A single-molecule study on polymer fluid dynamics in porous media.

Understanding the dynamic behavior of polymeric fluids in porous media is essential for vast geoscience applications, particularly enhanced oil recovery and polymer-enhanced soil washing, to clean up soil contamination. During the past decades, the behavior of polymeric fluids in microscopic space has only been investigated using ensemble-averaged experimental methods in which a bulk phase behavior of the fluids characterizes flow mechanisms. Multiple flow mechanisms have been proposed based on ensemble-averaged data; however, microscale characterization of the interactions between polymers and solid surfaces and the mechanisms governing polymer retention and permeability reduction as well as the reversibility of polymer retention are lacking, resulting in a limited understanding of the flow mechanisms. Here we report direct visualization and multi-scale characterization of the dynamic behavior of polymer molecules in a representative porous medium by integrating microfluidics with single-molecule imaging. We demonstrate that the polymers' adsorption, entrapment and hydrodynamic retention contribute to their overall retention in porous media. Our study illustrates how microfluidics can help in understanding the dynamic behavior of polymers, their interactions with the solid/fluid interface and their effects on flow properties. Additionally, it demonstrates the role of microfluidic platforms in providing a more representative and accurate model for polymer retention and permeability reduction in porous media. The obtained insights encourage the development of improved models that better capture the behavior of complex fluids in confined environments and have significant implications for a wide range of applications in geoscience, materials science, and rheology.

Experimental and numerical investigation of polymer pore-clogging in micromodels.

Polymers have been used effectively in the Oil & Gas Industry for a variety of field applications, such as enhanced oil recovery (EOR), well conformance, mobility control, and others. Polymer intermolecular interactions with the porous rock, in particular, formation clogging and the associated alterations to permeability, is a common problem in the industry. In this work, fluorescent polymers and single-molecule imaging are presented for the first time to assess the dynamic interaction and transport behavior of polymer molecules utilizing a microfluidic device. Pore-scale simulations are performed to replicate the experimental observations. The microfluidic chip, also known as a "Reservoir-on-a-Chip" functions as a 2D surrogate to evaluate the flow processes that take place at the pore-scale. The pore-throat sizes of an oil-bearing reservoir rock, which range from 2 to 10 nm, are taken into consideration while designing the microfluidic chip. Using soft lithography, we created the micromodel from polydimethylsiloxane (PDMS). The conventional use of tracers to monitor polymers has a restriction due to the tendency of polymer and tracer molecules to segregate. For the first time, we develop a novel microscopy method to observe the dynamic behavior of polymer pore-clogging and unclogging processes. We provide direct dynamic observations of polymer molecules during their transport within the aqueous phase and their clustering and accumulations. Pore-scale simulations were carried out to simulate the phenomena using a finite-element simulation tool. The simulations revealed a decline in flow conductivity over time within the flow channels that experienced polymer accumulation and retention, which is consistent with the experimental observation of polymer retention. The performed single-phase flow simulations allowed us to assess the flow behavior of the tagged polymer molecules within the aqueous phase. Additionally, both experimental observation and numerical simulations are used to evaluate the retention mechanisms that emerge during flow and how they affect apparent permeability. This work provides new insights to assessing the mechanisms of polymer retention in porous media.

Graphene and Liquid Metal Integrated Multifunctional Wearable Platform for Monitoring Motion and Human-Machine Interfacing.

Motion sensors are an essential component of many electronic systems. However, the development of inertial motion sensors based on fatigue-free soft proof mass has not been explored extensively in the field of soft electronics. Nontoxic gallium-based liquid metals are an emerging class of material that exhibit attractive electromechanical properties, making them excellent proof mass materials for inertial sensors. Here, we propose and demonstrate a fully soft laser-induced graphene (LIG) and liquid metal-based inertial sensor integrated with temperature, humidity, and breathing sensors. The inertial sensor design confines a graphene-coated liquid metal droplet inside a fluidic channel, rolling over LIG resistive electrode. The proposed sensor architecture and material realize a highly mobile proof mass and a vibrational space for its oscillation. The inertial sensor exhibits a high sensitivity of 6.52% m-1 s2 and excellent repeatability (over 12 500 cycles). The platform is fabricated using a scalable, rapid laser writing technique and integrated with a programmable system on a chip (PSoC) to function as a stand-alone system for real-time wireless monitoring of movement patterns and the control of a robotic arm. The developed printed inertial platform is an excellent candidate for the next-generation of wearables motion tracking platforms and soft human-machine interfaces.

