The overall goal of this experiment is to probe the structure and dynamics of interfacial water at the atomic scale using submolecular resolution imaging, molecular manipulation and single bond vibrational spectroscopy. This method can help answer fundamental issues about water science such as identifying the hydrogen bond and directionality of water and probing the hydrogen bond dynamics and vibrational spectroscopy of water molecules as shown on solid surfaces. The main advantage of this technique is that STM combines the capability of sub-angstrom Spatial resolution, atomic manipulation, and single bond vibrational sensitivity. Except for providing insight into the structure, dynamics, and nuclear quantum effects of surface water, it can also be applied to more complex and realistic hydrogen bond system such as confined water, buck eyes, multilayer water, and water hydrogen systems. To begin, follow along with the accompanying text protocol to clean the gold 111 single crystal using cycles of argon ion sputtering and subsequent annealing. Deposit sodium chloride onto the surface of the gold crystal and then transfer it to the scanning stage of an STM set up. Using standard STM techniques, check the coverage and size of the bi-layer sodium chloride 001 eye lens on the gold 111 substrateaight. The results should look similar to those shown here. Next purify water using freeze, pump, thaw cycles to remove any remaining impurities. Pump the gas line to 10 to the minus five pascals and then freeze the liquid water with liquid nitrogen. Now close the bellows sealed valve and leave the gas line under vacuum. Then open the diaphragm sealed valve and let the water vapor fill in the gas line. Then decrease the temperature of the sample to five kelvin. Open the leak valve slowly to make the pressure of the ultra high vacuum STM chamber increase to two times 10 to the minus 10th millibar. Next open the shutter. Dose the water molecules onto the gold supported sodium chloride surface for one minute. Then close the shutter and the leak valve. At this point, check the coverage of water molecules on the surface using standard STM techniques. Expect to see isolated water monomers on the sample surface. To begin, fabricate an electrochemically etched tungsten tip, etch it in three molar sodium hydroxide and then clean it using distilled water and ethanol as described in the accompanying text protocol. Next apply voltage pulses and controlled crashing procedures on the STM tip until the atomic chlorine atoms of the sodium chloride surface are resolved. Then position the STM tip over the center of one of the chlorine atoms and bring the bare tip close to the sodium chloride surface in proximity with the set point. Next retract the tip to the original set point and scan the same area. Check that a chlorine atom has attached to the tip by visualizing both the improved resolution and the missing chlorine atom in the STM image. To begin, set up the biospectroscopy module. Select the current, the differential conductance, the derivative of the differential conductance channels. Then adjust the setting time to 50 milliseconds and integration time as 300 milliseconds. The spectro tunneling spectroscopy and the inelastic electro tunneling spectroscopy are acquired simultaneously using a lock in amplifier by modulating the first and second harmonics of the tunneling current respectively. Increase the integration time and sweep times as needed to obtain smooth spectra. Then tune the Z offset to take the biospectroscopy at different tip heights. Next open lock in, modulate the bias, and demodulate the current. Set the modulation frequency as a few hundred hertz and the modulation amplitude as five to seven millivolts. After setting the modulation frequency, make sure there is no mechanical and electronic noise at the set point frequency and the corresponding second harmonic frequency. To set the first harmonic phase, start by switching to the Z-Controller module. Set the tip lift to 10 nanometers and turn off the feedback, then switch to the lock in module and turn on the lock in button. Click on the first harmonic auto phase and record the phase. Repeat the auto phase at least five times and take the average. Then subtract 90 degrees from the averaged phase to get the phase of the junction. Next set the second harmonic phase. To accomplish this, position the STM tip on the gold substrate and start the biospectroscopy sweep from minus one volts to one volt. Then select the differential conductance channel LI X 1, and the function dY/dX which together show the derivative of DI over DV spectrum. Find a prominent peak feature in the spectrum and set the corresponding energy as the bias. Next turn on the lock in and keep the STM system in tunneling mode. Click the second harmonic auto phase at least five times and take the average. To begin, scan the water monomer with the chlorine atom tip. Then position the tip on the sodium chloride surface and take the biospectroscopy as the background signal. Next position the tip on the water monomer and start the biospectroscopy sweep. If the dI/dV and second derivative spectra of water are featureless, simply follow the background sodium chloride coated surface, then decrease the tip height by tuning the Z offset until the vibrational features emerge in the spectra. To begin the construction of a water tetramer, first scan for an area containing four water monomers and position the chlorine tip on top of a monomer at the set point of V equals 100 millivolts and I equals 50 picoamperes. Decrease the height so the voltage is 10 millivolts and the current is 150 picoamperes. This will enhance the tip water interaction. Next move the chlorine atom tip along the predesigned trajectories. Then retract the tip to its initial set point and rescan the same area to check that the water dimer is formed. Repeat this process until a water trimer and eventually tetramer are formed. The tetramer contains two degenerate chiral states. Anti clockwise, and clockwise H bonded loops. As the chlorine atom terminated tip is lowered, the representative current bounces around as the tetramer changes between the clockwise and anticlockwise states. When retracting the tip to the original height, the tetramer shown here is left in the anti clockwise state. The switching rates between clockwise and anti clockwise can be extracted from the current versus time trace to show the lifetime distribution of a tetramer. The clockwise tetramer can be fitted by an exponential decay. To explore the mechanism of the proton transfer in the tetramer, the effect of full and partial isotopic substitution on the chirality switching is described here. Strikingly the chirality switching rate of the four water tetramer is substantially reduced by replacing a single water molecule with deuterium oxide. Almost to the same level of the four deuterium oxide tetramer. While performing the procedure for manipulation and vibrational spectroscopy, it is important to remember to functionalize the STM tip with a single chlorine atom. This technology provides surface signs an ingenious method to explore the detailed topology of hydrogen bond network and the quantum motions of protons in water clusters at an atomic scale. After watching this video you should have a good understanding of how to identify the hydrogen bond directionality via opto imaging. You should also understand how to push the vibrational spectroscopy down to a single bond limit and how to manipulate water molecules in a controlled manner.

