Non-volatile memories based on patterned metal–semiconductor heterostructures of niobium disulfide and molybdenum disulfide

Z. Wang; G. Migliato Marega; E. Collette; M. Tripathi; H. G. Ji et al. 

The performance of transistors based on two-dimensional transition metal dichalcogenide semiconductors is restricted by the poor interface quality between two-dimensional materials and conventional three-dimensional contacts. Transition-metal-dichalcogenide-based metal–semiconductor heterostructures have been developed to enhance device performance, but finding fabrication techniques that combine high-quality growth with scalability and broad applicability remains a challenge. Here we show that a method that combines metal–organic chemical vapour deposition and sulfurization can be used to create patterned heterostructures of niobium disulfide and molybdenum disulfide at the wafer scale. The niobium disulfide–molybdenum disulfide heterostructures can be used as the active channel material of field-effect transistors and non-volatile memory devices. Compared with pristine molybdenum disulfide, the heterostructures exhibit up to nine times higher on current due to a reduced contact resistance, a maximum effective mobility of 77 cm2 V−1 s−1 and a 95.8% yield (of 144 field-effect transistors). Furthermore, our floating-gate field-effect transistors show a large programming window, precise and continuous conductance modulation, endurance over 60,000 programming pulses and an estimated retention time of around 19 years. Device simulation shows that the large programming window of the long-channel devices (around 14 V) can be maintained at scaled gate lengths below 100 nm with proper control oxide scaling.

Isotopic Fingerprints of Proton-Mediated Dielectric Relaxation in Solid and Liquid Water

A. Ryzhov; A. Andreev; A. Radenovic; V. Artemov 

We report cross-validated measurements of the isotope effect on dielectric relaxation for four isotopologues of ice and water, including the 1–105 Hz region, in which only sporadic and inconsistent measurements were previously available. In ice, the relaxation rates exhibit an activated temperature dependence with an isotope-independent activation energy. Across 248–273 K, the H2O-to-D2O relaxation rate ratio remains constant at 2.0±0.1. This scaling agrees with Kramers’ theory in the high-friction limit if the moving mass is the proton or deuteron, indicating that dielectric relaxation is governed by a classic proton transfer over an energy barrier rather than molecular reorientation.

Charge and slip-length optimization in lipid-bilayer-coated nanofluidics for enhanced osmotic energy harvesting

Y. Teng; T. Chen; N. Cai; P. Saud; H. Xu et al. 

Optical Sensing with Defects in Two-Dimensional Materials

Nanopore Trap for Label‐Free Fingerprinting of Surface‐modified Single Nanoparticles

N. Cai; T. Chen; Y. Teng; A. S. Naidu; A. Radenovic 

Label‐free characterization of nanoparticle surface functionalization at single‐particle resolution is essential for a wide range of applications. Solid‐state nanopore sensing provides a direct electrical readout that is intrinsically sensitive to the size, surface layer, and interfacial chemistry of single particles in liquid environments. The trapping‐based nanopore sensing regime further enables probing surface‐dependent particle‐pore interactions with extended observation time. Here, a solid‐state nanopore trap‐based fingerprinting method is presented to differentiate single nanoparticles with distinct surface modifications. The method combines a “trap‐release” measurement protocol with a multi‐metric analysis workflow that extracts blockade distributions, sub‐level statistics and frequency‐domain signatures from trapping events, and constructs a unique fingerprint for each particle species. Applied to silica cores (≈25–30 nm) functionalized with APTES, NHS‐PEG 4 ‐Biotin and Tween‐20, the approach generates distinct fingerprints that map to surface charge, coating conformation and configuration heterogeneity. Moreover, in situ detection of surface chemical transformation via specific streptavidin binding is demonstrated, with stoichiometry‐dependent progression of the fingerprints. This platform provides a complementary tool to optical, spectral and ensemble assays for characterizing engineered nanoparticle surfaces and tracking interfacial molecular interactions in solution with label‐free and single‐particle sensitivity.