Nanoporous membrane fabrication by nanoimprint lithography for nanoparticle sieving.

An isoporous membrane with strictly controlled pore size, shape and distribution could provide an efficient, precise and mild sieving of particles in nanotechnology and biomedical applications. However there is a lack of highly porous polymeric membranes combining isoporosity and high permeance in the range below 500 nm. Track-etched membranes are practically the only commercial option. Membranes prepared by phase inversion typically have a broad pore size distribution. Most nanofabrication methods have limited the preparation of membranes with pores in the micrometer range. In this work, we present a nanotechnology-based fabrication methodology to manufacture a stable and flexible nanoporous polymeric membrane with 300 nm isopores using UV nanoimprint lithography. The highly porous membrane has a pore density of 4 × 109 pores per cm2 and stable permeance of 108 000 L m-2 h-1 bar-1. Uniform ZIF-8 nanoparticles were synthesized and the isoporous membrane successfully demonstrated as high as 100% rejection and size-based sieving performance of nanoparticles.

Flexible, Air-Stable, High-Performance Heaters Based on Nanoscale-Thick Graphite Films.

Graphite sheets are known to exhibit remarkable performance in applications such as heating panels and critical elements of thermal management systems. Industrial-scale production of graphite films relies on high-temperature treatment of polymers or calendering of graphite flakes; however, these methods are limited to obtaining micrometer-scale thicknesses. Herein, we report the fabrication of a flexible and power-efficient cm2-scaled heater based on a polycrystalline nanoscale-thick graphite film (NGF, ∼100 nm thick) grown by chemical vapor deposition. The stability of these NGF heaters (operational in air over the range 30-300 °C) is demonstrated by a 12-day continuous heating test, at 215 °C. The NGF exhibits a fast switching response and attains a steady peak temperature of 300 °C at a driving bias of 7.8 V (power density of 1.1 W/cm2). This excellent heating performance is attributed to the structural characteristics of the NGF, which contains well-distributed wrinkles and micrometer-wide few-layer graphene domains (characterized using conductive imaging and finite element methods, respectively). The efficiency and flexibility of the NGF device are exemplified by externally heating a 2000 µm-thick Pyrex glass vial and bringing 5 mL of water to a temperature of 96 °C (at 2.4 W/cm2). Overall, the NGF could become an excellent active material for ultrathin, flexible, and sustainable heating panels that operate at low power.

Three-Dimensional Ti3C2Tx MXene-Prussian Blue Hybrid Microsupercapacitors by Water Lift-Off Lithography.

The construction of electrochemical energy-storage devices by scalable thin-film microfabrication methods with high energy and power density is urgently needed for many emerging applications. Herein, we demonstrate an in-plane hybrid microsupercapacitor with a high areal energy density by employing a battery-type CuFe-Prussian blue analogue (CuFe-PBA) as the positive electrode and pseudocapacitive titanium carbide MXene (Ti3C2Tx) as the negative electrode. A three-dimensional lignin-derived laser-induced graphene electrode was prepared as the substrate by laser exposure combined with an environmentally friendly water lift-off lithography. The designed hybrid device achieved enhanced electrochemical performance thanks to the ideal match of the two types of high-rate performance materials in proton-based electrolytes and the numerous electrochemically active sites. In particular, the device delivers a high areal capacitance of 198 mF cm-2, a wide potential window (1.6 V), an ultrahigh rate performance (75.8 mF cm-2 retained even at a practical/high current density of 100 mA cm-2), and a competitive energy density of 70.5 and 27.6 µWh cm-2 at the power densities 0.74 and 52 mW cm-2, respectively. These results show that the Ti3C2Tx/CuFe-PBA hybrid microsupercapacitors are promising energy storage devices in miniaturized portable and wireless applications.

