Kitty Hawk demonstration of Bio-inspired Engineering for Exploration Systems (BEES)
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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This paper reviews the various aspects of the field of biomimetics and the role that EAP play and the outlook for its evolution.
The evolution of nature over 3.8 billion years led to the highly effective and power efficient biological mechanisms. Imitating these mechanisms offers enormous potentials for the improvement of our life and the tools we use.
One of the newest fields of biomimetics is the electroactive polymers (EAP) that are also known as artificial muscles. To take advantage of these materials, efforts are made worldwide to establish a strong infrastructure addressing the need for comprehensive analytical modeling of their response mechanism and develop effective processing and characterization techniques. The field is still in its emerging state and robust materials are still not readily available however in recent years significant progress has been made and commercial products have already started to appear. This paper covers the current state of- the-art and challenges to making artificial muscles and their potential biomimetic applications.
As humans push further beyond the grasp of earth, robotic missions in advance of human missions will play an increasingly important role. These robotic systems will find and retrieve valuable resources as part of an in-situ resource utilization (ISRU) strategy. They will need to be highly autonomous while maintaining high task performance levels. NASA Kennedy Space Center has teamed up with the Biological Computation Lab at the University of New Mexico to create a swarm of small, low-cost, autonomous robots to be used as a ground-based research platform for ISRU missions. The behavior of the robot swarm mimics the central-place foraging strategy of ants to find and collect resources in a previously unmapped environment and return those resources to a central site. This talk will guide the audience through the Swarmie robot project from its conception by students in a New Mexico research lab to its robot trials in an outdoor parking lot at NASA. The software technologies and techniques used on the project will be discussed, as well as various challenges and solutions that were encountered by the development team along the way.
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Self-assembly of 3D structures introduce an attractive and scalable route to realize reconfigurable and functionally capable mesoscale devices without human intervention. A common approach for achieving this is to utilize stimuli-responsive folding of hinged structures, which requires the integration of different materials and/or geometric arrangements along the hinges. It is also demonstrated that the inclusion of Kirigami cuts in planar, hingeless bilayer thin sheets can be used to produce complex 3D shapes in an on-demand manner. Nonlinear finite element models are developed to elucidate the mechanics of shape morphing in bilayer thin sheets and verify the predictions through swelling experiments of planar, millimeter-scaled PDMS (polydimethylsiloxane) bilayers in organic solvents. Building upon the mechanistic understandings, The transformation of Kirigami-cut simple bilayers into 3D shapes such as letters from the Roman alphabet (to make “ADVANCED FUNCTIONAL MATERIALS”) and open/closed polyhedral architectures is experimentally demonstrated. A possible application of the bilayers as tether-less optical metamaterials with dynamically tunable light transmission and reflection behaviors is also shown. As the proposed mechanistic design principles could be applied to a variety of materials, this research broadly contributes toward the development of smart, tetherless, and reconfigurable multifunctional systems.
The dream to produce green, clean and sustainable hydrogen from earth-abundant and free resources such as seawater and sunlight is highly motivating because of the interest for desirable economical and societal applications in energy. However, it remains challenging to develop an efficient and unassisted photocatalytic device to split seawater molecules with just sunlight without any external bias. For the first time, a such novel hierarchical material has been developed, based on thin film technology that integrates TiO 2 semiconductor layers, embedded gold nanoparticles and a photosensitive carbo-benzene layer. The design of the triptych device placing the photocatalyst in be-to-be increases the photoactive surface area by a factor 2. Its stability (>120 successive hours of hydrogen production and >5 days in a day/night representative alternation) and efficiency (STH 0.06%) are measured in NaCl-salted water. Here, the chloride ions act as hole scavengers and induce an increase of pH increasing in turn the sun-driven hydrogen production rate.
Foaming prediction is critical for selecting materials and designing processes in industries such as bioprocessing and gas processing. Existing models lack the generality needed for a wide range of materials and overlook the foaming behavior in pure liquids. Here, this work presents a novel method for predicting foaming in pure liquids based on their density, surface tension, and viscosity, using Reynolds ( Re ) and Ohnesorge ( Oh ) numbers. A foaming prediction map, leveraging the theory of fluid drop behavior, was developed by plotting these numbers. This map delineates distinct non-foaming and foaming regions, functioning as a binary classifier for foaming predictions. The map was fitted and validated through shake test experiments on 46 liquids, demonstrating reliable predictions, except for a specific region characterized by small Oh and large Re numbers. This region corresponded to relatively low foam stability and high turbulence, making foaming predictions challenging for liquids in this category.
Thermally adaptive textiles (TATs) enable human subjects to attain thermal comfort without energy consumption, which can lead to enormous energy savings on heating, ventilation, and air conditioning (HVAC) in buildings. Herein, TAT structures which respond to the sweat and generate pores by opening an array of flap‐shaped pores patterned on the fabric surface are proposed. A moisture‐driven self‐actuator for flap opening by constructing a bilayer consisting of a hygroscopic layer using polyethylene glycol and cellulose acetate, and a hydrophobic polymer using a polyester type polymer, is used and successfully demonstrated an essentially instant 4 °C apparent temperature cooling performance within one minute of sweat–humidity‐initiated actuation while wearing TAT using a sweating skin simulated device.
Abstract The organic ligand environment surrounding enzymatic and homogeneous catalytic active sites often determines catalytic activity. Ruthenium nanoparticles, ≤1 nm in diameter, are synthesized using monodentate thiol, monodentate phosphine, and bidentate bisphosphine ligands. Even though some of the ruthenium surface is blocked by the ligands, catalytic activity is still observed for CO oxidation and H 2 O 2 decomposition. All three ligand‐stabilized ruthenium nanoparticles have similar CO oxidation rates; however, the bisphosphine‐stabilized Ru nanoparticles are approximately 2.5 times less active than the monothiol‐stabilized and monophosphine‐stabilized ruthenium nanoparticles for H 2 O 2 decomposition. It is observed that the organic ligand environment is modulated in situ during nanoparticle synthesis via partial oxidation of the bisphosphine as confirmed by 31 P NMR measurements. We hypothesize that bisphosphine‐bound Ru nanoparticles consist of a Ru core with some of the ligands bound in a monodentate manner where the other P atom is oxidized and not bound to the Ru surface leading to a thicker hydrophobic layer around the Ru nanoparticles. The increase in hydrophobicity is confirmed via contact angle and zeta potential measurements. H 2 O 2 decomposition rates are known to decrease with increasing hydrophobicity, and this work illustrates a pathway for increasing hydrophobicity in situ using ligand‐bound metallic nanoparticles.
Designing model-independent anomaly detection algorithms for analyzing LHC data remains a central challenge in the search for new physics, due to the high dimensionality of collider events. In this work, we develop a graph autoencoder as an unsupervised, model-agnostic tool for anomaly detection, using the LHC Olympics dataset as a benchmark. By representing jet constituents as a graph, we introduce a method to systematically control the information available to the model through sparse graph constructions that serve as physically motivated inductive biases. Specifically, (1) we construct graph autoencoders based on locally rigid Laman graphs and globally rigid unique graphs, and (2) we explore the clustering of jet constituents into subjets to interpolate between high- and low-level input representations. We obtain the best performance, measured in terms of the Significance Improvement Characteristic curve for an intermediate level of subjet clustering and certain sparse unique graph constructions. We further investigate the role of graph connectivity in jet classification tasks. Our results demonstrate the potential of leveraging graph-theoretic insights to refine and increase the interpretability of machine learning tools for collider experiments.
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