Traditionally we've used the tester to study non-living tissues to calculate friction coefficients but we are significantly expanding the tester's capabilities to test living tissues and to evaluate biological interactions. The friction testing device delivers reciprocal translating motion and compressive load to contacting surfaces of living tissue explants. The device is modular, allowing for the testing of various biological counterfaces. The method could provide insight into how frictional forces affect the mechanical and mechanicobiological responses of living cartilage and synovium, which may lead to new strategies for maintaining joint health. Begin by harvesting the juvenile bovine synovium. Using a scalpel blade, trace the outline of the synovium region of interest. Using forceps, grasp one end of the synovium and gently lift to stretch the synovium distal to the underlying bone. Use a scalpel blade to remove the synovium from the bone and place the tissue in appropriate culture media or testing bath solution. Then harvest the juvenile bovine cartilage by securing the tibia in an adjustable holder. Remove the meniscus carefully while avoiding contact with the cartilage surface. On the outer edges of the tibial plateau, use a box cutter to cut perpendicular to the cartilage toward the bone. Cut completely through the cartilage to make straight edges or sides. Remove excess tissue. On the outside edges, use the box cutter to make a clean cut at the interface between the bone and the cartilage. To remove the tibial strip from the plateau surface, gently insert a flathead screwdriver below the cut and gently rotate to loosen the articular cartilage from the subchondral bone. As the sample loosens, slowly push the screwdriver forward until the cartilage strip detaches from the bone. Ensure that the screwdriver is pushed towards the bone, not the cartilage. Using a box cutter, cut the tibial plateau surface to produce rectangular samples of desired size and thickness. Place tissue in appropriate culture media or testing bath solution. If the tibial strip is used as the bottom counterface, remove the detachable magnetic base and glue a 60-millimeter diameter Petri dish to the top surface of the detachable base. With the Petri dish glued in place, attach the detached base to the fixed base and mark the Petri dish to indicate a sliding direction. Apply a small amount of cyanoacrylate to the center of the dish. Align the tibial strip with the sliding direction of the stage. Gently press the cartilage strip onto the dish. Restore the removable magnetic base to its paired fixed base in the friction tester. Fill the Petri dish with the desired testing bath solution. If the synovium is used as the top counterface, remove the loading platen and support rod from the friction tester. Place the synovium on top of the circular platen. To secure the synovium, spread an O-ring over its circumference. Using forceps, gently pull at the synovium to stretch tissue taut and flat beneath the O-ring. Trim excess tissue with surgical scissors. Restore the loading platen and support rod to the friction tester. Adjust the vertical height of the loading platen such that the synovium hovers over the bottom counterface and is submerged in the testing bath. Insert the mounted specimens into the friction tester device. Open the analog data build MF DAQ. Initialize Load PID and Trigger Dynamic Caller Windows in the program. Run the analog data build MF DAQ and initialize load PID window by pressing the Run button. Navigate to the Stepper tab in the Trigger Dynamic Caller window. Specify the acceleration, speed, and distance of the translation stage in the user input boxes. To input the test duration, click on the Open Folder button at the bottom right of the Time State table and select the Stepper Time Index file path. Then specify the test duration again in the Voice Coil tab. Select the Voice Coil Index file path by clicking on the Open Folder button at the bottom right of the Time State table and select the file. This must be performed whether the voice coil is used or not. Apply the normal load. If using deadweights, place desired weights on the linear bearings above the loading platen. Ensure that the load applied plus the weight of the loading platen and support rod do not surpass the load cell-rated capacity. Select the path and file name for data storage using the Open Folder button to the right of the Right to File box. Save the file with a txt extension. Center the bottom counterface underneath the top counterface and set this as the zero X position. To do this, run the Trigger Dynamic Caller window by pressing the Run button. In the Stepper tab click on the Home button to move the stage to the last saved zero X position. If counterfaces are not aligned, move the stage by clicking the green left and right arrow buttons. When the desired location is reached, click on the zero button to save the current stage location as the new zero X position. Stop the Trigger Dynamic Caller window by clicking on the Stop button. Once the top and bottom counterfaces are centered, initiate friction testing of the samples by starting the cyclic movement of the stage. Once the stage moves, slowly bring the top counterface into contact with the bottom. Let the test run, collecting the friction testing data. After the desired testing duration, stop the test by pressing the Stop button and by unloading the specimens by raising the top counterface and moving it out of contact with the bottom counterface. Use the custom code to calculate the friction coefficient and the hysteresis per cycle. Ensure a single folder contains all relevant files. Open the Friction Cycle run. m file. Click on the Run button in the script. Select the raw data file to analyze and the desired save location. The friction coefficient and hysteresis plots will be output by MATLAB. A synovium-on-cartilage configuration was used to friction test juvenile bovine explants where the synovium was mounted on a 10-millimeter diameter acrylic loading platen such that the intimal layer would be in contact with the underlying cartilage. A tibial strip was used as the cartilage counterface. An effective friction coefficient was calculated from the average of FT divided by FN over each reciprocating cycle and then plotted against test duration to yield a friction coefficient-versus-time plot. For each test, friction coefficient values were averaged over the entire test. In a PBS testing bath, the average friction coefficient values increased as the contact stress increased. Conversely, the average friction coefficient values remained similar as the contact stress increased in a bovine synovial fluid bath. Remember to start collecting load data before bringing the surfaces into contact. This ensures a proper tare load can be calculated. Tissue and lubricating bath components can be assessed before and after testing to evaluate the biological changes imparted by a given experimental regimen.