Rendering SiO2/Si Surfaces Omniphobic by Carving Gas-Entrapping Microtextures Comprising Reentrant and Doubly Reentrant Cavities or Pillars.

We present microfabrication protocols for rendering intrinsically wetting materials repellent to liquids (omniphobic) by creating gas-entrapping microtextures (GEMs) on them comprising cavities and pillars with reentrant and doubly reentrant features. Specifically, we use SiO2/Si as the model system and share protocols for two-dimensional (2D) designing, photolithography, isotropic/anisotropic etching techniques, thermal oxide growth, piranha cleaning, and storage towards achieving those microtextures. Even though the conventional wisdom indicates that roughening intrinsically wetting surfaces (θo < 90°) renders them even more wetting (θr < θo < 90°), GEMs demonstrate liquid repellence despite the intrinsic wettability of the substrate. For instance, despite the intrinsic wettability of silica θo ≈ 40° for the water/air system, and θo ≈ 20° for the hexadecane/air system, GEMs comprising cavities entrap air robustly on immersion in those liquids, and the apparent contact angles for the droplets are θr > 90°. The reentrant and doubly reentrant features in the GEMs stabilize the intruding liquid meniscus thereby trapping the liquid-solid-vapor system in metastable air-filled states (Cassie states) and delaying wetting transitions to the thermodynamically-stable fully-filled state (Wenzel state) by, for instance, hours to months. Similarly, SiO2/Si surfaces with arrays of reentrant and doubly reentrant micropillars demonstrate extremely high contact angles (θr ≈ 150°-160°) and low contact angle hysteresis for the probe liquids, thus characterized as superomniphobic. However, on immersion in the same liquids, those surfaces dramatically lose their superomniphobicity and get fully-filled within <1 s. To address this challenge, we present protocols for hybrid designs that comprise arrays of doubly reentrant pillars surrounded by walls with doubly reentrant profiles. Indeed, hybrid microtextures entrap air on immersion in the probe liquids. To summarize, the protocols described here should enable the investigation of GEMs in the context of achieving omniphobicity without chemical coatings, such as perfluorocarbons, which might unlock the scope of inexpensive common materials for applications as omniphobic materials. Silica microtextures could also serve as templates for soft materials.

Proof-of-Concept for Gas-Entrapping Membranes Derived from Water-Loving SiO2/Si/SiO2 Wafers for Green Desalination.

Desalination through direct contact membrane distillation (DCMD) exploits water-repellent membranes to robustly separate counterflowing streams of hot and salty seawater from cold and pure water, thus allowing only pure water vapor to pass through. To achieve this feat, commercial DCMD membranes are derived from or coated with water-repellent perfluorocarbons such as polytetrafluoroethylene (PTFE) and polyvinylidene difluoride (PVDF). However, the use of perfluorocarbons is limiting due to their high cost, non-biodegradability, and vulnerability to harsh operational conditions. Unveiled here is a new class of membranes referred to as gas-entrapping membranes (GEMs) that can robustly entrap air upon immersion in water. GEMs achieve this function by their microstructure rather than their chemical make-up. This work demonstrates a proof-of-concept for GEMs using intrinsically wetting SiO2/Si/SiO2 wafers as the model system; the contact angle of water on SiO2 is θo ≈ 40°. Silica-GEMs had 300 µm-long cylindrical pores whose diameters at the (2 µm-long) inlet and outlet regions were significantly smaller; this geometrically discontinuous structure, with 90° turns at the inlets and outlets, is known as the "reentrant microtexture". The microfabrication protocol for silica-GEMs entails designing, photolithography, chrome sputtering, and isotropic and anisotropic etching. Despite the water loving nature of silica, water does not intrude silica-GEMs on submersion. In fact, they robustly entrap air underwater and keep it intact even after six weeks (>106 seconds). On the other hand, silica membranes with simple cylindrical pores spontaneously imbibe water (< 1 s). These findings highlight the potential of the GEMs architecture for separation processes. While the choice of SiO2/Si/SiO2 wafers for GEMs is limited to demonstrating the proof-of-concept, it is expected that the protocols and concepts presented here will advance the rational design of scalable GEMs using inexpensive common materials for desalination and beyond.

