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Soft pneumatic actuators have a wide range of applications, including providing haptic feedback embedded in smart garments. Here we investigate actuators fabricated from thermoplastic coated textiles. We measure the effects of fabrication parameters on the robustness and airtightness of small, round pneumatic pouch actuators made from heat-sealed thermoplastic polyurethane-coated nylon, which we call PneuDots. We determine the optimal temperature, time, and pressure for heat-pressing of the textile to create strong bonds and identify the most effective glue to create an airtight seal at the inlet. Compared to elastomeric pneumatic actuators, PneuDots reduce the thickness of the actuator by 96.4% and the mass by 57.2%, increasing their wearability while maintaining a strong force output. We evaluated the force output of the actuators, along with their performance over time. In a blocked force test, PneuDot maximum force transmission was 36.1N, which is 95.3% of the peak force output of an elastomeric pneumatic actuator with the same diameter and pressure. Cyclical testing showed that PneuDots had more stable behavior over time. These results provide best practices for fabrication and indicate the feasibility of textile pneumatic actuators for future wearable applications.

Based on experimental and simulation methods we helped develop, we are advancing mechanistic understanding of how self-assembled NC metamaterials can produce distinctive near- and far-field optical properties not readily achievable in lithographically patterned structures. First, the impacts of the inevitable defects and disorder associated with self-assembly can be rationalized and, in some cases, recognized as advantageous. Second, self-assembly enables intimate nanoscale intermixing of different NC and molecular components. By incorporating probe molecules within the gaps between NCs where the electric field enhancement is strongest, we show enhanced detection of molecular vibrations that can be optimized by tuning the size and resonance frequency of the NCs. We show how metasurfaces incorporating mixtures of NCs with different doping concentrations can achieve epsilon-near-zero dielectric response over a broad frequency range. Finally, considering the NC metasurface itself as a building block, we show how photonic structures incorporating these assemblies can harness and amplify their distinctive properties. Through modeling the NC monolayer as a slab with an effective permittivity response, we designed a frequency-tunable IR perfect absorber by layering the NCs on a simple open cavity structure. Since the perfect absorption architecture further enhances the IR electric field localization strength, we expect that this integration strategy can enhance molecular vibration coupling or non-linear optical response. The versatility of the NC assembly and integration approach suggests opportunities for various metal oxide NC superstructures, including mixing and stacking of NCs beyond a single monolayer, representing a vast parameter space for design of linear and nonlinear IR optical components., Comment: 33 pages, 5 figures

3C 264 is one of the few FRI radio galaxies with detected TeV emission. It is a low-luminosity AGN (LLAGN) and is generally associated with a radiatively inefficient accretion flow (RIAF). Earlier multiwavelength studies suggest that the X-ray emission originates from a jet. However, the possibility that the RIAF can significantly contribute to the X-rays cannot be ruled out. In particular, hard X-ray emission $\gtrsim$10 keV has never been detected, making it challenging to distinguish between X-ray models. Here we report a NuSTAR detection up to 25 keV from 3C 264. We also present subpixel deconvolved Chandra images to resolve jet emission down to ~0.2 arcsec from the center of the unresolved X-ray core. Together with a simultaneous Swift observation, we have constrained the dominant hard X-ray emission to be from its unresolved X-ray core, presumably in its quiescent state. We found evidence of a cutoff in the energy around 20 keV, indicating that at least some of the X-rays from the core can be attributed to the RIAF. The Comptonization model suggests an electron temperature of about 15 keV and an optical depth ranging between 4 and 7, following the universality of coronal properties of black hole accretion. The cutoff energy or electron temperature of 3C 264 is the lowest among those of other LLAGNs. The detected hard X-ray emission is at least an order of magnitude higher than that predicted by synchrotron self-Compton models introduced to explain $\gamma$-ray and TeV emission, suggesting that the synchrotron electrons might be accelerated to higher energies than previously thought., Comment: 19 pages, 6 figures, 2 tables, accepted for publication in ApJ, figure 3 is compressed to reduce file size

