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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.

Nanopore technology is widely used for sequencing DNA, RNA, and peptides with single-molecule resolution, for fingerprinting single proteins, and for detecting metabolites. However, the molecular driving forces controlling the analyte capture, its residence time, and its escape have remained incompletely understood. The recently developed Nanopore Electro-Osmotic trap (NEOtrap) is well fit to study these basic physical processes in nanopore sensing, as it reveals previously missed events. Here, we use the NEOtrap to quantitate the electro-osmotic and electrophoretic forces that act on proteins inside the nanopore. We establish a physical model to describe the capture and escape processes, including the trapping energy potential. We verified the model with experimental data on CRISPR dCas9-RNA-DNA complexes, where we systematically screened crucial modeling parameters such as the size and net charge of the complex. Tuning the balance between electrophoretic and electro-osmotic forces in this way, we compare the trends in the kinetic parameters with our theoretical models. The result is a comprehensive picture of the major physical processes in nanopore trapping, which helps to guide the experiment design and signal interpretation in nanopore experiments.

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.

Nanopores are versatile single-molecule sensors offering a simple label-free readout with great sensitivity. We recently introduced the nanopore electro-osmotic trap (NEOtrap) which can trap and sense single unmodified proteins for long times. The trapping is achieved by the electro-osmotic flow (EOF) generated from a DNA-origami sphere docked onto the pore, but thermal fluctuations of the origami limited the trapping of small proteins. Here, we use site-specific cholesterol functionalization of the origami sphere to firmly link it to the lipid-coated nanopore. We can lock the origami in either a vertical or horizontal orientation which strongly modulates the EOF. The optimized EOF greatly enhances the trapping capacity, yielding reduced noise, reduced measurement heterogeneity, an increased capture rate, and 100-fold extended observation times. We demonstrate the trapping of a variety of single proteins, including small ones down to 14 kDa. The cholesterol functionalization significantly expands the application range of the NEOtrap technology.

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.

Conductive hydrogels have been studied as promising materials for the flexible and wearable bioelectronics, because of their unique electrical and mechanical properties. Addition of conducting polymers in biomaterial-based hydrogel matrix is a simple yet effective way to construct hydrogels with good conductivity and flexibility. In this work, a conductive hydrogel composed by a silk hydrogel and a conducting polymer, polypyrrole (PPy), is developed via in situ polymerization of pyrrole into the silk fibroin network. The silk-PPy hydrogel shows high conductivity (26 S m(-1)), as well as sensitive and fast responses to corresponding conformation changes. Taking advantages of these properties, flexible and wearable strain sensors are proposed for the monitoring of various body movements, which can detect both the large and subtle human motions with good sensitivity, reproducibility and stability. The hybridization of biomaterials and conducting polymers endows the multifunctions of the conductive hydrogels, thus showing considerable potentials in the advancement of the wearable electronics.

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.

Source data used in the manuscript: Orientation-locked DNA origami improves single-protein trapping in the NEOtrap The measurements were implemented in 600 KHM buffer under the bias voltage of 100 mV. Names of these files specify the trapped protein's name with corresponding measurement conditions, i.e., bare origami sphere, Cholesterol functionalized sphere in vertical configuration, and Cholesterol functionalized sphere in horizontal configuration.

Solid-state nanopore (SSNP) technology presents an emerging single-molecule based analytical tool for separation and analysis of biomolecules or nanoparticles. Different prominent approaches have been pursued to attain the anticipated detection performance: process innovation to achieve pore size matching the physical dimensions of biomolecules so as to boost signal; electrolyte management to control translocation speed so as to improve signal quality; surface functionalisation to amplify molecular differences so as to enhance specificity; and implementation of additional, complementary means, such as optical, to manipulate the translocation so as to increase data fidelity. This review focuses on the fundamentals pertaining to the physical processes involved in nanopore sensing based on SSNPs of distinct shapes. It also provides a comprehensive picture regarding challenges and development trends in putting nanopore-based molecular sensors in use. This effort is facilitated by establishing physical-phenomenological models supported by experiment and numerical simulation. To assist the readership, the discussion starts from relatively simple cases and then develops towards complex systems, i.e. from open-pore state to analyte translocation and from single pores to pore arrays. Key physical parameter threading through these aspects is effective transport length that is simple to perceive and easy to calculate.

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.

Surface states of mesoporous NiO semiconductor films have particular properties differing from the bulk and are able to dramatically influence the interfacial electron transfer and adsorption of chemical species. To achieve a better performance of NiO-based p-type dye-sensitized solar cells (p-DSCs), the function of the surface states has to be understood. In this paper, we applied a modified atomic layer deposition procedure that is able to passivate 72% of the surface states on NiO by depositing a monolayer of Al2O3. This provides us with representative control samples to study the functions of the surface states on NiO films. A main conclusion is that surface states, rather than the bulk, are mainly responsible for the conductivity in mesoporous NiO films. Furthermore, surface states significantly affect dye regeneration (with I–/I3– as redox couple) and hole transport in NiO-based p-DSCs. A new dye regeneration mechanism is proposed in which electrons are transferred from reduced dye molecules to intra-bandgap states, and then to I3– species. The intra-bandgap states here act as catalysts to assist I3– reduction. A more complete mechanism is suggested to understand the particular hole transport behavior in p-DSCs, in which the hole transport time is independent of light intensity. This is ascribed to the percolation hole hopping on the surface states. When the concentration of surface states was significantly reduced, the light-independent charge transport behavior in pristine NiO-based p-DSCs transformed into having an exponential dependence on light intensity, similar to that observed in TiO2-based n-type DSCs. These conclusions on the function of surface states provide new insight into the electronic properties of mesoporous NiO films.

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.

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.

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.

Hysteresis is a frequently observed phenomenon in the transfer characteristics of thin film transistors. Charge trapping/de-trapping processes of gate oxide and gate-channel interface are commonly known to be the origin of hysteresis and correlated to low frequency noise (LFN) properties of the devices. In this letter, a rapid four-point sweeping method (RFSM) is proposed to reveal the dependence of hysteresis, as well as the distribution of effective trap density on sweeping rate and gate bias range. Based on the RFSM, the hysteresis properties of four-layer MoS2 FETs are studied in detail. The experimental results demonstrate that the hysteresis and trap density at different frequencies and gate voltages, which could further roughly map the traps with different time constants and energy depths, can be obtained by the simple RFSM. Trap density estimated by RFSM shows a comparable range with that extracted from LFN, indicating that the traps inducing the hysteresis may also cause LFN.

Solid-state nanopores (SSN) are of significant potential as a versatile tool for chemical sensing, biomolecule inspection, nanoparticle detection, etc. High throughput characterization of SSN in an arrayed format is highly desired for a wide range of applications. Herein, we demonstrate a novel design to integrate an SSN array with microfluidics and a multiplexer. Ionic current measurement on each nanopore can then be individually addressed fluidically and/or electrically with minimum cross talk (electric leakage). This integration provides a scalable platform for automated high-throughput, low-cost, and rapid electrical characterization potentially of a large number of SSN.

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.