Single crystal hybrid perovskite field-effect transistors.

The fields of photovoltaics, photodetection and light emission have seen tremendous activity in recent years with the advent of hybrid organic-inorganic perovskites. Yet, there have been far fewer reports of perovskite-based field-effect transistors. The lateral and interfacial transport requirements of transistors make them particularly vulnerable to surface contamination and defects rife in polycrystalline films and bulk single crystals. Here, we demonstrate a spatially-confined inverse temperature crystallization strategy which synthesizes micrometre-thin single crystals of methylammonium lead halide perovskites MAPbX3 (X = Cl, Br, I) with sub-nanometer surface roughness and very low surface contamination. These benefit the integration of MAPbX3 crystals into ambipolar transistors and yield record, room-temperature field-effect mobility up to 4.7 and 1.5 cm2 V-1 s-1 in p and n channel devices respectively, with 104 to 105 on-off ratio and low turn-on voltages. This work paves the way for integrating hybrid perovskite crystals into printed, flexible and transparent electronics.

Nanomembrane-Based, Thermal-Transport Biosensor for Living Cells.

Knowledge of materials' thermal-transport properties, conductivity and diffusivity, is crucial for several applications within areas of biology, material science and engineering. Specifically, a microsized, flexible, biologically integrated thermal transport sensor is beneficial to a plethora of applications, ranging across plants physiological ecology and thermal imaging and treatment of cancerous cells, to thermal dissipation in flexible semiconductors and thermoelectrics. Living cells pose extra challenges, due to their small volumes and irregular curvilinear shapes. Here a novel approach of simultaneously measuring thermal conductivity and diffusivity of different materials and its applicability to single cells is demonstrated. This technique is based on increasing phonon-boundary-scattering rate in nanomembranes, having extremely low flexural rigidities, to induce a considerable spectral dependence of the bandgap-emission over excitation-laser intensity. It is demonstrated that once in contact with organic or inorganic materials, the nanomembranes' emission spectrally shift based on the material's thermal diffusivity and conductivity. This NM-based technique is further applied to differentiate between different types and subtypes of cancer cells, based on their thermal-transport properties. It is anticipated that this novel technique to enable an efficient single-cell thermal targeting, allow better modeling of cellular thermal distribution and enable novel diagnostic techniques based on variations of single-cell thermal-transport properties.

Perovskite Photodetectors Operating in Both Narrowband and Broadband Regimes.

Photodetectors are designed, which operate in the broadband regime upon bottom illumination (from the indium tin oxide (ITO) side) and in the narrowband regime upon top illumination (from the air/perovskite side). The narrowband photodetectors show high external quantum efficiency of above 104 %. The operational spectrum of the photodetectors can also be tuned by adjusting the halide composition in the active material.

Fractal dimension analysis for spike detection in low SNR extracellular signals.

OBJECTIVE: Many algorithms have been suggested for detection and sorting of spikes in extracellular recording. Nevertheless, it is still challenging to detect spikes in low signal-to-noise ratios (SNR). We propose a spike detection algorithm that is based on the fractal properties of extracellular signals and can detect spikes in low SNR regimes. Semi-intact spikes are low-amplitude spikes whose shapes are almost preserved. The detection of these spikes can significantly enhance the performance of multi-electrode recording systems. APPROACH: Semi-intact spikes are simulated by adding three noise components to a spike train: thermal noise, inter-spike noise, and spike-level noise. We show that simulated signals have fractal properties which make them proper candidates for fractal analysis. Then we use fractal dimension as the main core of our spike detection algorithm and call it fractal detector. The performance of the fractal detector is compared with three frequently used spike detectors. MAIN RESULTS: We demonstrate that in low SNR, the fractal detector has the best performance and results in the highest detection probability. It is shown that, in contrast to the other three detectors, the performance of the fractal detector is independent of inter-spike noise power and that variations in spike shape do not alter its performance. Finally, we use the fractal detector for spike detection in experimental data and similar to simulations, it is shown that the fractal detector has the best performance in low SNR regimes. SIGNIFICANCE: The detection of low-amplitude spikes provides more information about the neural activity in the vicinity of the recording electrodes. Our results suggest using the fractal detector as a reliable and robust method for detecting semi-intact spikes in low SNR extracellular signals.

