Encapsulating commercial accelerometers with epoxy and fluoroelastomer for harsh hydrocarbon fluid environment.

Traditionally, in the oil and gas industry, accelerometers are mounted externally on motors for condition monitoring of vertically suspended, closed suction hydrocarbon pumps due to their inability to withstand harsh downhole environments, preventing the detection of impeller failures. This study addresses the need for encapsulation solutions for accelerometers submerged in hydrocarbon fluid environments. It evaluates the feasibility of epoxy and fluoroelastomer as encapsulation materials for long-term immersion in high-temperature hydrocarbon fluid and determines their impact on the accelerometer's performance. Extensive testing involved submersion in high-temperature hydrocarbon fluid at 150 °C for over 10,000 h and six months in brine. Material characterization, including mass variation, microscopic imaging, and FTIR spectroscopy, revealed negligible degradation. Encapsulated accelerometers effectively detected vibrations with an acceptable alteration in amplitude. In comparison with commercial alternatives, our encapsulation outperformed them. While oil traces became evident within just 24 h in the alternatives, our solution exhibited no signs of leakage. This research pioneers a novel packaging solution employing epoxy and fluoroelastomer for side-exit commercial sensors tailored for high-temperature hydrocarbon fluid applications, addressing a critical gap in the industry. Our work enhances reliability and safety for vertical oil pump condition monitoring in downhole applications, benefiting the oil and gas sector.

Active Probe Atomic Force Microscopy with Quattro-Parallel Cantilever Arrays for High-Throughput Large-Scale Sample Inspection.

An Atomic Force Microscope (AFM) is a powerful and versatile tool for nanoscale surface studies to capture 3D topography images of samples. However, due to their limited imaging throughput, AFMs have not been widely adopted for large-scale inspection purposes. Researchers have developed high-speed AFM systems to record dynamic process videos in chemical and biological reactions at tens of frames per second, at the cost of a small imaging area of up to several square micrometers. In contrast, inspecting large-scale nanofabricated structures, such as semiconductor wafers, requires nanoscale spatial resolution imaging of a static sample over hundreds of square centimeters with high productivity. Conventional AFMs use a single passive cantilever probe with an optical beam deflection system, which can only collect one pixel at a time during AFM imaging, resulting in low imaging throughput. This work utilizes an array of active cantilevers with embedded piezoresistive sensors and thermomechanical actuators, which allows simultaneous multi-cantilever operation in parallel operation for increased imaging throughput. When combined with large-range nano-positioners and proper control algorithms, each cantilever can be individually controlled to capture multiple AFM images. With data-driven post-processing algorithms, the images can be stitched together, and defect detection can be performed by comparing them to the desired geometry. This paper introduces principles of the custom AFM using the active cantilever arrays, followed by a discussion on practical experiment considerations for inspection applications. Selected example images of silicon calibration grating, highly-oriented pyrolytic graphite, and extreme ultraviolet lithography masks are captured using an array of four active cantilevers ("Quattro") with a 125 µm tip separation distance. With more engineering integration, this high-throughput, large-scale imaging tool can provide 3D metrological data for extreme ultraviolet (EUV) masks, chemical mechanical planarization (CMP) inspection, failure analysis, displays, thin-film step measurements, roughness measurement dies, and laser-engraved dry gas seal grooves.

Review: Advanced Atomic Force Microscopy Modes for Biomedical Research.

Visualization of biomedical samples in their native environments at the microscopic scale is crucial for studying fundamental principles and discovering biomedical systems with complex interaction. The study of dynamic biological processes requires a microscope system with multiple modalities, high spatial/temporal resolution, large imaging ranges, versatile imaging environments and ideally in-situ manipulation capabilities. Recent development of new Atomic Force Microscopy (AFM) capabilities has made it such a powerful tool for biological and biomedical research. This review introduces novel AFM functionalities including high-speed imaging for dynamic process visualization, mechanobiology with force spectroscopy, molecular species characterization, and AFM nano-manipulation. These capabilities enable many new possibilities for novel scientific research and allow scientists to observe and explore processes at the nanoscale like never before. Selected application examples from recent studies are provided to demonstrate the effectiveness of these AFM techniques.

Building block 3D printing based on molecular self-assembly monolayer with self-healing properties.

The spontaneous formation of biological substances, such as human organs, are governed by different stimuli driven by complex 3D self-organization protocols at the molecular level. The fundamentals of such molecular self-assembly processes are critical for fabrication of advanced technological components in nature. We propose and experimentally demonstrate a promising 3D printing method with self-healing property based on molecular self-assembly-monolayer principles, which is conceptually different than the existing 3D printing protocols. The proposed molecular building-block approach uses metal ion-mediated continuous self-assembly of organic molecular at liquid-liquid interfaces to create 2D and 3D structures. Using this technique, we directly printed nanosheets and 3D rods using dithiol molecules as building block units.

