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We aim to automatize the identification of collective variables to simplify and speed up enhanced sampling simulations of conformational dynamics in biomolecules. We focus on anharmonic low-frequency vibrations that exhibit fluctuations on timescales faster than conformational transitions but describe a path of least resistance towards structural change. A key challenge is that harmonic approximations are ill-suited to characterize these vibrations, which are observed at far-infrared frequencies and are easily excited by thermal collisions at room temperature. Here, we approached this problem with a frequency-selective anharmonic (FRESEAN) mode analysis that does not rely on harmonic approximations and successfully isolates anharmonic low-frequency vibrations from short molecular dynamics simulation trajectories. We applied FRESEAN mode analysis to simulations of alanine dipeptide, a common test system for enhanced sampling simulation protocols, and compare the performance of isolated low-frequency vibrations to conventional user-defined collective variables (here backbone dihedral angles) in enhanced sampling simulations. The comparison shows that enhanced sampling along anharmonic low-frequency vibrations not only reproduces known conformational dynamics but can even further improve sampling of slow transitions compared to user-defined collective variables. Notably, free energy surfaces spanned by low-frequency anharmonic vibrational modes exhibit lower barriers associated with conformational transitions relative to representations in backbone dihedral space. We thus conclude that anharmonic low-frequency vibrations provide a promising path for highly effective and fully automated enhanced sampling simulations of conformational dynamics in biomolecules. 

Peptides that bind to inorganic materials can be used to functionalize surfaces, control crystallization, or assist ininterfacial self-assembly. In the past, inorganic-binding peptides have been found predominantly through peptide library screening. While this method has successfully identified peptides that bind to a variety of materials, an alternative design approach that can intelligently search for peptides and provide physical insight for peptide affinity would be desirable. In this work, we develop a computational, physics-based approach to design inorganic-binding peptides, focusing on peptides that bind to the common plastics polyethylene, polypropylene, polystyrene, and poly(ethylene terephthalate). The PepBD algorithm, a Monte Carlo method that samples peptide sequence and conformational space, was modified to include simulated annealing, relax hydration constraints, and an ensemble of conformations to initiate design. These modifications led to the discovery of peptides with significantly better scores compared to those obtained using the original PepBD. PepBD scores were found to improve with increasing van der Waals interactions, although strengthening the intermolecular van der Waals interactions comes at the cost of introducing unfavorable electrostatic interactions. The best designs are enriched in amino acids with bulky side chains and possess hydrophobic and hydrophilic patches whose location depends on the adsorbed conformation. Future work will evaluate the top peptide designs in molecular dynamics simulations and experiment, enabling their application in microplastic pollution remediation and plastic-based biosensors. 

Proton transfer reactions are ubiquitous in chemistry, especially in aqueous solutions. We investigate photo-induced proton transfer between the photoacid 8-hydroxypyrene-1,3,6-trisulfonate (HPTS) and water using fast fluorescence spectroscopy and ab initio molecular dynamics simulations. Photo-excitation causes rapid proton release from the HPTS hydroxyl. Previous experiments on HPTS/water described the progress from photoexcitation to proton diffusion using kinetic equations with two time constants. The shortest time constant has been interpreted as protonated and photoexcited HPTS evolving into an “associated” state, where the proton is “shared” between the HPTS hydroxyl and an originally hydrogen bonded water. The longer time constant has been interpreted as indicating evolution to a “solvent separated” state where the shared proton undergoes long distance diffusion. In this work, we refine the previous experimental results using very pure HPTS. We then use excited state ab initio molecular dynamics to elucidate the detailed molecular mechanism of aqueous excited state proton transfer in HPTS. We find that the initial excitation results in rapid rearrangement of water, forming a strong hydrogen bonded network (a “water wire”) around HPTS. HPTS then deprotonates in ≤3 ps, resulting in a proton that migrates back and forth along the wire before localizing on a single water molecule. We find a near linear relationship between emission wavelength and proton-HPTS distance over the simulations’ time scale, suggesting that emission wavelength can be used as a ruler for proton distance. Our simulations reveal that the “associated” state corresponds to a water wire with a mobile proton and that the diffusion of the proton away from this water wire (to a generalized “solvent-separated” state) corresponds to the longest experimental time constant. 