Label-free detection of sex determining region Y (SRY) via capacitive biosensor.

In this work, we present for the first time, the use of a simple fractal capacitive biosensor for the quantification and detection of sex-determining region Y (SRY) genes. This section of genetic code, which is found on the Y chromosome, finds importance for study as it causes fetuses to develop characteristics of male sex-like gonads when a mutation occurs. It is also an important genetic code in men, and disorders involving the SRY gene can cause infertility and sexual malfunction that lead to a variety of gene mutational disorders. We have therefore designed silicon-based, label-free fractal capacitive biosensors to quantify various proteins and genes. We take advantage of a good dielectric material, Parylene C for enhancing the performance of the sensors. We have integrated these sensors with a simple microchannel for easy handling of fluids on the detection area. The read-out value of an Agilent LCR meter used to measure capacitance of the sensor at a frequency of 1 MHz determined gene specificity and gene quantification. These data revealed that the capacitance measurement of the capacitive biosensor for the SRY gene depended on both the target and the concentration of DNA. The experimental outcomes in the present study can be used to detect DNA and its variations in crucial fields that have a great impact on our daily lives, such as clinical and veterinary diagnostics, industrial and environmental testing and forensic sciences.

A cyclically actuated electrolytic drug delivery device.

This work, focusing on an implantable drug delivery system, presents the first prototype electrolytic pump that combines a catalytic reformer and a cyclically actuated mode. These features improve the release performance and extend the lifetime of the device. Using our platinum (Pt)-coated carbon fiber mesh that acts as a catalytic reforming element, the cyclical mode is improved because the faster recombination rate allows for a shorter cycling time for drug delivery. Another feature of our device is that it uses a solid-drug-in-reservoir (SDR) approach, which allows small amounts of a solid drug to be dissolved in human fluid, forming a reproducible drug solution for long-term therapies. We have conducted proof-of-principle drug delivery studies using such an electrolytic pump and solvent blue 38 as the drug substitute. These tests demonstrate power-controlled and pulsatile release profiles of the chemical substance, as well as the feasibility of this device. A drug delivery rate of 11.44 ± 0.56 µg min(-1) was achieved by using an input power of 4 mW for multiple pulses, which indicates the stability of our system.

Insights on Capacitive Interdigitated Electrodes Coated with MOF Thin Films: Humidity and VOCs Sensing as a Case Study.

A prototypical metal-organic framework (MOF), a 2D periodic porous structure based on the assembly of copper ions and benzene dicarboxylate (bdc) ligands (Cu(bdc)·xH2O), was grown successfully as a thin film on interdigitated electrodes (IDEs). IDEs have been used for achieving planar CMOS-compatible low-cost capacitive sensing structures for the detection of humidity and volatile organic compounds (VOCs). Accordingly, the resultant IDEs coated with the Cu(bdc)·xH2O thin film was evaluated, for the first time, as a capacitive sensor for gas sensing applications. A fully automated setup, using LabVIEW interfaces to experiment conduction and data acquisition, was developed in order to measure the associated gas sensing performance.

Eye Velocity Gain Fields in MSTd During Optokinetic Stimulation.