Wide-field fluorescence lifetime imaging of single molecules with a gated single-photon camera

N. Ronceray; S. Bennani; M. F. Mitsioni; N. Siegel; M. J. Marcaida et al. 

Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to discriminate fluorescent molecules or probe their nanoscale environment. Traditionally, FLIM uses time-correlated single-photon counting (TCSPC), which is precise but intrinsically low-throughput due to its dependence on point detectors. Although time-gated cameras have demonstrated the potential for high-throughput FLIM in bright samples with dense labeling, their use in single-molecule microscopy has not been explored extensively. Here, we report fast and accurate single-molecule FLIM with a commercial time-gated single-photon camera. Our optimized acquisition scheme achieves single-molecule lifetime measurements with a precision only about three times less than TCSPC, while imaging with a large number of pixels (512 × 512) allowing for the spatial multiplexing of over 3000 molecules. With this approach, we demonstrate parallelized lifetime measurements of large numbers of labeled pore-forming proteins on supported lipid bilayers, and temporal single-molecule Förster resonance energy transfer measurements at 5-25 Hz. This method holds considerable promise for the advancement of multi-target single-molecule localization microscopy and biopolymer sequencing.

Lumen charge governs gated ion transport in β-barrel nanopores

S. F. Mayer; M. F. Mitsioni; P. Robin; L. van den Heuvel; N. Ronceray et al. 

β-Barrel nanopores are involved in crucial biological processes, from ATP export in mitochondria to bacterial resistance, and represent a promising platform for emerging sequencing technologies. However, in contrast to ion channels, the understanding of the fundamental principles governing ion transport through these nanopores remains largely unexplored. Here we integrate experimental, numerical and theoretical approaches to elucidate ion transport mechanisms in β-barrel nanopores. We identify and characterize two distinct nonlinear phenomena: open-pore rectification and gating. Through extensive mutation analysis of aerolysin nanopores, we demonstrate that open-pore rectification is caused by ionic accumulation driven by the distribution of lumen charges. In addition, we provide converging evidence suggesting that gating is controlled by electric fields dissociating counterions from lumen charges, promoting local structural deformations. Our findings establish a rigorous framework for characterizing and understanding ion transport processes in protein-based nanopores, enabling the design of adaptable nanofluidic biotechnologies. We illustrate this by optimizing an aerolysin mutant for computing applications.

Assessment of neurobehavioural traits under gnotobiotic conditions: an approach for multiple analyses in the same mouse

A. Rutsch; M. Iachizzi; J. Kirundi; J. B. Kantsjö; A. L. Planchette et al. 

The gut-microbiota-brain axis influences neuroinflammation, neural development and behaviour such as sociability, memory and anxiety. To study these traits in vivo, especially during development or disease, it is crucial to analyse them over time and with multiple analyses in the same animal. With a growing understanding of the role of specific bacteria in neurodegenerative disease and behaviour, the demand for gnotobiotic mouse models has increased. However, maintaining stable hygienic conditions during behavioural testing is challenging, as exposure to conventional environments can alter the hygienic status of mice and affect behaviour. We established protocols to perform behavioural tests assessing memory, anxiety, exploration, learning and recognition under axenic conditions using flexible film isolators. Our study compared the behaviour of germ-free mice with mice carrying a defined minimal or moderately diverse microbiota. The results showed no effect of the microbiota on short- and long-term memory or novel object recognition. However, we showed that mice colonised with defined moderately diverse commensal bacteria exhibited more anxiety-like behaviour than germ-free mice. In addition, we showed that microbiota complexity is important, as only mice colonised with moderately diverse microbiota exhibited anxiety-like behaviour, allowing us to disentangle the contribution of specific microbial species or community interactions to this phenotype. This phenotype associated with differences in hippocampal and serum metabolic profiles between colonised and germ-free mice. We propose a novel approach to study rodent behaviour at different physiological and pathological stages in their life without compromising hygiene, thus promoting the refinement and reduction of mice used in experiments.