The overall goal of this procedure is to test the frictional properties of phyllosilicates, with faults sheared in the in-situ geometry, and to show that this friction is significantly lower than friction of powders obtained by the same material. During the long-term evolution of tectonic faults, numerous geological studies have documented fluid-assisted reaction softening, that promotes the replacement of strong and granular minerals with phyllosilicates. In particular, fracturing processes along faults increase permeability, and facilitate the influx of hydrous fluids into the fault zone. Fluids react with fine-grained rock, promoting dissolution of the strong minerals like quartz, feldspar and calcite. They become platy phyllosilicates and form foliated microstructures, like the one presented here in green. Slip along the phyllosilicates from the micro-scale is transmitted to the entire fault zone via the interconnectivity of the phyllosilicate-rich shear zones. This is an example of the continuity of the phyllosilicate shear zone at the outcrop scale, that can be extended up to crustal-scale faults with thicknesses of more than 100 meters. Along phyllosilicate-rich fault like this one, the tonic shearing has produced the phyllosilicate alignment, producing this fault rock anisotropy. In order to take into account the role of anisotropy in frictional properties of the fault, we have to collect the right rock samples. To do that, we have to collect a representative rock sample, and within the outcrop, we select a portion where the kinematic indicators are best preserved. And then we use a chisel and a hammer to collect the rock sample. Once the rock sample has been collected, we mark the sense of shear, and then we bring the rock sample to the lab for the experiment. With this procedure, we cut the rock samples to obtain wafers that fit the forcing blocks of the rock deformation apparatus. This is usually achieved in 2 steps. In the first step, we use a standard laboratory saw to obtain rock samples that are slightly larger than the forcing blocks. Secondly, we use a high precision rotary blade, or a hand grinder, to shape the wafers so they're 5 by 5 centimeters in area, and about 1 centimeter in thickness. From the same piece of rock, we use a disk mill to obtain a granular material that is sieved to reach the desired grain size, usually below 125 microns. The 2 identical wafers are mounted on stainless steel forcing blocks with a nominal frictional area of contact of 5 by 5 centimeters, and then are assembled with a central forcing block to compose the symmetric, double-direct configuration. In the same way, the powders are used to construct 2 identical layers whose thickness is about 5 millimeters, and whose area of contact is 5 by 5 centimeters. These are then used to compose a similar double-direct shear configuration. At this point, the double-direct shear configuration is positioned within our biaxial apparatus, and we're ready to start the friction experiment. We use a servo-controlled hydraulic piston to apply and maintain a constant normal stress on the rock sample. Then by advancing the vertical ram, we apply shear stress at constant sliding velocity;it is usually 10 microns per second. Most of the experiments are characterized by an initial strain hardening, where the shear stress increases rapidly during elastic loading, followed by shear stress at steady state. The shear stress to normal stress ratio gives us the friction coefficient. At the end of the friction test, we carefully extract the experimental fault, we impregnate the rock sample with epoxy resin, we cut the sample in a direction parallel to the sense of shear, and we build thin sections from the cuts for microstructural studies. We use an optical microscope to characterize the bulk faults on the microstructure. We analyze microstructures with a scanning electron microscope to investigate the main deformation processes. We use a transmission electron microscope to obtain details about deformation processes down to the nanoscale. In a diagram of normal stress versus shear stress, both the solid foliated wafers and the powder samples plot along the line, consistent with a brittle failure envelope. But the solid wafers have a friction value significantly lower than the powdered analogs. In particular, the powders show friction of about 0.6, whereas the foliated rocks have significantly lower values. At each normal stress, the foliated rocks have a friction coefficient that is 0.2 to 0.3 units lower than the powders made from them. Microstructural studies of the tested rocks show that the low friction of the solid wafers is due to sliding along the pre-existing, very fine-grained foliations made of phyllosilicates. TEM images show that slip is mainly accommodated by fracturing, translation, and rotation along the phyllosilicates, with frequent inner layer delamination. In contrast, experiments conducted on powders indicate that much of the deformation occurs along zones effected by fracturing and grain size reduction. This results in higher values of friction. This is a summary of the frictional properties of natural, phyllosilicate-rich tectonic faults from different tectonic environments. Data show that friction is in the range of 0.1 to 0.3, and this friction is significantly lower than the traditional Byerlee value of friction obtained from a large gamut of rock types, that are predominantly made of granular mineral phases. To summarize, our friction experiments show that foliated samples are extremely weak compared to their powdered equivalents. Microstructural studies indicate that the lower friction, or in other words, fault weakness of the foliated fault rocks is due to the reactivation of the pre-existing natural phyllosilicate-rich surfaces. These surfaces are absent in the powdered samples since the sample preparation step destroys them. Our friction tests on solid foliated samples show that low friction, and therefore fault weakness, can occur in cases where weak mineral phases constitute only a small percentage of the total fault rock, implying that a significant number of crustal faults are weak.

