-shaped nanopores combining properties of ultrathin membrane and tapering geometry are manufactured using a self-limiting process developed on the basis of standard silicon technology. The upper opening of the bowl-nanopores is 60-120 nm in diameter, and the bottom orifice reaches sub-5 nm. Current-voltage characteristics of the fabricated bowl-nanopores display insignificant rectification indicating weak ionic selectivity, in accordance to numerical simulations showing minor differences in electric field and ionic velocity upon the reversal of bias voltages. Simulations reveal, concomitantly, high-momentum electroosmotic flow downward along the concave nanopore sidewall. Collisions between the left and right tributaries over the bottom orifice drive the electroosmotic flow both up into the nanopore and down out of the nanopore through the orifice. The resultant asymmetry in electrophoretic-electroosmotic force is considered the cause responsible for the experimentally observed strong directionality in λ-DNA translocation with larger amplitude, longer duration, and higher frequencies for the downward movements from the upper opening than the upward ones from the orifice. Thus, the resourceful silicon nanofabrication technology is shown to enable nanopore designs toward enriching sensor applications.

A Guide to Signal Processing Algorithms for Nanopore Sensors.

Nanopore technology holds great promise for a wide range of applications such as biomedical sensing, chemical detection, desalination, and energy conversion. For sensing performed in electrolytes in particular, abundant information about the translocating analytes is hidden in the fluctuating monitoring ionic current contributed from interactions between the analytes and the nanopore. Such ionic currents are inevitably affected by noise; hence, signal processing is an inseparable component of sensing in order to identify the hidden features in the signals and to analyze them. This Guide starts from untangling the signal processing flow and categorizing the various algorithms developed to extracting the useful information. By sorting the algorithms under Machine Learning (ML)-based versus non-ML-based, their underlying architectures and properties are systematically evaluated. For each category, the development tactics and features of the algorithms with implementation examples are discussed by referring to their common signal processing flow graphically summarized in a chart and by highlighting their key issues tabulated for clear comparison. How to get started with building up an ML-based algorithm is subsequently presented. The specific properties of the ML-based algorithms are then discussed in terms of learning strategy, performance evaluation, experimental repeatability and reliability, data preparation, and data utilization strategy. This Guide is concluded by outlining strategies and considerations for prospect algorithms.

Deep Learning of Nanopore Sensing Signals Using a Bi-Path Network.

Temporal changes in electrical resistance of a nanopore sensor caused by translocating target analytes are recorded as a sequence of pulses on current traces. Prevalent algorithms for feature extraction in pulse-like signals lack objectivity because empirical amplitude thresholds are user-defined to single out the pulses from the noisy background. Here, we use deep learning for feature extraction based on a bi-path network (B-Net). After training, the B-Net acquires the prototypical pulses and the ability of both pulse recognition and feature extraction without a priori assigned parameters. The B-Net is evaluated on simulated data sets and further applied to experimental data of DNA and protein translocation. The B-Net results are characterized by small relative errors and stable trends. The B-Net is further shown capable of processing data with a signal-to-noise ratio equal to 1, an impossibility for threshold-based algorithms. The B-Net presents a generic architecture applicable to pulse-like signals beyond nanopore currents.

Surfactant-Free Stabilization of Aqueous Graphene Dispersions Using Starch as a Dispersing Agent.

Attention to graphene dispersions in water with the aid of natural polymers is increasing with improved awareness of sustainability. However, the function of biopolymers that can act as dispersing agents in graphene dispersions is not well understood. In particular, the use of starch to disperse pristine graphene materials deserves further investigation. Here, we report the processing conditions of aqueous graphene dispersions using unmodified starch. We have found that the graphene content of the starch-graphene dispersion is dependent on the starch fraction. The starch-graphene sheets are few-layer graphene with a lateral size of 3.2 µm. Furthermore, topographical images of these starch-graphene sheets confirm the adsorption of starch nanoparticles with a height around 5 nm on the graphene surface. The adsorbed starch nanoparticles are ascribed to extend the storage time of the starch-graphene dispersion up to 1 month compared to spontaneous aggregation in a nonstabilized graphene dispersion without starch. Moreover, the ability to retain water by starch is reduced in the presence of graphene, likely due to environmental changes in the hydroxyl groups responsible for starch-water interactions. These findings demonstrate that starch can disperse graphene with a low oxygen content in water. The aqueous starch-graphene dispersion provides tremendous opportunities for environmental-friendly packaging applications.

SCN11A gene deletion causes sensorineural hearing loss by impairing the ribbon synapses and auditory nerves.