In joining Fe-alloys and Cu-containing alloys to access the high strength of steels and corrosion resistance of Cu-alloy, cracking is widely observed due to the significant Cu microsegregation during the solidification process, resulting in an interdendritic Cu-rich liquid film at the end of solidification. By fabricating functionally graded materials (FGMs) that incorporate additional elements like Ni in the transition region between these terminal alloy classes, the hot cracking can be reduced. In the present work, the joining of stainless steel 316L (SS316L) and Monel400 by modifying the Ni concentration in the gradient region was studied. A new hot cracking criterion based on hybrid Scheil-equilibrium approach was developed and validated with monolithic multi-layer samples within the SS316L-Ni-Monel400 three-alloy system and an SS316L to 55/45 wt% SS316L/Ni to Monel400 FGM sample fabricated by direct energy deposition (DED) process. The new hot cracking criterion, based on the hybrid Scheil-equilibrium approach, is expected to help design FGM paths between other Fe-alloys and Cu-containing alloys as well., Comment: 23 pages, 11 figure, 1 table

We report results from 8 hours of JWST/MIRI LRS spectroscopic monitoring directly followed by 7 hours of JWST/NIRSpec prism spectroscopic monitoring of the benchmark binary brown dwarf WISE 1049AB, the closest, brightest brown dwarfs known. We find water, methane, and CO absorption features in both components, including the 3.3 $\mu$m methane absorption feature and a tentative detection of small grain ($<$ 1$\mu$m) silicate absorption at $>$8.5 $\mu$m in WISE 1049A. Both components vary significantly ($>$1$\%$), with WISE 1049B displaying larger variations than WISE 1049A. Using K-means clustering, we find three main transition points in wavelength for both components of the binary: 1) change in behavior at $\sim$2.3 $\mu$m coincident with a CO absorption bandhead, 2) change in behavior at 4.2 $\mu$m, close to the CO fundamental band at $\lambda >$ 4.4 $\mu$m, and 3) change in behavior at 8.3-8.5 $\mu$m, potentially corresponding to silicate absorption. We interpret the lightcurves observed with both NIRSpec and MIRI as likely stemming from 1) a deep pressure level driving the double-peaked variability seen in WISE 1049B at wavelengths $<$2.3 $\mu$m and $>$8.5 $\mu$m, 2) an intermediate pressure level shaping the lightcurve morphology between 2.3 and 4.2 $\mu$m, and 3) a higher-altitude pressure level producing single-peaked and plateaued lightcurve behavior between 4.2 and 8.5 $\mu$m., Comment: 28 pages, 27 figures, accepted to MNRAS

In the present work, the ideal shear strength (Tis) of dilute Ni34XZ ternary alloys (X or Z = Al, Co, Cr, Fe, Mn, Mo, Nb, Si, Ti) are predicted by first-principles calculations based on density functional theory (DFT) in terms of pure alias shear deformations. The results show that within the concentration up to 8.3% of the alloying elements, Tis increases with composition in binary systems with Mn, Fe, Co in ascending order, and decreases with composition with Nb, Si, Mo, Ti, Al, Cr in descending order. Combined with Ni34XZ in the present work and Ni11X in the literature from DFT-based calculations, the composition dependence of Tis in binary and ternary systems is modeled using the CALculation of PHAse Diagrams (CALPHAD) approach considering lattice instability, indicating that atomic bonding strength significantly influences Tis. Furthermore, correlational analyses show that Burgers vector and elastic constant C11 affect Tis the most out of the elemental features., Comment: 10 Figures Submitted to Computational Materials Science on April 25th

New implicit and implicit-explicit time-stepping methods for the wave equation in second-order form are described with application to two and three-dimensional problems discretized on overset grids. The implicit schemes are single step, three levels in time, and based on the modified equation approach. Second and fourth-order accurate schemes are developed and they incorporate upwind dissipation for stability on overset grids. The fully implicit schemes are useful for certain applications such as the WaveHoltz algorithm for solving Helmholtz problems where very large time-steps are desired. Some wave propagation problems are geometrically stiff due to localized regions of small grid cells, such as grids needed to resolve fine geometric features, and for these situations the implicit time-stepping scheme is combined with an explicit scheme: the implicit scheme is used for component grids containing small cells while the explicit scheme is used on the other grids such as background Cartesian grids. The resulting partitioned implicit-explicit scheme can be many times faster than using an explicit scheme everywhere. The accuracy and stability of the schemes are studied through analysis and numerical computations.