Soft polymer actuators are in increasing demand due to their more fluid like motion and flexibility when actuated than compared with rigid actuators, which makes them valuable in diverse engineering applications. One of the main types of soft polymer actuators is the dielectric elastomer actuator, whose working principle is to apply a voltage potential difference between electrodes to reduce the thickness of the elastomeric material while expanding its area. This paper looks at manufacturing a micro soft polymer dielectric elastomer actuator utilizing two-photon polymerization 3D printing. The actuator contains micro channels that are filled with an electrode by using capillary action. A complex helical geometry is designed, printed, and tested for electrode filling capabilities. Quite a few obstacles are described in this paper including the use of a newly released two-photon polymerization resin which has limited supporting resources, as well as the complex helical geometry having a large compliance that vastly complicates its fabrication, post-processing, handling, electrode filling, electrode integration, and actuation testing. However, these challenges are overcome by using the standard printing recipes currently available for the resins, adding electrode isolation layers, and printing thicker elastomer zones for more structural support. The results found solidify the approach of filling microchannels with electrodes through capillary action and lead to further the focus and creation of multi-functional micro soft actuators. 

Current robotic sensing is mainly visual, which is useful up until the point of contact. To understand how an object is being gripped, tactile feedback is needed. Human grasp is gentle yet firm, with integrated tactile touch feedback. Ras Labs makes Synthetic Muscle™, which is a class of electroactive polymer (EAP) based materials and actuators that sense pressure from gentle touch to high impact, controllably contract and expand at low voltage (battery levels), and attenuate force. The development of this technology towards sensing has provided for fingertip-like sensors that were able to detect very light pressures down to 0.01 N and even 0.005 N, with a wide pressure range to 25 N and more and with high linearity. By using these soft yet robust Tactile Fingertip™ sensors, immediate feedback was generated at the first point of contact. Because these elastomeric pads provided a soft compliant interface, the first point of contact did not apply excessive force, allowing for gentle object handling and control of the force applied to the object. The Tactile Fingertip could also detect a change in pressure location on its surface, i.e., directional glide provided real time feedback, making it possible to detect and prevent slippage by then adjusting the grip strength. Machine learning (ML) and artificial intelligence (AI) were integrated into these sensors for object identification along with the determination of good grip (position, grip force, no slip, no wobble) for pick-and-place and other applications. Synthetic Muscle™ is also being retrofitted as actuators into a human hand-like biomimetic gripper. The combination of EAP shape-morphing and sensing promises the potential for robotic grippers with human hand-like control and tactile sensing. This is expected to advance robotics, whether it is for agriculture, medical surgery, therapeutic or personal care, or in extreme environments where humans cannot enter, including with contagions that have no cure, as well as for collaborative robotics to allow humans and robots to intuitively work safely and effectively together. 

Wearable dielectric elastomer actuators (DEAs) have been greatly considered for development of biomedical devices. In particular, a DEA cuff device has the capability of minimizing venous system disorders that occur in the lower limbs such as orthostatic intolerance (OI) and deep-vein thrombosis which are a result of substantial blood pooling. Recent works have shown that DEAs could regulate and even enhance venous blood flow return. This wearable technology orders a new light, low-cost, compliant, and simple countermeasure which could be safely and comfortably worn that includes mobility. In addition, it may supplement or even provide an alternative solution to exercise and medication. This work presents the design, model, and characterization of the DEA cuff device design that is capable of generating significant pressure change. A rolled DEA strip was actuated over a simulated muscle-artery apparatus using a periodic voltage input, and fluid pressure change was directly observed. A force sensitive resistor sensor was used to achieve a more precise pressure measurement. Performance analysis was conducted through frequency response analysis. The results provide a framework for implementing dynamic modelling and control to allow various forms of actuation input. 