Deep‐Learning‐Assisted SICM for Enhanced Real‐Time Imaging of Nanoscale Biological Dynamics

Z. Ayar; M. Penedo Garcia; B. Drake; J. Shi; S. M. Leitão et al. 

Scanning Ion Conductance Microscopy (SICM) provides high‐resolution, nanoscale imaging of living cells, but it is generally limited by a slow scan rate, making it challenging to capture dynamic processes in real time. To tackle this challenge, an integrated data acquisition and computational framework is proposed that improves the temporal resolution of SICM by selectively skipping certain scan lines. A partial convolutional neural network (Partial‐CNN) model is developed and trained on SICM images and their corresponding masks to reconstruct the complete images from the undersampled data, ensuring the retention of structural integrity. This approach significantly reduces the image acquisition time (i.e., by 30–63%) without compromising quality, as validated through multiple quantitative metrics. Compared to conventional deep learning methods, the Partial‐CNN demonstrates higher accuracy in reconstructing fine details and maintaining consistent height maps across skipped regions. It is shown that this method provides an increased temporal resolution and retains image fidelity, making it suitable for real‐time dynamic SICM imaging and improving the smart scanning microscopy applications in time‐resolved biological imaging.

Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging

K. A. Ibrahim; C. Cathala; C. Bevilacqua; L. Feletti; R. Prevedel et al. 

The process of protein aggregation, central to neurodegenerative diseases like Huntington’s, is challenging to study due to its unpredictable nature and relatively rapid kinetics. Understanding its biomechanics is crucial for unraveling its role in disease progression and cellular toxicity. Brillouin microscopy offers unique advantages for studying biomechanical properties, yet is limited by slow imaging speed, complicating its use for rapid and dynamic processes like protein aggregation. To overcome these limitations, we developed a self-driving microscope that uses deep learning to predict the onset of aggregation from a single fluorescence image of soluble protein, achieving 91% accuracy. The system triggers optimized multimodal imaging when aggregation is imminent, enabling intelligent Brillouin microscopy of this dynamic biomechanical process. Furthermore, we demonstrate that by detecting mature aggregates in real time using brightfield images and a neural network, Brillouin microscopy can be used to study their biomechanical properties without the need for fluorescence labeling, minimizing phototoxicity and preserving sample health. This autonomous microscopy approach advances the study of aggregation kinetics and biomechanics in living cells, offering a powerful tool for investigating the role of protein misfolding and aggregation in neurodegeneration.

Sum-Frequency Scattering Spectroscopy Reveals the Charging Mechanism and Surface Structure of hBN Nanoflakes in Solution

B. Rehl; N. Ronceray; L. Zhang; A. Rađenović; S. Roke 

A molecular understanding of the interactions between two-dimensional (2D) layered materials and liquids is crucial for nanofluidics, catalysis, and solution-based 2D material processing. Among 2D materials, hexagonal boron nitride (hBN) has a number of outstanding properties, but its interactions with liquids remain poorly characterized. Here, we investigate the interfacial structure of few-layer hBN nanoflakes suspensions in ethanol and ethanol−water mixtures. Electrophoretic light scattering suggests that the nanoflakes are effectively positively charged in ethanol and negatively charged in an ethanol−water mixture. Vibrational sum-frequency scattering spectroscopy reveals the surface structural changes underlying this charge reversal. Signatures of charge transfer of opposite direction are detected on both the flake lattice and in the liquid. The different (partial) charge distributions in ethanol and water explain the apparent charge reversal.