As a progressive and multifactorial disease, OA triggers structural and functional changes in the articular cartilage.Throughout the course of OA, impairments in mechanical features are accompanied by structural and biochemical changes at the surface of the articular cartilage27,31. The earliest pathological events occurring in OA are proteoglycan depletion coupled with collagen network disruption32,33,34. Such early subtle surface changes are difficult to pinpoint and identify with bulk testing, because the mechanical behavior is averaged over the whole tissue depth. Additionally, a still unaddressed question is whether functional changes at the organ and tissue levels relate to micro- or nano-scale structural and functional changes. To this end, AFM is considered to be one of the most sensitive methods, capable of detecting the earliest biomechanical changes occurring with OA onset7. It allows stiffness measurements on both micro- and nanometer scales in native samples, providing information on the mechanical properties of articular cartilage35,36. In this protocol, using micro-AFM indentations, we measured the elastic properties of healthy and osteoarthritic articular cartilage human explants. The results showed that the cartilage explants are highly representative of early local OA events with a notable gradual decrease in stiffness occurring in pattern-specific cartilage explants. Furthermore, the results are in line with previous published research that showed a notable stiffness decrease alongside the cellular pattern organization23,24,27,37. Corroborated native human models that mimic various aspects of OA pathogenesis and progression are currently needed to address the shortfalls of translational research and the challenges of translating in vitro data to a clinical setting.To date, no model can accurately represent the complex native human cartilage compartment, let alone the age-related joint tissues which are prone to OA in response to disease-initiating stimuli38. The most commonly used explant-based models thus far were of bovine or cattle origin and applied either a strong inflammatory cytokine treatment or mechanical loading39,40,41.This protocol, on the other side, demonstrates how to generate small (4 mm x 1 mm) explanted disc-shaped human cartilage samples, which are indicative of the individual stages of specific OA events. The cartilage explants are sorted and stage assigned using the cellular spatial organization as an image-based biomarker30,42. Since early changes in biomechanical properties can be already identified and quantified as soon as double strings start arising23,27, at a stage where the cartilage surface still appears macroscopically intact26, this explant-based model allows the investigation of a local native cartilage compartment and may provide insightful information on early OA. Furthermore, this cartilage model could be useful in investigating the cells and matrix response to mechanical and inflammatory alterations in a 3D native local habitat38,39. Being relatively simple and easy to generate, these cartilage explants can be also used to study OA heterogeneity, which is a limiting factor in developing and testing disease-modifying OA drugs43. It also has to be noted that scalability and dependency on patients undergoing joint replacement surgery are two of the model's shortcomings. It is well known that articular cartilage presents a peculiar behavior depending on the scale level that is tested. As indicated by Loparic et al., at the micro-scale, the cartilage behaves as a nonstructured and uniform material35, and such an approach gives an approximation of localized overall cartilage stiffness. With respect to whether micro- or nano-indentations are better suited, a 2004 study by Stolz et al.44 compared both micro- and nano-scale indentations in assessing the structure-mechanical properties of articular cartilage. The authors emphasized that for micro-scale spherical indentation of the articular cartilage, the nano-scale fine structural components (i.e., individual collagen fibers and proteoglycans) commonly share the task of load bearing. In such, the aggregate mechanical properties differ markedly from those of the individual nanocomponents. The same authors proposed that a combination of micro- and nano-indentations could be used to assess the overall local stiffness profiles of articular cartilage, as well as the stiffness related to the fine structural components44. Numerous AFM-based indentation experiments have used sharp pyramidal cantilever tips (radius = 15-20 nm)22,36,44 for assessing cartilage mechanics. Although the nanoindentations with sharp cantilevers are currently regarded to be more suitable for assessing the finest mechanical properties, spherical cantilever tips produce results that are more consistent and easier to model and interpret when testing soft biological samples44,45. Furthermore, Stolz et al. demonstrated that AFM nano-indentations of enzymatically (i.e., elastase) degraded articular cartilage are not possible because the tissue becomes so sticky that tip-sample adhesion dominates the force-distance curves, rendering the data unfeasible44. In the present AFM measurements, a cantilever with a spherical cantilever tip of 5 µm radius was used. The cantilever choice was motivated by the intention to average the mechanical properties of the tissue over a fairly large surface while minimizing the inflicted damage on the cartilage surface. The relationship between the cantilever-applied force and the resulting sample indentation was fitted with the Hertz fit model. When using spherical indenters, the Hertz fit model is recommended, with the attractive forces acting between the cantilever tip and the sample surface being neglected46. The equations for the Hertzian model are shown in Eq.1 and Eq.2. Eq.1 Eq.2 Where F = force; E = Young's modulus; v = Poisson's ratio; δ = indentation; a = radius of contact circle; and Rs = radius of sphere. The model ultimately computes the cellular/tissue elasticity47, formally expressed as the Young's modulus (E). The Hertz fit model takes into consideration several characteristics such as the tip shape and size, indentation, and sample deformability. If these requirements are not ideally met, the model may provide an inaccurate estimate of the Young's modulus46. The Hertz fit model assumes that the strain and elastic stress depend linearly on the elastic modulus, which implies that the indentation in the sample remains much smaller than the sample thickness itself46. This assumption was easily met in this setup, where the cartilage explants had a 1 mm thickness compared to indentations of few micrometers. Articular cartilage can be modeled as a porous viscoelastic material48,49. The viscoelastic behavior results from friction between the intracellular/cytoplasmic or matrix constituents such as molecules, organelles, and the collagen-proteoglycan network50,51. As the name implies, viscoelastic materials combine two distinct properties: viscous-the material deforms slowly when subjected to an external load-and elastic-the material returns to its initial configuration once the applied load is removed52,53. The viscoelastic behavior is manifested as a hysteresis between the approach (extended) and retraction curves in the force-distance curves46,52, similar to the ones obtained in this study (Figure 4C). Furthermore, a characteristic of viscoelastic materials is that their mechanical properties depend on the deformation rate, with the material's stiffness increasing with the rate at which loading is applied (indentation speed)54. Thus, by selecting different loading rates, a family of force-distance curves is generated, each of which represents the mechanical properties of the tested sample at each loading rate52. So, when attempting to compare the outcomes of various works, it is critical to take all of the indentation parameters into account. Overall, when measuring at the micrometer scale (as in this study with a 5 µm spherical cantilever tip), articular cartilage behaves as a nonstructured and uniform material, generating a cumulative elastic modulus that includes both elastic and viscous contributions to stiffness due to the poroviscoelastic nature of the tissue35. Another assumption of the Hertzian model is that the indentation depth is lower than the radius of the spherical cantilever tip55. The indentation depth represents the maximum displacement of the cantilever tip