Thin streams of liquid commonly break up into characteristic droplet patterns owing to the surface-tension-driven Plateau-Rayleigh instability. Very similar patterns are observed when initially uniform streams of dry granular material break up into clusters of grains, even though flows of macroscopic particles are considered to lack surface tension. Recent studies on freely falling granular streams tracked fluctuations in the stream profile, but the clustering mechanism remained unresolved because the full evolution of the instability could not be observed. Here we demonstrate that the cluster formation is driven by minute, nanoNewton cohesive forces that arise from a combination of van der Waals interactions and capillary bridges between nanometre-scale surface asperities. Our experiments involve high-speed video imaging of the granular stream in the co-moving frame, control over the properties of the grain surfaces and the use of atomic force microscopy to measure grain-grain interactions. The cohesive forces that we measure correspond to an equivalent surface tension five orders of magnitude below that of ordinary liquids. We find that the shapes of these weakly cohesive, non-thermal clusters of macroscopic particles closely resemble droplets resulting from thermally induced rupture of liquid nanojets.
Parylene C is a well-known polymer and it has been mainly employed as a protective layer for implantable electronics. In this paper, we propose a new approach to use Parylene C as a versatile template for patterning soft materials potentially applicable as scaffolds in cardiac tissue engineering (TE). Parylene C substrates were anisotropically patterned through standard lithographic process with hydrophilic channels separating raised hydrophobic strips. Ridges and grooves of the template are 10 µm width and depth ranging from 1 to 17 µm. Polydimethylsiloxane (PDMS) and Polyacrylamide (PAm) hydrogel have been chosen as soft polymers to be moulded. Thanks to their chemical and physical properties PDMS and PAm hydrogel mimic the extracellular matrix (ECM). PDMS was spin coated on micropatterned Parylene C obtaining composite substrates with 460 nm and 1.15 µm high grooves. The Young’s modulus of the composite Parylene C/PDMS was evaluated and it was found to be almost half when compared to PDMS. PAm hydrogel was also printed using collagen coated micro-grooved Parylene C. Optical micrographs and fluorescence analysis show the successful topographic and protein pattern transfer on the hydrogel.
The theory of photokinetic effects expresses the forces and torques exerted by a beam of light in terms of experimentally accessible amplitude and phase profiles. We use this formalism to develop an intuitive explanation for the performance of optical tweezers operating in the Rayleigh regime, including effects arising from the influence of light's angular momentum. First-order dipole contributions reveal how a focused beam can trap small objects, and what features limit the trap's stability. The first-order force separates naturally into a conservative intensity-gradient term that forms a trap and a non-conservative solenoidal term that drives the system out of thermodynamic equilibrium. Neither term depends on the light's polarization; light's spin angular momentum plays no role at dipole order. Polarization-dependent effects, such as trap-strength anisotropy and spin-curl forces, are captured by the second-order dipole-interference contribution to the photokinetic force. The photokinetic expansion thus illuminates how light's angular momentum can be harnessed for optical micromanipulation, even in the most basic optical traps.This article is part of the themed issue 'Optical orbital angular momentum'.
Structure-based drug discovery efforts require knowledge of where drug-binding sites are located on target proteins. To address the challenge of finding druggable sites, we developed a machine-learning algorithm called TACTICS (trajectory-based analysis of conformations to identify cryptic sites), which uses an ensemble of molecular structures (such as molecular dynamics simulation data) as input. First, TACTICS uses k-means clustering to select a small number of conformations that represent the overall conformational heterogeneity of the data. Then, TACTICS uses a random forest model to identify potentially bindable residues in each selected conformation, based on protein motion and geometry. Lastly, residues in possible binding pockets are scored using fragment docking. As proof-of-principle, TACTICS was applied to the analysis of simulations of the SARS-CoV-2 main protease and methyltransferase and the Yersinia pestis aryl carrier protein. Our approach recapitulates known small-molecule binding sites and predicts the locations of sites not previously observed in experimentally determined structures. The TACTICS code is available at .
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