Quantification and reduction of Poisson-Gaussian mixed noise induced errors in ellipsometry.

Ellipsometry is an important metrology tool in a plethora of industries. The measurement accuracy can be significantly affected by the existence of Poisson-Gaussian mixed noise. This paper quantifies the induced error on normalized Mueller matrix measurements through statistical analysis. A method is then proposed to mitigate the effects of Poisson-Gaussian noise in spectroscopic ellipsometry signal demodulation, based on maximum likelihood estimation. The noise is characterized through experiments on an in-house setup. The improved performance of dimension reconstruction from the proposed method is demonstrated through simulations.

Lights Out! Nano-Scale Topography Imaging of Sample Surface in Opaque Liquid Environments with Coated Active Cantilever Probes.

Atomic force microscopy is a powerful topography imaging method used widely in nanoscale metrology and manipulation. A conventional Atomic Force Microscope (AFM) utilizes an optical lever system typically composed of a laser source, lenses and a four quadrant photodetector to amplify and measure the deflection of the cantilever probe. This optical method for deflection sensing limits the capability of AFM to obtaining images in transparent environments only. In addition, tapping mode imaging in liquid environments with transparent sample chamber can be difficult for laser-probe alignment due to multiple different refraction indices of materials. Spurious structure resonance can be excited from piezo actuator excitation. Photothermal actuation resolves the resonance confusion but makes optical setup more complicated. In this paper, we present the design and fabrication method of coated active scanning probes with piezoresistive deflection sensing, thermomechanical actuation and thin photoresist polymer surface coating. The newly developed probes are capable of conducting topography imaging in opaque liquids without the need of an optical system. The selected coating can withstand harsh chemical environments with high acidity (e.g., 35% sulfuric acid). The probes are operated in various opaque liquid environments with a custom designed AFM system to demonstrate the imaging performance. The development of coated active probes opens up possibilities for observing samples in their native environments.

Unevenly spaced continuous measurement approach for dual rotating-retarder Mueller matrix ellipsometry.

In order to efficiently extract the sample Mueller matrix by dual rotating-retarder ellipsometry, it is critical for the data reduction technique to achieve a minimal data processing burden while considering the ease of retarder control. In this paper, we propose an unevenly spaced sampling strategy to reach a globally optimal measurement matrix with minimum sampling points for continuous measurements. Taking into account the robustness to both systematic errors and detection noise, we develop multi-objective optimization models to identify the optimal unevenly spaced sampling points. A combined global search algorithm based on the multi-objective genetic algorithm is subsequently designed to solve our model. Finally, simulations and experiments are conducted to validate our approach as well as to provide near-optimal schemes for different design scenarios. The results demonstrate that significant improvement on error immunity performance can be achieved by applying an unevenly sampled measurement strategy compared to an evenly sampled one for our ellipsometer scenario.

Multifunctional "Hydrogel Skins" on Diverse Polymers with Arbitrary Shapes.

Slippery and hydrophilic surfaces find critical applications in areas as diverse as biomedical devices, microfluidics, antifouling, and underwater robots. Existing methods to achieve such surfaces rely mostly on grafting hydrophilic polymer brushes or coating hydrogel layers, but these methods suffer from several limitations. Grafted polymer brushes are prone to damage and do not provide sufficient mechanical compliance due to their nanometer-scale thickness. Hydrogel coatings are applicable only for relatively simple geometries, precluding their use for the surfaces with complex geometries and features. Here, a new method is proposed to interpenetrate hydrophilic polymers into the surface of diverse polymers with arbitrary shapes to form naturally integrated "hydrogel skins." The hydrogel skins exhibit tissue-like softness (Young's modulus ≈ 30 kPa), have uniform and tunable thickness in the range of 5-25 µm, and can withstand prolonged shearing forces with no measurable damage. The hydrogel skins also provide superior low-friction, antifouling, and ionically conductive surfaces to the polymer substrates without compromising their original mechanical properties and geometry. Applications of the hydrogel skins on inner and outer surfaces of various practical polymer devices including medical tubing, Foley catheters, cardiac pacemaker leads, and soft robots on massive scales are further demonstrated.

Context-Aware Gossip-Based Protocol for Internet of Things Applications.