after first contact with the sample. At maximum load, the maximum indentation depth is the overall displacement of the sample and the cantilever tip. Bueckle's guideline states a maximum indentation depth of 10% of the overall thickness of a sample with the same structure throughout56, else, the results vary according to the depth-to-thickness ratio. For a cantilever tip radius of 5 µm, the cartilage explants in this study were indented at 1.1 µm on average, with a few peaks of 3 µm in a few instances, particularly for the highly degenerated cartilage explants.In this case, a compromise was sought, as, in the experimental setting, relatively high forces associated with large indentations are required to neutralizethe surface irregularities of degenerated cartilage.A milder indentation would result in the examination of superficial fibrillation and collagen fissuring, both of which are common features of highly degenerated cartilage57. Crucial for the Hertz fit model is also the correct identification of the point at which the cantilever tip comes into direct contact with the sample, generically termed the contact point. However, this might turn out to be problematic when indenting too sticky or too soft samples, as it may result in multiple probe-sample contact points58,59. In fact, as nicely emphasized by A-Hassan et al., for soft biological tissues, the accurate determination of the point of contact is one of the most vexing problems60. This effect was also observed in the native osteoarthritic cartilage explants, as, depending on the stage of degeneration, the tissue surface loses its native mechanical characteristics and is often uneven, presenting superficial fibrillation and clefting (Figure 3B,C). This phenomenon was particularly noted in the cartilage explants where the dominant cellular pattern was big clusters (Figure 2C). These inhomogeneities in the cartilage surface might lead to multiple probe-sample contact points and, thus, erroneous results. Vast deflections were observed in some cases, followed by a rapid recovery of the baseline before the final stretch of the force-distance curve (Figure 5A). This could be attributed to a large obstacle in the cantilever tip's path (e.g., advanced fibrillation areas with fraying and splitting cartilage). In other instances, the final slope of the force-distance curve was scattered with smaller irregularities (Figure 5B), indicating contact with successively smaller hindrances (e.g., micro-fibrillation of the tissue). In such cases, the measurement site must be remeasured or even changed to ensure data reliability and reproducibility. To this end, it is also important to carefully inspect the force-distance curve output of the AFM for the correct identification of the contact point. This is a crucial point to be aware of, as it has been shown that an incorrect identification of the contact point by 50 nm results in an incorrect estimation of the value of E by an order of magnitude61. Several studies have begun to use automated approaches to determine the contact point of force-distance curves, with the goal of bypassing subjective user input when estimating the contact point by visual inspection and improving accuracy. This becomes even more crucial when dealing with a large number of force-displacement curves, such as those generated in cell mechanics mesurements47,62. Although several strategies have been proposed to automate the contact point determination47,63,64,65, the optimal strategy is highly dependent on experimental conditions and factors such as the model used to analyze the data, the shape of the probe, the (non-)adhesive mechanical interaction between the cantilever tip and the sample, as well as the (non-)Hertzian behavior of the sample63. Sample drift is another common issue that may cause artifacts and erroneous contact point determination (Figure 3E). It basically means that the sample is not properly mounted in the sample holder (Petri dish) and the sample is moving during the AFM measurements. The effect is particularly pronounced when moving the AFM cantilever to a new measurement site. This aspect can be easily observed during the actual measurements by a sudden change in the focal plane. The resulting force-distance curves typically have a biphasic extended slope, with a mild rise at first, corresponding to the narrowing of the empty space between the bottom of the disc and the Petri dish as the disc is pushed down by the cantilever (see Figure 3E), followed by a firmer inclination in the second of the slope, indicating that the disc is being further indented now that it is in direct contact with the bottom of the Petri dish (Figure 5C,D). To overcome the distortions, one can try to better fix the samples by using an adequate sample adhesive (Figure 3D), keeping the temperature constant by turning off external sources of heat (lights) to avoid thermal drifting, and conducting fast scanning measurements.In the experiments here, we observed a cantilever deflection drift that occurred within the first 15 min of the cantilever's immersion in media (due to sudden changes in temperature). After this time lapse, the drift is usually negligible. As a result, we advise the experimenter to carefully examine the baseline after cantilever immersion and to begin measuring once it has stabilized.The duration of this process can vary greatly depending on the cantilever used. Another critical parameter for any AFM measurement is the set point, which is, simplistically, a measure of the force applied by the cantilever to the sample. For the contact mode (as used in this study), the set point represents a certain deflection of the cantilever. When performing several scans or several site repetitions, like in the protocol here, the cantilever tip can adsorb particles from the sample surface, thus making it sometimes necessary to remove the cantilever, properly clean it66, and then recalibrate before proceeding with the measurements. While AFM micro-indentations provide new and interesting data collection opportunities, in particular in the context of osteoarthritic cartilage, the consistency and reproducibility of the data produced are heavily dependent on several parameters, as outlined above.When using this approach to assess the mechanical changes caused by cartilage tissue degeneration, some pilot measurements on various spatial patterns must first be performed in order to scale up the results to the specific experimental design.Pilot AFM measurements should be performed with the most standardizable procedure taking enough samples (e.g., five discs) of the same pattern to provide an indication of the extent of data variability. This is particularly important when attempting to quantify and assess the earliest relevant OA stiffness changes (i.e., between single strings and double strings, Figure 4A). In fact, in a previous study, using a similar approach, we showed that a sample size of 30 human specimens was required to assess biomechanical changes in the matrix as a function of the spatial organization of the cells37. Furthermore, many of the steps presented in this protocol are susceptible to human error and heavily rely on the operator's experience.Given all of the factors that can influence the actual AFM results, the absolute E values reported in this study are not generalizable and are rather specific to this experimental setup. However, the relationship presented here between the various Young's moduli and the cellular pattern-based cartilage explants (the more pathologic the spatial pattern, the lower the elastic modulus [EM] of the cartilage) is unaffected, as the findings are consistent with previous studies showing stiffness changes as a function of cellular pattern organization23,37. Overall, this step-to-step protocol demonstrates the functionality of standardized 3D native articular cartilage explants, which are not only representative of OA-driven cellular reorganization events ranging from onset to advanced progression but are also associated with a gradual decrease in stiffness. The explants may reflect a reliable biomimetic model for studying OA onset and progression, allowing the testing and development of different treatment modalities ex vivo. The use of such a human explant model in combination with AFM-based biomechanical assessment could result in a paradigm shift for biomedical research and the pharmaceutical industry, paving the way for new ways to identify greatly needed effective OA drugs.

