Herein, we demonstrate how the chemical sensitivity and mechanical stability of 2D thin films of eutectic gallium indium (eGaIn) can be leveraged to sense the presence of dilute amounts of fluorinated compounds (e.g., per- and polyfluorinated alkyl substances or PFAS). The method utilizes the interfacial interactions between 2D thin films of eGaIn and PFAS microdroplets, which induce thin film delaminations due to the perturbations in the Ga-to-O ratio at the interface. We tested three fluorinated samples - 200 ppm perfluorooctanoic acid (PFOA), 0.014 ppb PFAS, and 0.001 ppb PFAS to investigate the delamination, which exhibits sensitivities to concentrations. We leveraged energy-dispersive X-ray spectroscopy (EDS) and Raman spectroscopy to quantify and probe the shift in elemental distributions and surface dynamics of the eGaIn films. The observed delamination phenomena and the spectroscopic analyses suggest that our method provides a rapid in situ PFAS analysis tool related to total organic fluorine detection, complementing the existing technologies. Such a simplistic tool offers a fast approach to developing low-cost, field-deployable chemical sensors for total organofluorine detection.

Strong chemical or voltage-driven studies of gallium alloys (liquid metal, LM) show methods of altering the surface energy of the bare alloys by controlling Ga2O3 (Gallium Oxide)- a 3-5 nm surface oxide that forms on LM. However, various fluids (i.e., water) interact weakly compared to strong acids or bases and do not etch Ga2O3. Specialized instruments are often required to study such interactions, which are not readily available. Herein, an LM-based nanoporous conductive wire platform is demonstrated, which can effectively be utilized for real-time weaker interfacial studies. The unconventional platform allows fluid transport and interfacial studies within the nanoporous domain, which is still foreign in the literature. Nanoporous conductive wires are fabricated by injecting eutectic gallium indium (eGaIn) into hollow microtubes collected from expired and unused artificial kidneys. These steps upcycle medical waste and confine Ga2O3 at the nanopores for an inexpensive metal-oxide/metal framework. The platform for interfacial fluidics is harnessed, leveraging deionized (DI) water, 1 m hydrochloric acid (HCl), and 95% ethanol (EtOH). This study also demonstrates capacitive sensors that can be immediately implemented using nanoporous conducive wires. Advanced applications from this study suggest that future exploration of such soft systems can lead to more nano/bioanalyses harnessing LM alloys. This study demonstrates liquid metal-based nanoporous conductive wires fabricated from medical waste for interfacial fluidic studies. The characterization techniques and experimental results are analyzed based on fluid transport properties and changes in the oxide's physicochemical state. Perturbed electrical and electromagnetic signals, harnessing the interactions, demonstrate the utility of such unconventional functional systems, which can be expanded to the nano/biosensors paradigm.image

Here, we describe a simple and unique architecture of a microfluidic mixer that can mix two streams (Water and Fluorescein Isothiocyanate (FITC) buffer) with 30 diffusion, and to enhance mixing, we used three different types of geometric obstacles inside the channel. Comsol multiphysics simulation software was used to validate the theoretical mixing efficiency (at Reynolds Number, Re   0.1, 1, and 10) of this device. We utilized soft lithography and replica molding techniques to fabricate the device out of Polydimethylsiloxane (PDMS, a commonly used polymer) on a glass substrate. The effective length of our microfluidic mixer is 5mm, and the channel width is about 200 microns with 50 micron height. It is composed of three different shapes of obstacles (e.g., 6 cones, 3 arrays of rectangular bars, and 5 circular posts), and all of these are placed inside the main channel. FITC buffer (Diffusion co-efficient, D = 0.5 x 10-9 m2/s) and DI water were used to investigate the mixer performance at Re 1. Simulated and experimental results are based on approximately 1.1 mm2 flow area and suggest that 30