This paper proposes a gossip-based protocol that utilises a multi-factor weighting function (MFWF) that takes several parameters into account: residual energy, Chebyshev distances to neighbouring nodes and the sink node, node density, and message priority. The effects of these parameters were examined to guide the customization of the weight function to effectively disseminate data to three types of IoT applications: critical, bandwidth-intensive, and energy-efficient applications. The performances of the three resulting MFWFs were assessed in comparison with the performances of the traditional gossiping protocol and the Fair Efficient Location-based Gossiping (FELGossiping) protocol in terms of end-to-end delay, network lifetime, rebroadcast nodes, and saved rebroadcasts. The experimental results demonstrated the proposed protocol's ability to achieve a much shorter delay for critical IoT applications. For bandwidth-intensive IoT application, the proposed protocol was able to achieve a smaller percentage of rebroadcast nodes and an increased percentage of saved rebroadcasts, i.e., better bandwidth utilisation. The adapted MFWF for energy-efficient IoT application was able to improve the network lifetime compared to that of gossiping and FELGossiping. These results demonstrate the high level of flexibility of the proposed protocol with respect to network context and message priority.

Characterization of Environmental Dust in the Dammam Area and Mud After-Effects on Bisphenol-A Polycarbonate Sheets.

Owing to recent climate changes, dust storms are increasingly common, particularly in the Middle East region. Dust accumulation and subsequent mud formation on solid surfaces in humid environments typically have adverse effects on surface properties such as optical transmittance, surface texture, and microhardness. This is usually because the mud, which contains alkaline and ionic species, adheres strongly to the surface, often through chemical bonds, and is therefore difficult to remove. In this study, environmental dust and the after-effects of mud formed on a polycarbonate sheet, which is commonly used as a protective glass in photovoltaic cells. Ionic compounds (OH(-)) are shown to significantly affect the optical, mechanical, and textural characteristics of the polycarbonate surface, and to increase the adhesion work required to remove the dry mud from the polycarbonate surface upon drying. Such ability to modify characteristics of the polycarbonate surface could address the dust/mud-related limitations of superhydrophobic surfaces.

Multi-eigenmode control for high material contrast in bimodal and higher harmonic atomic force microscopy.

High speed imaging and mapping of nanomechanical properties in atomic force microscopy (AFM) allows the observation and characterization of dynamic sample processes. Recent developments involve several cantilever frequencies in a multifrequency approach. One method actuates the first eigenmode for topography imaging and records the excited higher harmonics to map nanomechanical properties of the sample. To enhance the higher frequencies' response two or more eigenmodes are actuated simultaneously, where the higher eigenmode(s) are used to quantify the nanomechanics. In this paper, we combine each imaging methodology with a novel control approach. It modifies the Q factor and resonance frequency of each eigenmode independently to enhance the force sensitivity and imaging bandwidth. It allows us to satisfy the different requirements for the first and higher eigenmode. The presented compensator is compatible with existing AFMs and can be simply attached with minimal modifications. Different samples are used to demonstrate the improvement in nanomechanical contrast mapping and imaging speed of tapping mode AFM in air. The experiments indicate most enhanced nanomechanical contrast with low Q factors of the first and high Q factors of the higher eigenmode. In this scenario, the cantilever topography imaging rate can also be easily improved by a factor of 10.

Aggrecan nanoscale solid-fluid interactions are a primary determinant of cartilage dynamic mechanical properties.

Poroelastic interactions between interstitial fluid and the extracellular matrix of connective tissues are critical to biological and pathophysiological functions involving solute transport, energy dissipation, self-stiffening and lubrication. However, the molecular origins of poroelasticity at the nanoscale are largely unknown. Here, the broad-spectrum dynamic nanomechanical behavior of cartilage aggrecan monolayer is revealed for the first time, including the equilibrium and instantaneous moduli and the peak in the phase angle of the complex modulus. By performing a length scale study and comparing the experimental results to theoretical predictions, we confirm that the mechanism underlying the observed dynamic nanomechanics is due to solid-fluid interactions (poroelasticity) at the molecular scale. Utilizing finite element modeling, the molecular-scale hydraulic permeability of the aggrecan assembly was quantified (kaggrecan = (4.8 ± 2.8) × 10(-15) m(4)/N·s) and found to be similar to the nanoscale hydraulic permeability of intact normal cartilage tissue but much lower than that of early diseased tissue. The mechanisms underlying aggrecan poroelasticity were further investigated by altering electrostatic interactions between the molecule's constituent glycosaminoglycan chains: electrostatic interactions dominated steric interactions in governing molecular behavior. While the hydraulic permeability of aggrecan layers does not change across species and age, aggrecan from adult human cartilage is stiffer than the aggrecan from newborn human tissue.

Event triggered state estimation techniques for power systems with integrated variable energy resources.