This paper focuses on the two different fabrication processes for the hand lay-up method with low cost. Therefore, two fabrication processes were selected to be carefully described in this paper, which are simpler, easier to master, lower in investment cost, and suitable for production with material modification in laboratories and small-scale factories. During the cure of laminates, high consolidation pressure plays an important role in manufacturing laminates with high quality. The adoption of the traditional WL process without enough external pressure can lead to a high resin volume fraction. High resin volume is one of the major factors that reduce the mechanical properties of laminates. In this work, a fabrication process based on the traditional WL process using a vacuum bag to remove air bubbles and provide pressure is described. In this fabrication process, it is important to control the proportion of materials and sequence of steps. The main factors that affect the mechanical properties of laminates are fiber volume fraction and voids; therefore, protocol steps to remove bubbles, as described in steps 2.1.4, 2.1.8, and 2.1.13, are critical. To compare the mechanical properties of laminates manufactured by different fabrication processes, the tensile test and low-velocity impact tests are carried out. In this study, laminates manufactured by the WLVB process show better mechanical properties, including tensile strength, tensile modulus, and impact energy absorption. The results illustrate that laminates manufactured using the WLVB process have an increase of 18.3% in specific energy absorption, as well as an increase of 16.3% and 14.6% in tensile strength and modulus, respectively. Compared with the WL process, the WLVB process compensates for the insufficient molding pressure through a low-cost vacuum bag, absorbing excess resin from the system to increase the fiber volume fraction and reduce the internal pore content, thereby greatly improving the mechanical properties of the laminate. The quality of laminates manufactured by the WLVB process is better. Due to the pressure exerted by vacuum bag being more uniform, the thickness of the laminate manufactured by the WLVB process is also more uniform. The thickness of the laminate prepared by the WL process using only the weight to provide pressure is uneven, resulting in unstable quality of laminates. The testing results show that the error bars of the tensile and impact properties of the WLVB samples are smaller. It is crucial for the stability of laminate quality to apply uniform pressure during curing. The WLVB process has important driving significance for the composite material production field with small capital investment. Compared with other preparation processes, the WLVB process has several advantages, including simple equipment requirements and uncomplicated process technology, and the products are not limited by size and shape. This process has a high degree of freedom and can be integrated with metal, wood, plastic, or foam. However, the WLVB process also has some limitations, such as its low efficiency and long cycle. Of note, because it is mainly suitable for small batch production, and laminate performances are closely related to the skill level of operators and construction conditions, it is necessary to design and optimize the manufacturing process quantitatively to achieve a high yield.

Abstract An atomic force microscope (AFM) fundamentally measures the interaction between a nanoscale AFM probe tip and the sample surface. If the force applied by the probe tip and its contact area with the sample can be quantified, it is possible to determine the nanoscale mechanical properties (e.g., elastic or Young's modulus) of the surface being probed. A detailed procedure for performing quantitative AFM cantilever-based nanoindentation experiments is provided here, with representative examples of how the technique can be applied to determine the elastic moduli of a wide variety of sample types, ranging from kPa to GPa. These include live mesenchymal stem cells (MSCs) and nuclei in physiological buffer, resin-embedded dehydrated loblolly pine cross-sections, and Bakken shales of varying composition. Additionally, AFM cantilever-based nanoindentation is used to probe the rupture strength (i.e., breakthrough force) of phospholipid bilayers. Important practical considerations such as method choice and development, probe selection and calibration, region of interest identification, sample heterogeneity, feature size and aspect ratio, tip wear, surface roughness, and data analysis and measurement statistics are discussed to aid proper implementation of the technique. Finally, co-localization of AFM-derived nanomechanical maps with electron microscopy techniques that provide additional information regarding elemental composition is demonstrated.