Ras Labs makes Synthetic Muscle™, which is a class of electroactive polymer (EAP) based materials and actuators that sense pressure (gentle touch to high impact), controllably contract and expand at low voltage (1.5 V to 50 V, including use of batteries), and attenuate force. We are in the robotics era, but robots do have their challenges. Currently, robotic sensing is mainly visual, which is useful up until the point of contact. To understand how an object is being gripped, tactile feedback is needed. For handling fragile objects, if the grip is too tight, breakage occurs, and if the grip is too loose, the object will slip out of the grasp, also leading to breakage. Rigid robotic grippers using a visual feedback loop can struggle to determine the exact point and quality of contact. Robotic grippers can also get a stuttering effect in the visual feedback loop. By using soft Synthetic Muscle™ based EAP pads as the sensors, immediate feedback was generated at the first point of contact. Because these pads provided a soft, compliant interface, the first point of contact did not apply excessive force, allowing the force applied to the object to be controlled. The EAP sensor could also detect a change in pressure location on its surface, making it possible to detect and prevent slippage by then adjusting the grip strength. In other words, directional glide provided feedback for the presence of possible slippage to then be able to control a slightly tighter grip, without stutter, due to both the feedback and the soft gentleness of the fingertip-like EAP pads themselves. The soft nature of the EAP fingertip pad also naturally held the gripped object, improving the gripping quality over rigid grippers without an increase in applied force. Analogous to finger-like tactile touch, the EAPs with appropriate coatings and electronics were positioned as pressure sensors in the fingertip or end effector regions of robotic grippers. This development of using Synthetic Muscle™ based EAPs as soft sensors provided for sensors that feel like the pads of human fingertips. Basic pressure position and magnitude tests have been successful, with pressure sensitivity down to 0.05 N. Most automation and robots are very strong, very fast, and usually need to be partitioned away from humans for safety reasons. For many repetitive tasks that humans do with delicate or fragile objects, it would be beneficial to use robotics; whether it is for agriculture, medical surgery, therapeutic or personal care, or in extreme environments where humans cannot enter, including with contagions that have no cure. Synthetic Muscle™ was also retrofitted as actuator systems into off-the-shelf robotic grippers and is being considered in novel biomimetic gripper designs, operating at low voltages (less than 50 V). This offers biomimetic movement by contracting like human muscles, but also exceeds natural biological capabilities by expanding under reversed electric polarity. Human grasp is gentle yet firm, with tactile touch feedback. In conjunction with shape-morphing abilities, these EAPs also are being explored to intrinsically sense pressure due to the correlation between mechanical force applied to the EAP and its electronic signature. The robotic field is experiencing phenomenal growth in this fourth phase of the industrial revolution, the robotics era. The combination of Ras Labs’ EAP shape-morphing and sensing features promises the potential for robotic grippers with human hand-like control and tactile sensing. This work is expected to advance both robotics and prosthetics, particularly for collaborative robotics to allow humans and robots to intuitively work safely and effectively together. 

Ras Labs makes Synthetic Muscle™, which is a class of electroactive polymer (EAP) based materials and actuators that controllably contract and expand at low voltage (1.5 V to 50 V, including use of batteries), potentially sense pressure (gentle touch to high impact), and attenuate force. This offers biomimetic movement by contracting similar to human muscles, but also exceeds natural biological capabilities by expanding under reversed electric polarity. These EAPs are affordable and robust. They have been tested in many harsh environments, including extreme temperatures, high pressure underwater environments, and in space on the International Space Station. Potential load bearing applications are feasible, with significant mechanical strength when tested in compression. Selected EAP samples were tested and survived 3,000,000 cycles at 4 Hz from 5 psi to 30 psi, followed by a 50-psi compression. Human grasp is gentle yet firm, with tactile touch feedback. In conjunction with shape-morphing abilities, these EAPs also are being explored to intrinsically sense pressure due to the correlation between mechanical force applied to the EAP and its electronic signature. We are continuing to advance EAP technology and apply this technology towards robotic grippers. The robotic field is experiencing phenomenal growth in this fourth phase of the industrial revolution, the robotics era. The combination of Ras Labs’ EAP shape-morphing and sensing features promises the potential for robotic grippers with human hand-like control and tactile sensing. This work is expected to advance both robotics and prosthetics, particularly for collaborative robotics to allow humans and robots to intuitively work safely and effectively together.