In situ measurement of analytes for in vivo or in vitro systems has been challenging due to the bulky size of traditional analytical instruments. Also, frequent in vitro concentration measurements rely on fluorescence-based methods or direct slicing of the matrix for analyses. These traditional approaches become unreliable if localized and in situ analyses are needed. In contrast, for in situ and real-time analysis of target analytes, surface-engineered optical fibers can be leveraged as a powerful miniaturized tool, which has shown promise from bio to environmental studies. Herein, we demonstrate an optical fiber functionalized with gold nanoparticles using a dip-coating process to investigate the interaction of light with molecules at or near the surface of the optical fiber. Localized surface plasmon resonance from the light-matter interaction enables the detection of minute changes in the refractive index of the surrounding medium. We used this principle to assess the in situ molecular distribution of a synthetic drug (methylene blue) in an in vitro matrix (agarose gel) having varying concentrations. Leveraging the probed Z-height in diffused analytes, combined with its in silico data, our platform shows the feasibility of a simple optofluidic tool. Such straightforward in situ measurements of analytes with optical fiber hold potential for real-time molecular diffusion and molecular perturbation analyses relevant to biomedical and clinical studies.

Differentially wettable surfaces are well sought after in energy, water, health care, separation science, self-cleaning, biology, and other lab-on-chip applications-however, most demonstrations of realizing differential wettability demand complex processes. Herein, we chemically etch gallium oxide (Ga2O3) from in-plane patterns (2D) of eutectic gallium indium (eGaIn) to demonstrate a differentially wettable interface using chlorosilane vapor. We produce 2D patterns of eGaIn on bare glass slides in native air using cotton swabs as paint brushes. Exposing the entire system to chlorosilane vapor induces chemical etching of the oxide layer, which recovers the high-surface energy of eGaIn, to produce nano-to-mm droplets on the pre-patterned area. We rinse the entire system with deionized (DI) water to achieve differentially wettable surfaces. Measurements of contact angles using a goniometer confirmed hydrophobic and hydrophilic interfaces. Scanning electron microscopy (SEM) images confirmed the distribution and energy dispersive spectra (EDS) exhibited the elemental compositions of the micro-to-nano droplets after silanization (silane treatment). Also, we demonstrated two proofs of concept, i.e., open-ended microfluidics and differential wettability on curved interfaces, to demonstrate the advanced applications of the current work. This straightforward approach using two soft materials (silane and eGaIn) to achieve differential wettability on laboratory-grade glass slides and other surfaces has future implications for nature-inspired self-cleaning surfaces in nanotechnologies, bioinspired and biomimetic open-channel microfluidics, coatings, and fluid-structure interactions.

Optimizing drug delivery to brain tumors requires knowledge of momentum transport and molecular diffusion within the interstitial fluid of normal and tumor tissue in the central nervous system (CNS). The delivery method, tissue material properties, individual-specific interstitial fluid flow, and molecular drug properties all impact drug distribution. Convection-enhanced delivery (CED) can deliver drugs to the CNS by helping to bypass the blood-brain barrier (BBB). Improved modeling of CED-mediated drug distribution may help optimize the tumor area covered by the infused drugs. Moreover, rational multi-catheter systems could empower concurrent recovery of pharmacodynamic biomarkers indicative of therapeutic activity within the tumor tissue. Toward this goal, finite element methods (FEM) tools, such as COMSOL Multiphysics, can simulate molecular distribution inside specific predefined shapes and porous material properties. While most CED literature leverages a single catheter to deliver the drug to the tumor, adding extraction catheters could enable biomarkers and spatially -directed fluid convection recovery. We leveraged COMSOL Multiphysics to perform a computational study simulating CED with one or two extraction catheters perturbing the concentration profile over the region of interest. We evaluate volumetric drug distribution across relevant variables by varying the distance between the infusion and extraction catheters, flow rates, and drug diffusivity. We also validated our in silico results with in vitro agarose gel models, a matrix widely used to simulate diffusion within brain tissue. This in silico simulation system can be applied to studies spanning therapeutic local drug delivery and early phase in situ pharmacody-namic drug testing trials within live human and engineered tissues.