The overall goal of this procedure is to use liquid-cell transmission electron microscropy to investigate the motion of nanoparticles in the solution phase in real time. This method can help answer key questions in the field of nanoscience, for example, about how nanoparticles form self-assembled structures during solvent drying. The main advantage of this technique is that it makes checking nanoparticle motion in real space and real time possible. The implications of this liquid cell technique is tends towards tracking individual motions of nanoparticles that are not shown by conventional methods. Though this method can provide insight into self-assembly of nanoparticles it can be also applied into other models such as oriented attachment of nanoparticles. To begin the procedure, place in a 100 milliliter three neck round bottom flask 17.75 milligrams of ammonium hexacholoroplatinate, 3.72 milligrams of ammonium tetrachloroplatinate and 115.5 milligrams of tetramethylammonium bromide. Add to the flask 109 milligrams of polyvinylpyrrolidone and 10 milliliters of anhydrous ethylene glycol. Equip the flask with a stir bar, a rubber septum and a reflux condenser. Start the stir motor and while stirring at 1000 rpm, degas the reaction flask under vacuum for one hour. Then, under a flow of argon, heat the reaction mixture to 180 degrees Celsius at 10 degrees per minute. Stir the mixture at 180 degrees Celsius for 20 minutes then allow the mixture to cool to room temperature. Transfer the cooled mixture to a 50 milliliter centrifuge tube. Add to the tube 30 milliliters of acetone to precipitate the platinum nanoparticles. Centrifuge the mixture at 2400 times G for 10 minutes. Discard the supernatant and disperse the precipitate in 10 milliliters of ethanol. Obtain a four inch 100 micron silicon wafer coated with about 25 nanometers of silicon nitride. Load photo resist using a spin coater. Then use photo resist to mount the ultra thin wafer on a 500 micron thick silicon wafer. Spin coat the wafer with 10 milliliters of positive photo resist at 3000 rpm for 30 seconds. Bake the wafer at 85 degrees Celsius for 60 seconds. Then cover the wafer with a chromium mask and expose the wafer to 365 nanometer light for 10 seconds. Immerse the wafer in 50 milliliters of the appropriate developer solution for 40 seconds and then in 50 milliliters of deionized water for one minute. Immerse the wafer in 50 milliliters of deionized water for one minute, then place the patterned wafer in a reactive ion etcher. Etch the exposed silicon nitride for one minute. Use a water bath to evenly heat a container of a 30 milligram per liter aqueous solution of potassium hydroxide to 85 degrees Celsius. Soak the ultra thin wafer in the hot potassium hydroxide for two hours to etch the exposed silicon. When the exposed silicon appears to have been completely etched away, carefully remove the wafer from the solution at an angle to avoid rupturing the silicon nitride window. Repeat this process with the second chromium mask to obtain the top and bottom chips. Use the third chromium mask to pattern indium spacers onto the bottom chip. Align the top and bottom chips and bond the chips together at 100 degrees Celsius. Transfer 20 microliters of the prepared nanoparticle dispersion to a five milliliter vial. Allow the solvent to evaporate under ambient conditions for 10 minutes. Inspect the liquid cell under an optical microscope to verify that the silicon nitride windows are intact. Then disperse the nanoparticles in a mixture of one milliliter of orthodichlorobenzene, 250 microliters of pentadecane and 10 microliters of oleylamine. With the liquid cell under the optical microscope use an injector with an ultra thin capillary to load 100 nanoliters of the dispersion into the liquid cell reservoirs. Use filter paper to absorb the excess dispersion outside the reservoirs. Allow the cell to sit in ambient air for 10 minutes to evaporate the orthodichlorobenzene. Then apply vacuum grease to one side of a two millimeter copper aperture grid with a 600 micron hole. Carefully cover the liquid cell with the grid, being careful to align the aperture with the liquid cell window. Mount the cell in a standard TEM holder and load the cell into the instrument. Acquire images in continuous image acquisition mode as the solvent dries. Use image processing software to calculate the radial distribution function for the particles in each acquired image. TEM images of a platinum nanoparticle suspension drying in a silicon nitride liquid cell showed the nanoparticles being pulled inward by the receding solvent front. This behavior was attributed to the strong capillary forces of the thin layer of solvent and the reduced free energy of the nanoparticles at the solvent interface. The nanoparticles initially formed amorphous multilayer agglomerates as they were drawn together. As the solvent dried, the agglomerates flattened into an ordered monolayer. This ordering is reflected in the radial distribution functions derived from the TEM images. The radial distribution function of the image taken after 90 seconds had a large peak at 8.3 nanometers. The oleylamine capped platinum nanoparticles are about 8.3 nanometers in diameter, suggesting that a significant number of particles were assembled as closely as possible. Once mastered, this technique can be done in two days if it is performed properly. Generally individuals who are new to this method may struggle because fabricating and working with the liquid cell require different levels of optimization for different nanoparticles or liquid cell compositions. While attempting this procedure, remember to protect the windows of the liquid cell from breaking. Following this procedure, other methods like applying voltages to the liquid cell can be performed to answer additional questions about the self-assembly of nanoparticles in the presence of external forces. After its development, this technique paved the way for researchers in the field of nanoscience to explore the assembly process of nanoparticles in the overall dry mechanism. After watching this video, you should have a good understanding of how to prepare liquid cells and measure the motions of nanoparticles in TEM experiment. Don't forget that working with KUH agent can be extremely hazardous. Precautions such as wearing safety glasses should always be taken while performing this experiment.