Fast Tracking with SPADs from Binary 1-Bit Per Pixel Output: Single-Photon Single-Particle Tracking

L. W. Q. Xu; N. Ronceray; M. Mitsioni; A. Radenovic; S. Pressé 

Resolution in super-resolution microscopy – facts, artifacts, technological advancements and biological applications

K. Prakash; D. Baddeley; C. Eggeling; R. Fiolka; R. Heintzmann et al. 

Super-resolution microscopy (SRM) has undeniable potential for scientific discovery, yet still presents many challenges that hinder its widespread adoption, including technical trade-offs between resolution, speed and photodamage, as well as limitations in imaging live samples and larger, more complex biological structures. Furthermore, SRM often requires specialized expertise and complex instrumentation, which can deter biologists from fully embracing the technology. In this Perspective, a follow-up to our recent Q&A article, we aim to demystify these challenges by addressing common questions and misconceptions surrounding SRM. Experts offer practical insights into how biologists can maximize the benefits of SRM while navigating issues such as photobleaching, image artifacts and the limitations of existing techniques. We also highlight recent developments in SRM that continue to push the boundaries of resolution. Our goal is to equip researchers with the crucial knowledge they need to harness the full potential of SRM.

Bottom-up designing nanostructured oxide libraries under a lab-on-chip paradigm towards a low-cost highly-selective E-nose

M. A. Solomatin; F. S. Fedorov; D. A. Kirilenko; V. Trouillet; A. S. Varezhnikov et al. 

Background: The multisensor concept has been developed as a powerful alternative to well-known gas-analytical instrumentation for applications where a fast but accurate and reliable assessment of the environment is required. The concept follows a biology-inspired approach where the selectivity towards various gases/odors is attained via pattern recognition of multisensory signal vectors. Herein, we discuss how to design a selective multisensor library based on various metal oxide nanostructures like a lab-on-chip using a simple but efficient bottom-up growth of materials over the multi-electrode chip under robust dc electrochemical protocols. Results: In addition to a conventional growth of oxide layers over the metal electrodes, we show that the fine nanowall-like oxide structures appear as a quasi-matrixed percolation film over the SiO2 substrate surface in the inter-electrode gaps to constitute a chemiresistive film. We have tested two directions while applying the technique to grow Co, Ni, Mn, and Zn oxides to develop on-chip sensor arrays of, (i) monoxide type employing the oxide films with gradual change of growth time, and (ii) multi-oxide type based on the four oxides. The materials were thoroughly characterized by electron microscopy, X-ray diffraction, thermogravimetric analysis, and X-ray photoelectron spectroscopy/mapping to prove the composition and structure. Among tested oxides, ZnO readily appears not only at the electric potential-targeted chip zone but also in other areas to dope the films for yielding heterojunctions with other oxides that enhances a variability of functional properties in the on-chip sensor array. The gas-sensing performance of the chips has been tested versus various chemically akin alcohol vapors at the sub- and low ppm range of concentrations in a mixture with air. Significance: We show that the grown oxide nanostructures exhibit a high-sensitive chemiresistive signal which allows one to build a multisensor vector signal, selective to the kind of alcohols, even at sub-ppm concentrations. Moreover, the multi-oxide library yields options for a superior selectivity under LDA metrics than the gradient-grown mono-oxide one due to the versatility of materials while the low-cost growth protocols remain to be the same in both cases. The delivered method to produce multisensor arrays allows one producing low-cost but efficient electronic nose units for numerous applications.

Controlled Sensing of User-Defined Aptamer-Based Targets Using Scanning Ionic Conductance Spectroscopy