Pendant drops of oxide-coated high-surface tension fluids frequently produce perturbed shapes that impede interfacial studies. Eutectic gallium indium or Galinstan are high-surface tension fluids coated with a ∼5 nm gallium oxide (Ga _2 O _3 ) film and falls under this fluid classification, also known as liquid metals (LMs). The recent emergence of LM-based applications often cannot proceed without analyzing interfacial energetics in different environments. While numerous techniques are available in the literature for interfacial studies- pendant droplet-based analyses are the simplest. However, the perturbed shape of the pendant drops due to the presence of surface oxide has been ignored frequently as a source of error. Also, exploratory investigations of surface oxide leveraging oscillatory pendant droplets have remained untapped. We address both challenges and present two contributing novelties- (a) by utilizing the machine learning (ML) technique, we predict the approximate surface tension value of perturbed pendant droplets, (ii) by leveraging the oscillation-induced bubble tensiometry method, we study the dynamic elastic modulus of the oxide-coated LM droplets. We have created our dataset from LM’s pendant drop shape parameters and trained different models for comparison. We have achieved >99% accuracy with all models and added versatility to work with other fluids. The best-performing model was leveraged further to predict the approximate values of the nonaxisymmetric LM droplets. Then, we analyzed LM’s elastic and viscous moduli in air, harnessing oscillation-induced pendant droplets, which provides complementary opportunities for interfacial studies alternative to expensive rheometers. We believe it will enable more fundamental studies of the oxide layer on LM, leveraging both symmetric and perturbed droplets. Our study broadens the materials science horizon, where researchers from ML and artificial intelligence domains can work synergistically to solve more complex problems related to surface science, interfacial studies, and other studies relevant to LM-based systems.

Melt‐extruded hollow thermoplastic fibers are a new class of materials for advanced applications, i.e., robotic clothes, stretchable touch and twist sensors, and programmable knitted textiles. Under large mechanical deformation (strain), such materials exhibit hyperelasticity. However, fundamental knowledge of strain‐energy density harnessing integrated computational materials engineering (ICME) has remained untapped for hollow fibers. Due to this key knowledge gap, most emerging applications demand iterative and costly approaches to producing and studying hollow fibers. Herein, a data‐driven pathway harnessing the ICME is introduced to study, predict, and optimize the hyperelastic behavior of hollow fibers. MCalibration software is used to calibrate the material properties of the fibers utilizing the Three‐Network Model (TNM) and emulated experimental stress–strain behavior in a finite‐element‐based multiphysics environment (COMSOL) with 99.99% confidence. The feasibility of predicting strain‐energy density is shown to modulate shape and geometries for new understandings without running cost‐incurring melt extrusions or experiments. Furthermore, the strain‐energy density is leveraged as a tool to attach fibers on fabrics that otherwise need iterations. As a proof‐of‐concept, fibers to fabrics are attached for wearable microfluidic demonstrations. This ICME approach can be extended to design the next generation of pre‐programmed, undiscovered functional devices fabricated from hyperelastic hollow fibers.

Cotton threads and fabrics are the most used textile materials and have garnered widespread interest for smart textiles to capture human-centered cyber-physical and human-health-related bioanalytical data. Cotton threads are sewn (manually or digitally) into fabrics to achieve functional and fashion stitches that soften or stiffen the base fabric. There has been limited investigation into the influence of a single stitch on the mechanical properties of knitted cotton fabric. Such understanding may become critical to producing optimized textile-based composites/smart materials involving sewing operations. While stitching operations are investigated in numerous ways to produce a range of smart wearables, herein, we demonstrate the rheological modification of base cotton fabric induced by two types of singular stitches (straight and zigzag). We have sewn simple straight and zigzag cotton stitches to investigate the rheological modification of the base cotton fabrics. Uniaxial stress-strain experimental data, combined with constitutive modeling (i.e., three-network model, TNM) obtained from the calibration software (MCalibration), revealed the feasibility of a data-driven approach to investigate the rheological parameters. Our experimental analyses, combined with the calibrated data, suggest a 99.99% confidence in assessing the influence of a single stitch on knitted cotton fabrics. We have also used distributed strain energy to analyze the mechanics and failure of the base and stitched fabrics. Our study may enable the design and study of integrating smart threads in cotton fabrics to produce smart wearables, e-textile, biomedical and e-fashion textiles.