BACKGROUND: The SCN11A gene, encoded Nav1.9 TTX resistant sodium channels, is a main effector in peripheral inflammation related pain in nociceptive neurons. The role of SCN11A gene in the auditory system has not been well characterized. We therefore examined the expression of SCN11A in the murine cochlea, the morphological and physiological features of Nav1.9 knockout (KO) ICR mice. RESULTS: Nav1.9 expression was found in the primary afferent endings beneath the inner hair cells (IHCs). The relative quantitative expression of Nav1.9 mRNA in modiolus of wild-type (WT) mice remains unchanged from P0 to P60. The number of presynaptic CtBP2 puncta in Nav1.9 KO mice was significantly lower than WT. In addition, the number of SGNs in Nav1.9 KO mice was also less than WT in the basal turn, but not in the apical and middle turns. There was no lesion in the somas and stereocilia of hair cells in Nav1.9 KO mice. Furthermore, Nav1.9 KO mice showed higher and progressive elevated ABR threshold at 16 kHz, and a significant increase in CAP thresholds. CONCLUSIONS: These data suggest a role of Nav1.9 in regulating the function of ribbon synapses and the auditory nerves. The impairment induced by Nav1.9 gene deletion mimics the characters of cochlear synaptopathy.

Dynamics of DNA Clogging in Hafnium Oxide Nanopores.

Interfacing solid-state nanopores with biological systems has been exploited as a versatile analytical platform for analysis of individual biomolecules. Although clogging of solid-state nanopores due to nonspecific interactions between analytes and pore walls poses a persistent challenge in attaining the anticipated sensing efficacy, insufficient studies focus on elucidating the clogging dynamics. Herein, we investigate the DNA clogging behavior by passing double-stranded (ds) DNA molecules of different lengths through hafnium oxide(HfO2)-coated silicon (Si) nanopore arrays, at different bias voltages and electrolyte pH values. Employing stable and photoluminescent-free HfO2/Si nanopore arrays permits a parallelized visualization of DNA clogging with confocal fluorescence microscopy. We find that the probability of pore clogging increases with both DNA length and bias voltage. Two types of clogging are discerned: persistent and temporary. In the time-resolved analysis, temporary clogging events exhibit a shorter lifetime at higher bias voltage. Furthermore, we show that the surface charge density has a prominent effect on the clogging probability because of electrostatic attraction between the dsDNA and the HfO2 pore walls. An analytical model based on examining the energy landscape along the DNA translocation trajectory is developed to qualitatively evaluate the DNA-pore interaction. Both experimental and theoretical results indicate that the occurrence of clogging is strongly dependent on the configuration of translocating DNA molecules and the electrostatic interaction between DNA and charged pore surface. These findings provide a detailed account of the DNA clogging phenomenon and are of practical interest for DNA sensing based on solid-state nanopores.

On Induced Surface Charge in Solid-State Nanopores.

Solid-state nanopores constitute a versatile platform for study of ion transport in nanoconfinement. The electrical double layer (EDL) plays a vital role in such nanoconfinements, but effects of induced surface charge on the EDL in the presence of an external transmembrane electric field are yet to be characterized. Here, the formation of induced charge on the nanopore sidewall surface and its effects, via modulation of the EDL and electroosmotic flow, on the ionic current are elucidated using a novel experimental setup with solid-state truncated-pyramidal nanopores. This study consists of three complementary approaches, i.e., an analytical model for induced surface charge, numerical simulation of induced surface charge, electroosmotic flow, and ionic current, and experimental validation with respect to the ionic current. The induced surface charge is generated by polarization in the dielectric membrane as a response to the applied electric field. This charge generation results in a nonuniform density of surface charge along the nanopore sidewall. It further causes ions in the electrolyte to redistribute, leading to a massive accumulation of single-polarity ions in the EDL and their counterions near the smaller opening of the nanopore. It also alters electrohydrodynamic properties in the nanopore, giving rise to the formation of electroosmotic vortexes in the vicinity of the smaller opening of the nanopore. Finally, the pattern of the electroosmotic flow can significantly influence the transport properties of the nanopore.

Synergy of Ionic and Dipolar Effects by Molecular Design for pH Sensing beyond the Nernstian Limit.