A host of medical conditions, including amputations, diabetes, stroke, and genetic disease, result in loss of touch sensation. Because most types of sensory loss have no pharmacological treatment or rehabilitative therapy, we propose a haptic sensory prosthesis that provides substitutive feedback. The wrist and forearm are compelling locations for feedback due to available skin area and not occluding the hands, but have reduced mechanoreceptor density compared to the fingertips. Focusing on localized pressure as the feedback modality, we hypothesize that we can improve on prior devices by invoking a wider range of stimulus intensity using multiple points of pressure to evoke spatial summation, which is the cumulative perceptual experience from multiple points of stimuli. We conducted a preliminary perceptual test to investigate this idea and found that just noticeable difference is reduced with two points of pressure compared to one, motivating future work using spatial summation in sensory prostheses., Comment: 2 pages, 2 figures, 2024 IEEE Haptics Symposium Work-in-Progress Paper

Assembly of dissimilar metals can be achieved by different methods, for example, casting, welding, and additive manufacturing (AM). However, undesired phases formed in liquid-phase assembling processes due to solute segregation during solidification diminish mechanical and other properties of the processed parts. In the present work, an open-source software named MaterialsMap, has been developed based on the CALculation of Phase Diagrams (CALPHAD) approach. The primary objective of MaterialsMap is to facilitate the design of an optimal composition pathway for assembling dissimilar alloys with liquid-phases based on the formation of desired and undesired phases along the pathway. In MaterialsMap, equilibrium thermodynamic calculations are used to predict equilibrium phases formed at slow cooling rate, while Scheil-Gulliver simulations are employed to predict non-equilibrium phases formed during rapid cooling. By combining these two simulations, MaterialsMap offers a thorough guide for understanding phase formation in various manufacturing processes, assisting users in making informed decisions during material selection and production. As a demonstration of this approach, a compositional pathway was designed from pure Al to pure Cu through Ag using MaterialsMap. The design was experimentally verified using resistance spot welding (RSW).

Forecasting load at the feeder level has become increasingly challenging with the penetration of behind-the-meter solar, as this self-generation (also called total generation) is only visible to the utility as aggregated net-load. This work proposes a methodology for creation of scenarios of solar penetration at the feeder level for use by forecasters to test the robustness of their algorithm to progressively higher penetrations of solar. The algorithm draws on publicly available observations of weather \emph{condition} (e.g., rainy/cloudy/fair) for use as proxies to sky clearness. These observations are used to mask and weight the interval deviations of similar native usage profiles from which average interval usage is calculated and subsequently added to interval net generation to reconstruct interval total generation. This approach improves the estimate of annual energy generation by 23\%; where the net generation signal currently only reflects 52\% of total annual generation, now 75\% is captured via the proposed algorithm. This proposed methodology is data driven and extensible to service territories which lack information on irradiance measurements and geo-coordinates., Comment: accepted for presentation at the IEEE PES General Meeting 2024

nimCSO is a high-performance tool implementing several methods for selecting components (data dimensions) in compositional datasets, which optimize the data availability and density for applications such as machine learning. Making said choice is a combinatorically hard problem for complex compositions existing in highly dimensional spaces due to the interdependency of components being present. Such spaces are encountered, for instance, in materials science, where datasets on Compositionally Complex Materials (CCMs) often span 20-45 chemical elements, 5-10 processing types, and several temperature regimes, for up to 60 total data dimensions. At its core, nimCSO leverages the metaprogramming ability of the Nim language (nim-lang.org) to optimize itself at the compile time, both in terms of speed and memory handling, to the specific problem statement and dataset at hand based on a human-readable configuration file. As demonstrated in this paper, nimCSO reaches the physical limits of the hardware (L1 cache latency) and can outperform an efficient native Python implementation over 400 times in terms of speed and 50 times in terms of memory usage (not counting interpreter), while also outperforming NumPy implementation 35 and 17 times, respectively, when checking a candidate solution. It is designed to be both (1) a user-ready tool, implementing two efficient brute-force approaches (for handling up to 25 dimensions), a custom search algorithm (for up to 40 dimensions), and a genetic algorithm (for any dimensionality), and (2) a scaffold for building even more elaborate methods in the future, including heuristics going beyond data availability. All configuration is done with a simple human-readable YAML config file and plain text data files, making it easy to modify the search method and its parameters with no knowledge of programming and only basic command line skills., Comment: 5 pages, 3 figures, 2 tables, ULTERA Project, documented at https://nimcso.phaseslab.org, code at https://github.com/amkrajewski/nimCSO

In the present study, the DFT+U method was employed to predict the thermodynamic properties of Cr2O3, Nb2O5, and Ta2O5. Results were benchmarked with experimental data showing high accuracy, except for the negative thermal expansion (NTE) of Nb2O5, which is attributed to its polymorphic complexity. Additionally, we extended our analysis to rutile-type oxides CrNbO4 and CrTaO4, examining their entropy and heat capacity at finite temperatures. CrNbO4 displayed slightly higher entropy and heat capacity at high temperatures. The mean linear thermal expansion coefficients for CrNbO4 and CrTaO4 from 500 K to 2000 K were predicted to be 6.00*10-6/K and 13.49*10-6/K, respectively, corroborating with DFT predictions and experimental evidence. Our research highlights the precision of the DFT+U and phonon methods in predicting the thermodynamic properties of oxide materials, offering insights into the design of corrosion-resistant materials.