Numerous complex methods have been reported to generate heterogeneously wettable surfaces in the literature. These surfaces are well-sought in energy, water, health care, separation science, self-cleaning, biology, and other lab-on-chip applications. While most of the demonstrations of heterogeneous wettability rely on a series of complex fabrication protocols, we reveal an unconventional approach to achieving heterogeneous wettability through three simple steps (i.e., patterning, silanizing, and rinsing). Here, we show heterogeneous wettability on a planar substrate harnessing (a) the wetting and dewetting behavior of nano-textured conductive surface patterns of Gallium alloys and (b) interfacial chemical reactivity of the native surface oxides of these alloys in the presence of chloro-silane vapor. Alloys of Gallium (eGaIn and others) have emerged as one of the most promising soft metals for the fabrication of soft functional devices harnessing their surface oxides, mostly Gallium Oxide (Ga2O3). These alloys can be 2D patterned utilizing the wetting behavior of the Ga2O3, which seems impossible due to the high surface tension of the bare metal. We utilized such 2D metal patterns on the planar glass surface and exposed the patterns in chloro-silane vapors to begin our study. Chloro-silanes can alter the surface energy of different substrates (i.e., glass, silicon wafer) to offer hydrophobicity and releases Chlorine vapors which etch Ga2O3 that induces the delamination. A simple DI water rinsing operation reveals a thin hydrophilic layer on the pre-patterned area that we utilized for an open-ended microfluidic demonstration, as well. We confirmed hydrophilicity through contact angle measurements; elemental compositions, and Chlorine's presence through energy dispersive spectroscopic (EDS) analyses. We believe such an unconventional approach of achieving heterogeneous wettability has the potential for fundamental studies related to bioinspired and biomimetic applications.

The crystallization and the hydrogen absorption properties of a Ni32Nb28Zr30Fe10 melt spun ribbon were investigated. X-ray diffraction measurements reveal that a small fraction of the ribbon is in a crystalline state, whereas the main component is amorphous. The bulk crystallization process of the alloy ribbon occurs in two steps above 770 K, as measured by differential scanning calorimetry. At each step of the crystallization process, an unusually low activation energy of the order of 180 kJ/mol, was observed. Hydrogen absorption pressure-composition isotherms measured between 598 K and 673 K showed that the enthalpy of hydrogenation is quite high (similar to 85 kJ/mol), as compared to that of analogous ribbons. The isotherms of these ribbons do not exhibit any plateau, similarly to other amorphous materials, but they exhibited extremely slow kinetics for hydrogen absorption. To simulate the local atomic structure involving cluster formation in amorphous Ni32Nb28Zr30Fe10 alloy, DFT-MD approach was used to construct an amorphous supercell of this alloy with 108 atoms. Calculations predicted that a fully amorphous structure of Ni32Nb28Zr30Fe10 can form. The low activation energy of crystallization observed before hydrogenation is due to the presence of only 3 full icosahedra without any Ni-centered icosahedra, that could provide resistance against crystallization. Moreover, a cluster analysis of the Ni32Nb28Zr30Fe10 alloy after hydrogenation showed interaction of hydrogen atoms with only two icosahedra out of four found in this case, and this could be the probable reason for the extremely slow kinetics of hydrogen absorption. (C) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Individualized and anatomically correct computational models of the brain can be leveraged to improve knowledge of drug dispersal following simulation of drug delivery. Using a patient’s magnetic resonance image (MRI) scans, we were able to reconstruct the pial surface of the brain of the left hemisphere with strong anatomic accuracy. We then established the major internal features, including the lateral ventricle, a tumor, and drug delivery catheters. These were able to include relevant tissue characteristics such as porosity and permeability in the Multiphysics platform COMSOL to create a platform for brain modeling. To test the performance of this platform, we simulated direct drug infusion in both a healthy patient brain and a diseased patient model, focusing on glioblastoma (GBM). Using this platform, we simulated perturbed convection enhanced delivery of a cancer medication (similar to temozolomide (TMZ) but modeled using methylene blue) to the tumor. Consequently, with our patient derived model, we are able to simulate solute dispersal and fluid flow representative of in vivo conditions.