For many decades, state estimation (SE) has been a critical technology for energy management systems utilized by power system operators. Over time, it has become a mature technology that provides an accurate representation of system state under fairly stable and well understood system operation. The integration of variable energy resources (VERs) such as wind and solar generation, however, introduces new fast frequency dynamics and uncertainties into the system. Furthermore, such renewable energy is often integrated into the distribution system thus requiring real-time monitoring all the way to the periphery of the power grid topology and not just the (central) transmission system. The conventional solution is two fold: solve the SE problem (1) at a faster rate in accordance with the newly added VER dynamics and (2) for the entire power grid topology including the transmission and distribution systems. Such an approach results in exponentially growing problem sets which need to be solver at faster rates. This work seeks to address these two simultaneous requirements and builds upon two recent SE methods which incorporate event-triggering such that the state estimator is only called in the case of considerable novelty in the evolution of the system state. The first method incorporates only event-triggering while the second adds the concept of tracking. Both SE methods are demonstrated on the standard IEEE 14-bus system and the results are observed for a specific bus for two difference scenarios: (1) a spike in the wind power injection and (2) ramp events with higher variability. Relative to traditional state estimation, the numerical case studies showed that the proposed methods can result in computational time reductions of 90%. These results were supported by a theoretical discussion of the computational complexity of three SE techniques. The work concludes that the proposed SE techniques demonstrate practical improvements to the computational complexity of classical state estimation. In such a way, state estimation can continue to support the necessary control actions to mitigate the imbalances resulting from the uncertainties in renewables.

High-bandwidth AFM-based rheology reveals that cartilage is most sensitive to high loading rates at early stages of impairment.

Utilizing a newly developed atomic-force-microscopy-based wide-frequency rheology system, we measured the dynamic nanomechanical behavior of normal and glycosaminoglycan (GAG)-depleted cartilage, the latter representing matrix degradation that occurs at the earliest stages of osteoarthritis. We observed unique variations in the frequency-dependent stiffness and hydraulic permeability of cartilage in the 1 Hz-to-10 kHz range, a frequency range that is relevant to joint motions from normal ambulation to high-frequency impact loading. Measurement in this frequency range is well beyond the capabilities of typical commercial atomic force microscopes. We showed that the dynamic modulus of cartilage undergoes a dramatic alteration after GAG loss, even with the collagen network still intact: whereas the magnitude of the dynamic modulus decreased two- to threefold at higher frequencies, the peak frequency of the phase angle of the modulus (representing fluid-solid frictional dissipation) increased 15-fold from 55 Hz in normal cartilage to 800 Hz after GAG depletion. These results, based on a fibril-reinforced poroelastic finite-element model, demonstrated that GAG loss caused a dramatic increase in cartilage hydraulic permeability (up to 25-fold), suggesting that early osteoarthritic cartilage is more vulnerable to higher loading rates than to the conventionally studied "loading magnitude". Thus, over the wide frequency range of joint motion during daily activities, hydraulic permeability appears the most sensitive marker of early tissue degradation.

White-light scanning interferometer for absolute nano-scale gap thickness measurement.

A special configuration of white-light scanning interferometer is described for measuring the absolute air gap thickness between two planar plates brought into close proximity. The measured gap is not located in any interference arm of the interferometer, but acts as an amplitude-and-phase modulator of the light source. Compared with the common white-light interferometer our approach avoids the influence of the chromatic dispersion of the planar plates on the gap thickness quantification. It covers a large measurement range of from approximate contact to tens of microns with a high resolution of 0.1 nm. Detailed analytical models are presented and signal-processing algorithms based on convolution and correlation techniques are developed. Practical measurements are carried out and the experimental results match well with the analysis and simulation. Short-time and long-time repeatabilities are both tested to prove the high performance of our method.

Extracting cancer cell line electrochemical parameters at the single cell level using a microfabricated device.

Cancer cells have distinctive electrochemical properties. This work sheds light on the system design aspects and key challenges that should be considered when experimentally analyzing and extracting the electrical characteristics of a tumor cell line. In this study, we developed a cellularbased functional microfabricated device using lithography technology. This device was used to investigate the electrochemical parameters of cultured cancer cells at the single-cell level. Using impedance spectroscopy analyses, we determined the average specific capacitance and resistance of the membrane of the cancer cell line B16-F10 to be 1.154 +/- 0.29 microF/cm(2), and 3.9 +/- 1.15 KOmega.cm(2) (mean +/- SEM, n =14 cells), respectively. The consistency of our findings via different trails manifests the legitimacy of our experimental procedure. Furthermore, the data were compared with a proposed constructed analytical-circuit model. The results of this work may greatly assist researchers in defining an optimal procedure while extracting electrical properties of cancer cells. Detecting electrical signals at the single cell level could lead to the development of novel approaches for analysis of malignant cells in human tissues and biopsies.