Knowledge of interfacial interactions between analytes and functionalized sensor surfaces, from where the signal originates, is key to the development and application of electronic sensors. The present work explores the tunability of pH sensitivity by the synergy of surface charge and molecular dipole moment induced by interfacial proton interactions. This synergy is demonstrated on a silicon-nanoribbon field-effect transistor (SiNR-FET) by functionalizing the sensor surface with properly designed chromophore molecules. The chromophore molecules can interact with protons and lead to appreciable changes in interface dipole moment as well as in surface charge state. In addition, the dipole moment can be tuned not only by the substituent on the chromophore but also by the anion in the electrolyte interacting with the protonated chromophore. By designing surface molecules to enhance the surface dipole moment upon protonation, an above-Nernstian pH sensitivity is achieved on the SiNR-FET sensor. This finding may bring an innovative strategy for tailoring the sensitivity of the SiNR-FET-based pH sensor toward a wide range of applications.

Mechanism and Kinetics of Lipid Bilayer Formation in Solid-State Nanopores.

Solid-state nanopores provide a highly versatile platform for rapid electrical detection and analysis of single molecules. Lipid bilayer coating of the nanopores can reduce nonspecific analyte adsorption to the nanopore sidewalls and increase the sensing selectivity by providing possibilities for tethering specific ligands in a cell-membrane mimicking environment. However, the mechanism and kinetics of lipid bilayer formation from vesicles remain unclear in the presence of nanopores. In this work, we used a silicon-based, truncated pyramidal nanopore array as the support for lipid bilayer formation. Lipid bilayer formation in the nanopores was monitored in real time by the change in ionic current through the nanopores. Statistical analysis revealed that a lipid bilayer is formed from the instantaneous rupture of individual vesicle upon adsorption in the nanopores, differing from the generally agreed mechanism that lipid bilayer forms at a high vesicle surface coverage on a planar support. The dependence of the lipid bilayer formation process on the applied bias, vesicle size, and concentration was systematically studied. In addition, the nonfouling properties of the lipid bilayer coated nanopores were demonstrated during long single-stranded DNA translocation through the nanopore array. The findings indicate that the lipid bilayer formation process can be modulated by introducing nanocavities intentionally on the planar surface to create active sites or changing the vesicle size and concentration.

On Rectification of Ionic Current in Nanopores.

Rectification of ionic current, a frequently observed phenomenon with asymmetric nanopores varying in geometry and/or surface charge, has been utilized for studies of microfluidic circuits, nanopore sensors, and energy conversion devices. However, the physics behind the rectification phenomenon deserves further analysis, and the involved processes need renewed organization; however, the origin is known, and numerous simulations based on the Poisson-Nernst-Planck formalism provide details of the observation. Here, we present an analytical model by identifying the causal chain connecting the key physical factors and processes leading to rectification: the charge present on the pore sidewalls causing the selectivity of ion fluxes through the pore, the selectivity inducing enrichment-depletion of ions around the pore, and the established ion concentration gradient rendering the electric field redistribution in the pore. Our analytical model that considers nanopore geometry, surface charge density, and electrolyte concentration calculates the ionic current and corresponding rectification factor at given bias voltages. The model is validated by numerical simulations, and the model results agree well with experimental data. It is, therefore, a useful tool not only for gaining physical insights into ionic current rectification but also for providing practical guidelines in designing nanopore- and nanopipette-based ion sensors for a range of applications.

Rectification of protein translocation in truncated pyramidal nanopores.

Solid-state nanopore technology presents an emerging single-molecule-based analytical tool for the separation and analysis of nanoparticles. Different approaches have been pursued to attain the anticipated detection performance. Here, we report the rectification behaviour of protein translocation through silicon-based truncated pyramidal nanopores. When the size of translocating proteins is comparable to the smallest physical constriction of the nanopore, the frequency of translocation events observed is lower for proteins that travel from the larger to the small opening of the nanopore than for those that travel in the reverse direction. When the proteins are appreciably smaller than the nanopore, an opposite rectification in the frequency of translocation events is evident. The maximum rectification factor achieved is around ten. Numerical simulations reveal the formation of an electro-osmotic vortex in such asymmetric nanopores. The vortex-protein interaction is found to play a decisive role in rectifying the translocation in terms of polarity and amplitude. The reported phenomenon can be potentially exploitable for the discrimination of various nanoparticles.

Controlled size reduction and its underlying mechanism to form solid-state nanopores via electron beam induced carbon deposition.