Bioprinting technologies utilize hydrogel-based biomaterials to more accurately depict in vivo physical conditions within in vitro studies, yet, manufacturing the human brain from soft, poroelastic hydrogels remains a fundamental challenge. Conventional manufacturing routes to fabricate hydrogel brain models using techniques, i.e., 3D printing, seems challenging. This study aims to demonstrate an inverse replica molding fabrication technique that can overcome these challenges while maintaining the complex shape of an individual subject’s brain in a miniaturized model—allowing for a more robust hydrogel model that can capture the interactions between diffusing molecules and brain boundaries. This is done by taking a subject’s magnetic resonance imaging (MRI) scan and reconstructing the outer pial surface into a mesh surface. The mesh was then converted to an STL and printed out using an extrusion printer. A silicon mold was made from this print into which agarose was gelled. Once fully gelated, the synthetic gel brain was then carefully removed. Two infusion trials were run in the gel brain, each using a different infusion site. Then a diffusion profile was established and compared to a simple gel infusion model. The result shows different diffusion profiles at each location and between the simple and complex models. This model can better represent the interference the complex shape of the brain has on particle movement compared to simple gel models.

Nanoporous membranes have gained considerable interest in drug delivery1, ion transportation2, micro/nanofluidics3, molecular sensing4, and separation science5. Artificial kidneys, also known as dialyzers, reject pathogens and other unwanted substances from the blood, utilize hundreds of soft and nanoporous polymeric microtubes, and slowly become a burden to the environment with the growing number of dialysis patients worldwide. We demonstrate the fabrication of nanoporous conductive wires utilizing empty polysulfone microtubes collected from expired and unused artificial kidneys, also known as medical wastes. Injecting a fluidic, highly conductive, and room temperature liquid alloy (eutectic gallium indium-eGaIn$_6$, 75% Ga, 25% In) into microtubes of a twenty years old dialyzer, here, we have revealed a new class of nanoporous and conductive functional materials. These conductive fibers upcycle a medical waste, do not require expensive and conventional fabrication processes, and still provide the quintessential metal-oxide/metal framework due to the presence of the native surface oxide (i.e., Gallium Oxide, Ga2O3) of eGaIn at the nanoconfinement (i.e., nanopores) for nano/biosensing. We harnessed these new materials to sense and differentiate microliter volumes of deionized (DI) water, 1M hydrochloric acid (HCl), and 95% ethanol (EtOH), leveraging their electrical signatures. This new class of soft nanomaterials has the potential to become the paradigm-shift platforms for the next-generation of biomedical, bioelectronics, nanoelectronics, and sensor devices.