Large-area and high-resolution distortion measurement based on Moiré fringe method for hot embossing process.

A Moiré fringe approach is developed to identify simultaneously the global and local distortions in hot-embossed polymeric samples. A square grid pattern with a pitch of 63.5 microm is hot-embossed on the polymer substrate. When a reference grid, a polymeric film with the same pattern, is placed on top of the sample, a Moiré fringe pattern is observed and recorded by a document scanner. The deviation of the intersections of the fringes from their ideal positions presents the residual distortion in the sample. With different sample-reference rotation angles eight images are acquired for the same sample to achieve the optimal result by a data fitting technique. The validity of this method is proved by the self-consistency of the results from the eight images. To the best of our knowledge, this is the first time distortion quantification has been achieved both in a large area up to that of a scanner and with a high resolution at the level of 1 microm. Furthermore, we do not use any expensive instrument, nor need to measure the sample-reference rotation angle or position the sample precisely, and the process is run automatically by a computer instead of manual operation.

Cell motion model for moving dielectrophoresis.

Moving dielectrophoresis has been recently developed by the authors as an alternative method to achieve simultaneous cell fractionation and transportation. With an array of independently excitable microelectrodes, this method generates a moving electric field to sequentially fractionate and transport cells across a microchannel. Due to the peculiarity of this method, the motion of the cells is unsteady and there are interesting and distinct differences between cells experiencing positive or negative dielectrophoresis. For a proper understanding and design of a microdevice utilizing this methodology, this study presents a model for the equation of motion for a polarized cell and its unsteady motion under moving dielectrophoresis. The model considers the basic module to generate a moving electric field, where there is a finite-width top electrode and an infinite-width bottom electrode, in a parallel-plate configuration. The forces considered include dielectrophoretic force, fluid drag, buoyancy, and gravitational force. These forces are modeled as equivalent point forces acting at the center of mass of the cell. A parallel-plate wall correction factor is employed to account for the effect of the large cell size to microchannel height ratio. Various parameters are examined including the initial position of the cell relative to the electrodes, cell's Clausius-Mossotti factor, cell size, applied voltage, electrode width, interelectrode gap, microchannel height, number of energized electrodes, and types of electrode configurations. Reasonable agreements were obtained between simulated and experimental results. As the solution of the unsteady motion is rather tedious, a MATLAB algorithm, with all the associated files, for the prediction of the cell trajectory, is available on request.

Dynamic cell fractionation and transportation using moving dielectrophoresis.

This study presents a new cell manipulation method using a moving dielectrophoretic force to transport or fractionate cells along a microfluidic channel. The proposed moving dielectrophoresis (mDEP) is generated by sequentially energizing a single electrode or an array of electrodes to form an electric field that moves cells continuously along the microchannel. Cell fractionation is controlled by the applied electrical frequency, and cell transportation is controlled by the interelectrode activation time. The applicability of this method was demonstrated to simultaneously fractionate and transport Saccharomyces cerevisiae yeast cells, both viable and nonviable, by operating at conditions under which the cells were subjected to positive and negative dielectrophoresis, respectively. Compared to the conventional dielectrophoresis (cDEP and traveling wave dielectrophoresis (twDEP), moving dielectrophoresis allows cells to be separated on the basis of the real part of the Clausius-Mossotti factor, as in cDEP, but yet allows the direct transportation of separated cells without using fluid flow, as in twDEP. This dielectrophoresis technique provides a new way to manipulate cells and can be readily implemented on programmable multielectrode devices.

Measurements and quality assessments of near-infrared plasma glucose spectra in the combination band region using a scanning filter spectrometer.

Near-infrared measurements of glucose in human plasma are performed using a custom, rapid, high-throughput filter-based spectrometer covering a spectral range between 2080 and 2315 nm. Quality of the measured glucose signals is quantified through the use of two figures of merit: selectivity and limit of detection. Selectivity measures the uniqueness of the glucose spectrum from among the interfering spectra. Limit of detection measures the smallest glucose concentration change detectable. The proposed system, which includes the spectroscopic hardware and a spectral preprocessing algorithm, is shown to produce a selectivity value of 0.57, with zero being nonselective and one being fully selective, and a limit of detection value of 2.2 mM. Prediction of an independent dataset is also performed using net analyte signal-based and partial least-squares multivariate calibration techniques, which produce standard error of prediction values of 1.14 and 1.45 mM, respectively.