Pneumatic actuation benefits soft robotics by facilitating compliance, enabling large volume change, and concentrating actuator weight away from the end-effector. However, portability is compromised when pneumatic actuators are tethered to cumbersome air and power supplies. While there are existing options for portable pneumatic systems, they are limited in dynamic capabilities, constraining their applicability to low pressure and/or small-volume soft robots. In this work, we propose a portable, high-flow pressure supply and regulator (phloSAR) for use in untethered, weight-constrained, dynamic soft robot applications. PhloSAR leverages high-flow proportional valves, an integrated pressure reservoir, and Venturi vacuum generation to achieve portability and dynamic performance. We present a set of models that describe the system dynamics, experimentally validate them on physical hardware, and discuss the influence of design parameters on system operation. Lastly, we integrate a proof-of-concept prototype with a soft robot arm mounted on an aerial vehicle to demonstrate the system's applicability to mobile robotics. Our system enables new opportunities in mobile soft robotics by making untethered pneumatic supply and regulation available to a wider range of soft robots., Comment: 2024 IEEE International Conference on Soft Robotics

The mitigation of material defects from additive manufacturing (AM) processes is critical to reliability in their fabricated parts and is enabled by modeling the complex relations between available build monitoring signals and final mechanical performance. To this end, the present study investigates a machine learning approach for predicting mechanical properties for Ti-6Al-4V fabricated through laser powder bed fusion (PBF-LB) AM using in situ photodiode processing signals. Samples were fabricated under different processing parameters, varying laser powers and scan speeds for the purpose of probing a wide range of microstructure and property variations. Photodiode data were collected during fabrication, later to be arranged in image format and extracted to information-dense vectors by the transferal of deep convolutional neural network (DCNN) structures and weights pre-trained on a large computer vision benchmark image database. The extracted features were then used to train and test a newly designed regression model for mechanical properties. Average cross-validation accuracies were found to be 98.7% (r2 value of 0.89) for the prediction of ultimate tensile strength, which ranged from 900 to 1150 MPa in the samples studied, and 93.1% (r2 value of 0.96) for the prediction of elongation to fracture, which ranged from 0 to 17%. Thus, with high accuracy and hardware accelerated inference speeds, we demonstrate that a transfer learning framework can be used to predict strength and ductility of metal AM components based on processing signals in PBF-LB, illustrating a potential route toward real-time closed-loop control and process optimization of PBF-LB in industrial applications.

The crystal plasticity finite element method (CPFEM) is a widely used technique for resolving macroscopic stress and strain onto the physically relevant length scales of grains and slip systems in ductile crystalline materials like structural metals. Here, the calibration of a CPFEM model for single crystal applications was found to depend critically on loading orientation, with an effect significant even at an angle of 0.1 degrees. Slight misorientation from high symmetry loading affected lattice rotation during tensile deformation, changing the number of active slip systems, and, as a result, the overall stress-strain behavior. The strongest misorientation effects occurred around the multi-slip orientations of [001], [111], [101], and [102], while the single slip orientation of [213] showed a negligible effect, as expected, and the double slip orientation of [112] showed less of an effect than [102] due to its relative lattice orientation stability. The magnitude of the misorientation effect increased dramatically with the strength of slip system interaction, which, in the chosen hardening framework, is represented by the latent hardening coefficient. In a case study on [001] Cu, offsets of 0.3-2.0 degrees gave stress values at an engineering strain of 0.25 that were lower by 15-18% relative to the direct loading values, highlighting the importance of exact orientations for single crystal plasticity parameterization and application.