ABSTRACTPrecision drug delivery for optimized therapeutic targeting requires knowledge of momentum transport and molecular diffusion of molecules within the patient’s interstitial tissue, especially for tumor treatment within the brain. Dispersion in the interstitial space is impacted by delivery method, tissue material properties, individual-specific fluid flow, and particle size of the input solute. Knowledge of a drug’s dispersion allows for optimizing solute delivery, concentration, and flow rates to maximize drug distribution and biomarker recovery. For delivering drugs, increased knowledge of drug location after delivery can improve therapeutic treatment by optimizing the dosing of healthy and unhealthy tissue. Finite element methods (FEM) tools, such as COMSOL Multiphysics, can simulate molecular distribution inside-individual specific shapes and porous material properties. Furthermore, an additional unmet need is delivery methods that can be adjusted to manipulate diffusion regions through tissue via techniques such as directed flow. This would be especially valuable in targeted drug delivery within tumors to increase the cancerous surface area covered while limiting damage to surrounding tissues. In this project, the directed flow was induced by perfusing the injected solution at an input probe while withdrawing fluid at an output probe, enabling targeted flow through the desired region. FEM computation faithfully replicated these conditions and could be used to determine the effective concentrations perfused over the region of interest. We leveraged COMSOL Multiphysics to perform a computational study simulating convection-enhanced delivery (CED) with an output probe pulling the concentration profile over the region of interest. This simulation system can be applied to therapeutics targeting, vaccine subcutaneous injection, and waste and media diffusion in tissue engineering.

Soft and stretchable sensors have the potential to be incorporated into soft robotics and conformal electronics. Liquid metals represent a promising class of materials for creating these sensors because they can undergo large deformations while retaining electrical continuity. Incorporating liquid metal into hollow elastomeric capillaries results in fibers that can integrate with textiles, comply with complex surfaces, and be mass produced at high speeds. Liquid metal is injected into the core of hollow and extremely stretchable elastomeric fibers and the resulting fibers are intertwined into a helix to fabricate capacitive sensors of torsion, strain, and touch. Twisting or elongating the fibers changes the geometry and, thus, the capacitance between the fibers in a predictable way. These sensors offer a simple mechanism to measure torsion up to 800 rad m−1—two orders of magnitude higher than current torsion sensors. These intertwined fibers can also sense strain capacitively. In a complementary embodiment, the fibers are injected with different lengths of liquid metal to create sensors capable of distinguishing touch along the length of a small bundle of fibers via self‐capacitance. The three capacitive‐based modes of sensing described here may enable new sensing applications that employ the unique attributes of stretchable fibers.

This paper describes the utilization of vacuum to fill complex microchannels with liquid metal. Microchannels filled with liquid metal are useful as conductors for soft and stretchable electronics, as well as for microfluidic components such as electrodes, antennas, pumps, or heaters. Liquid metals are often injected manually into the inlet of a microchannel using a syringe. Injection can only occur if displaced air in the channels has a pathway to escape, which is usually accomplished using outlets. The positive pressure (relative to atmosphere) needed to inject fluids can also cause leaks or delamination of the channels during injection. Here we show a simple and hands-free method to fill microchannels with liquid metal that addresses these issues. The process begins by covering a single inlet with liquid metal. Placing the entire structure in a vacuum chamber removes the air from the channels and the surrounding elastomer. Restoring atmospheric pressure in the chamber creates a positive pressure differential that pushes the metal into the channels. Experiments and a simple model of the filling process both suggest that the elastomeric channel walls absorb residual air displaced by the metal as it fills the channels. Thus, the metal can fill dead-ends with features as small as several microns and branched structures within seconds without the need for any outlets. The method can also fill completely serpentine microchannels up to a few meters in length. The ability to fill dense and complex geometries with liquid metal in this manner may enable broader application of liquid metals in electronic and microfluidic applications.

We present a crossed dipole with frequency and polarization agility using electrochemically actuated liquid metal. For the first time, this antenna uses multidirectional displacement of liquid metal to enable frequency and polarization reconfiguration without the need for mechanical pumps or semiconductor devices. The dipole arms are composed of liquid metal that can be shortened and lengthened within the capillaries by applying DC voltages to each arm. Varying the lengths of the dipole arms generates two independently tuned, linearly polarized resonances from 0.8 to 3 GHz and polarization that can be switched from linear to circular over a portion of this band (0.89-1.63 GHz). Moreover, a circuit model predicts the circular polarization frequency from the input impedance. Simulation and experimental results validate the antenna concept and analysis techniques.