H. Miljkovic; L. Feletti; G. Pistoletti Blanchet; M. Penedo; Z. Ayar et al. 

Solid-state nanopores offer the possibility of detecting disease biomarkers in early diagnostic applications. Standard approaches harness fingerprinting, where protein targets are bound to DNA carriers and detected in free translocation with a solid-state nanopore. However, they suffer from several drawbacks, including uncontrolled fast translocations, which lead to low detection accuracy and a low signal-to-noise ratio (SNR). This has hampered their application in clinical settings. Here, we propose a nanopore-based system capable of sensing selected molecules of interest from biological fluids by harnessing programmable aptamer sequences attached to DNA carrier systems that are tethered to glass surfaces. This allows for spatial and velocity control over translocation in the x, y, and z directions and enables the repeated scanning of the same analyte. The scanning ion conductance spectroscopy (SICS) based approach distinguishes itself from standard nanopore-based approaches with its ability to repeatedly scan the same aptamer molecule target site more than 5 times. We designed a DNA carrier with multiple binding sites for different aptamers to increase the yield of the experiment. Our approach achieves a detection rate of up to 74%, significantly higher than the 14% achieved with standard solid-state nanopore measurements. The strong spatial control also allows for significantly increased densities of aptamer target sites along the same DNA carrier, thereby paving the way for multiplexed sensing. The system offers user-defined programmability with different aptamer sequences, potentially expanding the use of our system to sense other disease biomarkers.

Lumen Charge Governs Memristive Ion Transport in Β-barrel Nanopores

M. Mitsioni; S. F. Mayer; L. Van den Heuvel; P. Robin; N. Ronceray et al. 

Functionalized Solid-State Nanopore: Energy Harvesting and Ionic Circuitry

Intelligent and Self-Driving Microscopy of Protein Aggregation in Neurodegenerative Diseases

Particle Tracking for Quantized Intensities Accelerated with Parallelism

L. W. Xu; N. Ronceray; M. F. Mitsioni; T. Brossy; D. Šťastný et al. 

Traditional particle tracking methods approximate each pixel as reporting a continuous grayscale intensity, an assumption valid for long exposures with many detected photons. At short exposures, however, pixels record only a few discrete photon counts, and this quantization introduces both statistical and computational challenges. We present QTrack, a likelihood-based and parallelized framework that directly models discrete photon detections while exploiting correlations across all frames. By doing so, QTrack surpasses the Cramér – Rao lower bound (CRLB) prediction assuming continuous intensity and localization-and-linking. To make this possible in practice, QTrack exploits the parallelism inherent in both likelihood evaluation and posterior sampling through vectorization, multi-threading, and GPU acceleration, with lightweight interthread communication. On a single mid-range GPU (Nvidia GTX 1060, 6 GB), QTrack achieves up to a 50-fold speedup compared to a serial CPU implementation, while maintaining full accuracy and data efficiency. Together, these advances establish that short exposures with quantized photon detections are not a limitation but an opportunity: when modeled rigorously, they enable localization and diffusion coefficient estimates beyond the CRLB prediction for continuous-intensity data, setting a new standard for single-particle tracking.

Monitoring Electrochemical Dynamics through Single-Molecule Imaging of hBN Surface Emitters in Organic Solvents

E. Mayner; N. Ronceray; M. Lihter; T-H. Chen; K. Watanabe et al. 

Electrochemical techniques conventionally lack spatial resolution and average local information over an entire electrode. While advancements in spatial resolution have been made through scanning probe methods, monitoring dynamics over large areas is still challenging, and it would be beneficial to be able to decouple the probe from the electrode itself. In this work, we leverage single molecule microscopy to spatiotemporally monitor analyte surface concentrations over a wide area using unmodified hexagonal boron nitride (hBN) in organic solvents. Through a sensing scheme based on redox-active species interactions with fluorescent emitters at the surface of hBN, we observe a region of a linear decrease in the number of emitters against increasingly positive potentials applied to a nearby electrode. We find consistent trends in electrode reaction kinetics vs overpotentials between potentiostat-reported currents and optically read emitter dynamics, showing Tafel slopes greater than 290 mV·decade-1. Finally, we draw on the capabilities of spectral single-molecule localization microscopy (SMLM) to monitor the fluorescent species’ identity, enabling multiplexed readout. Overall, we show dynamic measurements of analyte concentration gradients on a micrometer-length scale with nanometer-scale depth and precision. Considering the many scalable options for engineering fluorescent emitters with two-dimensional (2D) materials, our method holds promise for optically detecting a range of interacting species with exceptional localization precision.