Lesion studies argue for an involvement of cortical area dorsal medial superior temporal area (MSTd) in the control of optokinetic response (OKR) eye movements to planar visual stimulation. Neural recordings during OKR suggested that MSTd neurons directly encode stimulus velocity. On the other hand, studies using radial visual flow together with voluntary smooth pursuit eye movements showed that visual motion responses were modulated by eye movement-related signals. Here, we investigated neural responses in MSTd during continuous optokinetic stimulation using an information-theoretic approach for characterizing neural tuning with high resolution. We show that the majority of MSTd neurons exhibit gain-field-like tuning functions rather than directly encoding one variable. Neural responses showed a large diversity of tuning to combinations of retinal and extraretinal input. Eye velocity-related activity was observed prior to the actual eye movements, reflecting an efference copy. The observed tuning functions resembled those emerging in a network model trained to perform summation of 2 population-coded signals. Together, our findings support the hypothesis that MSTd implements the visuomotor transformation from retinal to head-centered stimulus velocity signals for the control of OKR.

Neuronal variability of MSTd neurons changes differentially with eye movement and visually related variables.

Neurons in macaque cortical area MSTd are driven by visual motion and eye movement related signals. This multimodal characteristic makes MSTd an ideal system for studying the dependence of neuronal activity on different variables. Here, we analyzed the temporal structure of spiking patterns during visual motion stimulation using 2 distinct behavioral paradigms: fixation (FIX) and optokinetic response. For the FIX condition, inter- and intra-trial variability of spiking activity decreased with increasing stimulus strength, complying with a recent neurophysiological study reporting stimulus-related decline of neuronal variability. In contrast, for the optokinetic condition variability increased together with increasing eye velocity while retinal image velocity remained low. Analysis of stimulus signal variability revealed a correlation between the normalized variance of image velocity and neuronal variability, but no correlation with normalized eye velocity variance. We further show that the observed difference in neuronal variability allows classifying spike trains according to the paradigm used, even when mean firing rates (FRs) were similar. The stimulus-dependence of neuronal variability may result from the local network structure and/or the variability characteristics of the input signals, but may also reflect additional timing-based mechanisms independent of the neuron's mean FR and related to the modality driving the neuron.

A novel method to measure the generated voltage of a ZnO nanogenerator.

A novel method to measure the output voltage of a zinc oxide nanowire nanogenerator is proposed. Various tests are performed to verify that the output voltage does indeed originate from the nanogenerator and not from environmental noise. Although noise does influence the output voltage measurements, the output voltage is easily distinguishable from the measured noise. It is also shown that the method can be used to determine the internal resistance of the nanogenerator by measuring the output voltage over different output resistors.

Effects of unilateral midbrain lesions on gaze (eye and head) movements.

The rostral midbrain, especially the rostral interstitial nucleus of the medial longitudinal fasciculus (RIMLF) and the interstitial nucleus of Cajal (INC), plays an important role in the control of eye movements. Although the effect of midbrain lesions on eye movements is well investigated, little is known about its effect on head movements. In this study, we measured eye and head (gaze) movements in five patients with unilateral, acute midbrain lesions and nine healthy controls. In all patients, vertical eye velocity was reduced as a result of the lesion compared to healthy subjects, whereas peak head velocity was not affected. Further, most patients displayed an increased contralesional torsion in peripheral head positions, independently of whether they presented a head tilt in the straight-ahead position or not. Our results indicate that midbrain lesions affect the control of eye and head differently and independently.

An information-theoretic approach for evaluating probabilistic tuning functions of single neurons.

Neuronal tuning functions can be expressed by the conditional probability of observing a spike given any combination of explanatory variables. However, accurately determining such probabilistic tuning functions from experimental data poses several challenges such as finding the right combination of explanatory variables and determining their proper neuronal latencies. Here we present a novel approach of estimating and evaluating such probabilistic tuning functions, which offers a solution for these problems. By maximizing the mutual information between the probability distributions of spike occurrence and the variables, their neuronal latency can be estimated, and the dependence of neuronal activity on different combinations of variables can be measured. This method was used to analyze neuronal activity in cortical area MSTd in terms of dependence on signals related to eye and retinal image movement. Comparison with conventional feature detection and regression analysis techniques shows that our method offers distinct advantages, if the dependence does not match the regression model.