Multi-wavelength photometry of brown dwarfs and planetary-mass objects provides insight into their atmospheres and cloud layers. We present near-simultaneous $J-$ and $K_s-$band multi-wavelength observations of the highly variable T2.5 planetary-mass object, SIMP J013656.5+093347. We reanalyze observations acquired over a single night in 2015 using a recently developed data reduction pipeline. For the first time, we detect a phase shift between $J-$ and $K_s-$band light curves, which we measure to be $39.9^{\circ +3.6}_{ -1.1}$. Previously, phase shifts between near-infrared and mid-infrared observations of this object were detected and attributed to probing different depths of the atmosphere, and thus different cloud layers. Using the Sonora Bobcat models, we expand on this idea to show that at least two different patchy cloud layers must be present to explain the measured phase shift. Our results are generally consistent with recent atmospheric retrievals of this object and other similar L/T transition objects., Comment: 15 pages, 8 figures, Accepted for publication in ApJ

Many disciplines of science and engineering deal with problems related to compositions, ranging from chemical compositions in materials science to portfolio compositions in economics. They exist in non-Euclidean simplex spaces, causing many standard tools to be incorrect or inefficient, which is significant in combinatorically or structurally challenging spaces exemplified by Compositionally Complex Materials (CCMs) and Functionally Graded Materials (FGMs). Here, we explore them conceptually in terms of problem spaces and quantitatively in terms of computational feasibility. This work implements several essential methods specific to the compositional (simplex) spaces through a high-performance open-source library nimplex. Most significantly, we derive and implement an algorithm for constructing a novel n-dimensional simplex graph data structure, which contains all discretized compositions and all possible neighbor-to-neighbor transitions as pointer arrays. Critically, no distance or neighborhood calculations are performed, instead leveraging pure combinatorics and the ordering in procedurally generated simplex grids, keeping the algorithm $\mathcal{O}(N)$, so that graphs with billions of transitions take seconds to construct on a laptop. Furthermore, we demonstrate how such graph representations can be combined to express path-planning problem spaces and to incorporate prior knowledge while keeping the problem space homogeneous. This allows for efficient deployment of existing high-performance gradient descent, graph traversal search, and other path optimization algorithms., Comment: 18 pages; 11 figures; software source code at https://github.com/amkrajewski/nimplex and documentation at https://nimplex.phaseslab.org; minor updates in V2

A database for the Cr-Ni-V system was constructed by modeling the binary Cr-V and ternary Cr-Ni-V systems using the CALPHAD approach aided by density functional theory (DFT)-based first-principles calculations and ab initio molecular dynamics (AIMD) simulations. To validate this new database, a functionally graded material (FGM) using Ni-20Cr and elemental V was fabricated using directed energy deposition additive manufacturing (DED AM) and experimentally characterized. The deposited Ni-20Cr was pure fcc phase, while increasing the amount of V across the gradient resulted in the formation of sigma phase, followed by the bcc phase. The experimentally measured phase data was compared with computational predictions made using a Cr-Ni-V thermodynamic database from the literature as well as the database developed in the present work. The newly developed database was shown to better predict the experimentally observed phases due to its accurate modeling of binary systems within the database and the ternary liquid phase, which is critical for accurate Scheil calculations.

Smartphone-based measurement platforms can collect data on human sensory function in an accessible manner. We developed a smartphone app that measures vibration perception thresholds by commanding vibrations with varying amplitudes and recording user responses via (1) a staircase method that adjusts a variable stimulus, and (2) a decay method that measures the time a user feels a decaying stimulus. We conducted two studies with healthy adults to assess the reliability and usability of the app when the smartphone was applied to the hand and foot. The staircase mode had good reliability for repeated measurements, both with and without the support of an in-person experimenter. The app has the potential to be used at home in unguided scenarios., Comment: 9 pages, 5 figures, To be published in IEEE Haptics Symposium 2024

Tactile perception plays an important role in activities of daily living, and it can be impaired in individuals with certain medical conditions. The most common tools used to assess tactile sensation, the Semmes-Weinstein monofilaments and the 128 Hz tuning fork, have poor repeatability and resolution. Long term, we aim to provide a repeatable, high-resolution testing platform that can be used to assess vibrotactile perception through smartphones without the need for an experimenter to be present to conduct the test. We present a smartphone-based vibration perception measurement platform and compare its performance to measurements from standard monofilament and tuning fork tests. We conducted a user study with 36 healthy adults in which we tested each tool on the hand, wrist, and foot, to assess how well our smartphone-based vibration perception thresholds (VPTs) detect known trends obtained from standard tests. The smartphone platform detected statistically significant changes in VPT between the index finger and foot and also between the feet of younger adults and older adults. Our smartphone-based VPT had a moderate correlation to tuning fork-based VPT. Our overarching objective is to develop an accessible smartphone-based platform that can eventually be used to measure disease progression and regression., Comment: Accepted for publication in IEEE Transactions on Haptics 2024