This method can help answer key questions in the geomechanics field about compaction processes in rocks. The main advantage of this technique is that it allows quantitative measurement of the local elastic field within rock and mineral aggregates. Though this method can provide insight into stress distribution within samples during cold compression, it can also be applied to other techniques such as high temperature compression. Generally, individuals new to this method struggle because of challenges in preparing the sample and the cell assembly. Sample and cell assembly preparations are difficult to learn without visual demonstration because of how small and delicate the individual samples and parts of the cell assembly are. To begin preparing a mineral aggregate sample grind about 15 grams of a rock specimen or pre-existing powder, to approximately 4 micron diameter grains using a mortar and pestle, or a rotary tool with a grinding head. Pour the mineral grains into a 20 centimeter decantation column containing ethanol. Allow the grains to settle for an appropriate duration for their density. Then partition the suspension by height into three beakers. Allow the contents of the beakers to dry in air overnight. Measure the average grain diameter of each batch, and select the batch in which the average grain diameter is closest to four micrometers. Next, grind the ends of an alumina rod to be flat in parallel within 0.5 degrees. Clean the rod in an alumina ring by sonication in ethanol for 10 seconds. Allow the components to dry on a delicate task wipe. Working on a clean surface, cover one end of the hole in a D-DIA cell assembly cube with adhesive tape. Insert a boron nitrate sleeve into the assembly cube. Then use tweezers to slide a graphite ring in the alumina ring onto the alumina rod. Place the alumina rod and rings in the assembly cube with the graphite ring on the bottom. Ensure that the rod and rings are settled at the bottom of the hole with the graphite ring in contact with the tape. Mark the corner of the cube that will eventually be aligned with the incoming x-ray beam. Then cut a 1.5 millimeter by 17 millimeter piece of tantalum foil and fold it into a U shape. Insert the foil into the cube with the foil aligned so that the 2D projection of the foil is minimized with respect to the x-ray beam direction. Use a pin to gently press the foil against the edges of the space. Insert the previously prepared rock core or mineral aggregate reference sample into the the cell assembly cube. Lay a 1.7 millimeter by 1 millimeter piece of tantalum foil flat on top of the reference sample with the long side of the foil perpendicular to the x-ray beam. Then, carefully pack the mineral aggregate sample into the cell assembly cube using a small spatula. Leave 1.4 millimeters of space in the cube above the packed sample. Gently remove excess grains adhering to the walls of the cylindrical space with air. Use a pin and calipers to confirm that the final sample height has been reached. Place another 1.7 millimeter by 1 millimeter piece of tantalum foil on the packed sample. Then grind the ends of another alumina rod to be flat in parallel and clean the rod in an alumina ring. Use tweezers to fit the alumina ring and a graphite ring onto the rod. Place the rod on the samples so that the graphite ring is on top. Finally, seal the exposed alumina rod at each end of the cube with a zirconia powder based cement, being careful not to use excess cement. Trim the exposed tantalum foil once the cement has dried. Collect and analyze a diffraction pattern from an alumina standard. Remove the alumina standard and collect an open press x-ray spectrum with an exposure time of 500 seconds to measure the background without a sample assembly. After cleaning the anvils, insert the prepared sample assembly into the center of the experiment set up, ensuring that it is properly aligned with the x-ray beam. Slowly lower the opposing pairs of lateral anvils simultaneously. Gently push the anvils into alignment so that the anvils are level and the bottom and lateral anvils are in contact with the sample assembly. Then release the safety latch and insert the spacer into the hydraulic press. Close the hutch and enable the shutter to allow the x-ray beam to enter the hutch. Turn on the low pressure pump. Then move the top ram up until it rests against the spacer. Guided by real-time x-radiographic imaging, slowly and carefully move up the bottom ram until the anvils appear in the radiograph. Leave a fine gap so that the sample is not overloaded prior to the experiment. Then, turn off all controls on the low-pressure pump controller and close the pressurized valve. In the high pressure hydraulic pump controlled software, move the sample assembly parallel to the beam so that the center of the mineral aggregate sample is aligned with the diffraction focus mark. Collect a diffraction spectrum of the sample with an exposure time of 500 seconds. Capture a radiograph with an exposure time of six milliseconds. Then, move the assembly to center the rock core reference sample in the diffraction focus mark. Acquire diffraction spectrum in a radiograph under the same conditions. Next, start the hydraulic pump motor to drive the anvils inward. Set the target load to 50 tons and enable feedback with a rate of one second and a gain of 20. Set the upper limit of the speed to seven to achieve the slowest possible compression. They hydraulic pump motors drive the anvils inwards to provide pressure for the compression of the experimental cell. In the data collection window, define the locations of the rock core reference in the mineral aggregate sample in terms of the x and y press locations. Ensure that the exposure time is set to 500 seconds. Set the number of cycles required to zero, so that the data collection will continuously repeat. Then start the data collection. As compression progresses, update the sample and reference locations in the software as needed. Upon reaching the target load, stop the data collection. Set the lower limit of the speed control to minus 10 and the target load to zero tons to decompress the sample. Manually collect diffraction spectra in radiographs for the core and aggregate following unloading. Then, open the pressurized valve on the low-pressure pump panel. Turn on the low-pressure pump, and lower the top and bottom rams until the down indicator lamp is illuminated. Move the spacer arm to the out position and drive the top ram up until the safety lock engages. Then, turn off the controls in the pump motor control unit. Slowly move the lateral anvils outward manually and remove the sample assembly. At ambien pressure, the diffraction spectra of a quartz aggregate with the grain size of approximately 4 micrometers and novaculite reference sample with a grain size of six to nine micrometers were similar in intensity with end position. The quartz aggregate spectrum began to broaden with increasing pressure. The quartz peak continued broadening on the higher energy side as the pressure increased, whereas the novaculite peak shape was essentially unchanged. Both the quartz and novaculite peak positions shifted in the higher energy direction which corresponds to lower D spacing. The quartz aggregate showed a significant amount of differential stress in both axial and transverse directions, with nearly twice the amount of stress in the transverse direction than in the axial direction. This indicated that the transverse direction supported a significantly greater load than the axial direction. The modest broadening on the low energy sides of the quartz axial and transverse peaks indicated that a considerable amount of the grains remained stress free in both directions which can only occur if a significant number of grains had at least part of their surface area bounded by voids supporting zero pressure throughout the experiment. Once mastered, this experiment can be done in 16 hours if it is performed properly. After its development, this technique paved the way for researchers in the field of rock mechanics, mineral physics, geotechnic engineering, and material science to explore stress distribution in materials of interest. While attempting this procedure, remember to have the end surface contacts flat so that the applied load can be evenly distributed across the entire surface area. Following this procedure, this method can be used for high temperature applications and ultrasonic sound velocity measurements to determine other information about the rheological and elastic properties of the interior of the earth. After watching this video, you should have a good understanding of how to characterize local stress distribution within mineral aggregates using a multi-anvil deformation apparatus with synchrotron x-radiation.