Solid-state nanopores have drawn considerable attention for their potential applications in DNA sequencing and nanoparticle analysis. However, fabrication of nanopores, especially those of diameter below 30 nm, requires sophisticated techniques. Here, a versatile method to controllably reduce the diameter of prefabricated large-size pores down to sub-30 nm without greatly increasing the effective pore depth from the original membrane thickness is shown. This method exploits carbon deposition achieved via hydrocarbon evaporation, induced by an incident beam of electrons, and subsequent dissociation of hydrocarbon to solid carbon deposits. The carbon deposition employs a conventional scanning electron microscope equipped with direct visual feedback, along with a stable hydrocarbon source nearby the sample. This work systematically studies how electron beam accelerating voltage, imaging magnification, initial pore size and membrane composition affect the process of pore size reduction. Secondary electrons generated in the membrane material are confirmed to be the main cause of the dissociation of hydrocarbon. Thicker carbon deposited on one side than on the other of the membrane results in an asymmetric nanopore shape and a rectifying ionic transport. A physico-phenomenological model combined with Monte Carlo simulations is proposed to account for the observed carbon deposition behaviors.

Device Noise Reduction for Silicon Nanowire Field-Effect-Transistor Based Sensors by Using a Schottky Junction Gate.

The sensitivity of metal oxide semiconductor field-effect transistor (MOSFET) based nanoscale sensors is ultimately limited by noise induced by carrier trapping/detrapping processes at the gate oxide/semiconductor interfaces. We have designed a Schottky junction gated silicon nanowire field-effect transistor (SiNW-SJGFET) sensor, where the Schottky junction replaces the noisy oxide/semiconductor interface. Our sensor exhibits significantly reduced device noise, 2.1 × 10-9 V2 µm2/Hz at 1 Hz, compared to reference devices with the oxide/semiconductor interface operated at both inversion and depletion modes. Further improvement can be anticipated by wrapping the nanowire by such a Schottky junction, thereby eliminating all oxide/semiconductor interfaces. Hence, a combination of the low-noise SiNW-SJGFET device with a sensing surface of the Nernstian response limit holds promises for future high signal-to-noise ratio sensor applications.

Dramatically Enhanced Broadband Photodetection by Dual Inversion Layers and Fowler-Nordheim Tunneling.

Silicon photonics is now widely accepted as a key technology in a variety of systems. But owing to material limitations, now it is challenging to greatly improve the performance after decades of development. Here, we show a high-performance broadband photodetector with significantly enhanced sensitivity and responsivity operating over a wide wavelength range of light from near-ultraviolet to near-infrared at low power consumption. The specially designed textured top ceiling electrode works effectively as an antireflection layer to greatly improve the absorption of near-infrared light, thereby overcoming the absorption limitation of near-infrared light. Instead of the conventional p-n junction and p-intrinsic-n junction, we introduce a ∼15 nm thick alumina insulator layer between a p-type Si substrate and n-type ZnO nanowire (NW) arrays, which significantly enhances the charge carrier separation and collection efficiency. The photosensing responsivity and sensitivity are found to be nearly 1 order of magnitude higher than that of a reference device of p-Si/n-ZnO NW arrays, significantly higher than the commercial silicon photodiodes as well. The light-induced charge carriers flow across the appropriate thickness of insulator layer via the quantum mechanical Fowler-Nordheim tunneling mechanism. By virtue of the piezo-phototronic effect, the charge density at the interfaces can be tuned to alter the energy bands and the potential barrier distance for tunneling. Additionally, along with the use of incident light of different wavelengths, the influence of the insulator layer on the transport of electrons and holes separately is further investigated. The demonstrated concepts and study would lead to sensitivity improvement, quality enhancement of data transfer, decrease of power consumption, and cost reduction of silicon photonics.

A Sequential Process of Graphene Exfoliation and Site-Selective Copper/Graphene Metallization Enabled by Multifunctional 1-Pyrenebutyric Acid Tetrabutylammonium Salt.

This paper reports a procedure leading to shear exfoliation of pristine few-layer graphene flakes in water and subsequent site-selective formation of Cu/graphene films on polymer substrates, both of which are enabled by employing the water soluble 1-pyrenebutyric acid tetrabutylammonium salt (PyB-TBA). The exfoliation with PyB-TBA as an enhancer leads to as-deposited graphene films dried at 90 °C that are characterized by electrical conductivity of ∼110 S/m. Owing to the good affinity of the tetrabutylammonium cations to the catalyst PdCl42-, electroless copper deposition selectively in the graphene films is initiated, resulting in a self-aligned formation of highly conductive Cu/graphene films at room temperature. The excellent solution-phase and low-temperature processability, self-aligned copper growth, and high electrical conductivity of the Cu/graphene films have permitted fabrication of several electronic circuits on plastic foils, thereby indicating their great potential in compliant, flexible, and printed electronics.