Neural Level Set Topology Optimization Using Unfitted Finite Elements

To facilitate widespread adoption of automated engineering design techniques, existing methods must become more efficient and generalizable. In the field of topology optimization, this requires the coupling of modern optimization methods with solvers capable of handling arbitrary problems. In this work, a topology optimization method for general multiphysics problems is presented. We leverage a convolutional neural parameterization of a level set for a description of the geometry and use this in an unfitted finite element method that is differentiable with respect to the level set everywhere in the domain. We construct the parameter to objective map in such a way that the gradient can be computed entirely by automatic differentiation at roughly the cost of an objective function evaluation. The method produces optimized topologies that are similar in performance yet exhibit greater regularity than baseline approaches on standard benchmarks whilst having the ability to solve a more general class of problems, e.g., interface-coupled multiphysics.Comment: 16 pages + refs, 10 fig

The Host Galaxy and Central Engine of the Dwarf AGN POX 52

We present new multi-wavelength observations of the dwarf Seyfert 1 galaxy POX 52 in order to investigate the properties of the host galaxy and the active nucleus, and to examine the mass of its black hole, previously estimated to be ~ 10^5 M_sun. Hubble Space Telescope ACS/HRC images show that the host galaxy has a dwarf elliptical morphology (M_I = -18.4 mag, Sersic index n = 4.3) with no detected disk component or spiral structure, confirming previous results from ground-based imaging. X-ray observations from both Chandra and XMM show strong (factor of 2) variability over timescales as short as 500 s, as well as a dramatic decrease in the absorbing column density over a 9 month period. We attribute this change to a partial covering absorber, with a 94% covering fraction and N_H = 58^{+8.4}_{-9.2} * 10^21 cm^-2, that moved out of the line of sight in between the XMM and Chandra observations. Combining these data with observations from the VLA, Spitzer, and archival data from 2MASS and GALEX, we examine the spectral energy distribution (SED) of the active nucleus. Its shape is broadly similar to typical radio-quiet quasar SEDs, despite the very low bolometric luminosity of L_bol = 1.3 * 10^43 ergs/s. Finally, we compare black hole mass estimators including methods based on X-ray variability, and optical scaling relations using the broad H-beta line width and AGN continuum luminosity, finding a range of black hole mass from all methods to be M_bh = (2.2-4.2) * 10^5 M_sun, with an Eddington ratio of L_bol/L_edd = 0.2-0.5.Comment: 19 pages, 16 figures, accepted for publication in Ap

A metal-organic framework with ultrahigh glass-forming ability

Glass-forming ability (GFA) is the ability of a liquid to avoid crystallization during cooling. Metal-organic frameworks (MOFs) are a new class of glass formers (1?3), with hitherto unknown dynamic and thermodynamic properties. We report the discovery of a new series of tetrahedral glass systems, zeolitic imidazolate framework?62 (ZIF-62) [Zn(Im2?xbImx)], which have ultrahigh GFA, superior to any other known glass formers. This ultrahigh GFA is evidenced by a high viscosity ? (105 Pa?s) at the melting temperature Tm, a large crystal-glass network density deficit (??/?g)network, no crystallization in supercooled region on laboratory time scales, a low fragility (m = 23), an extremely high Poisson?s ratio (? = 0.45), and the highest Tg/Tm ratio (0.84) ever reported. Tm and Tg both increase with benzimidazolate (bIm) content but retain the same ultrahigh Tg/Tm ratio, owing to high steric hindrance and frustrated network dynamics and also to the unusually low enthalpy and entropy typical of the soft and flexible nature of MOFs. On the basis of these versatile properties, we explain the exceptional GFA of the ZIF-62 systempublishersversionPeer reviewe

New synthetic routes towards MOF production at scale

The potential commercial applications for metal organic frameworks (MOFs) are tantalizing. To address the opportunity, many novel approaches for their synthesis have been developed recently. These strategies present a critical step towards harnessing the myriad of potential applications of MOFs by enabling larger scale production and hence real-world applications. This review provides an up-to-date survey (212 references) of the most promising novel synthetic routes, i.e., electrochemical, microwave, mechanochemical, spray drying and flow chemistry synthesis. Additionally, the essential topic of downstream processes, especially for large scale synthesis, is critically reviewed. Lastly we present the current state of MOF commercialization with direct feedback from commercial players

Heart Rate and Energy Expenditure Concurrent Validity of Identical Garmin Wrist Watches During Moderately Heavy Resistance Training

Consistent with previous years, ACSM has found that wearable technology and resistance training (RT) are two of the top 5 fitness trends in 2023. Our lab recently found that wrist-worn devices, such as Garmin Instinct, are neither valid nor reliable at measuring average or maximal heart rate (HR) or estimating energy expenditure (EE) following light intensity circuit RT. We postulated that the errors may have been due to the device’s algorithms assuming higher intensity during RT. PURPOSE: The purpose of this study was to determine the concurrent validity of identical Garmin Instinct wrist-watches to record valid measures of average and maximal HR as well as estimated EE following moderately heavy RT. METHODS: Twenty-one adult participants completed this study (n=10 female, n=11 male). Two Garmin Instinct wrist-watches were evaluated, along with the Polar H10 chest strap and Cosmed K5 portable metabolic unit as the criterion devices for average/maximal HR and EE, respectively. Participants completed 8 supersets of the reverse lunge and shoulder press exercises using dumbbells at a light (4 sets) and moderately heavy (4 sets) intensity with 1 superset of 6 repetitions per exercise (12 repetitions per superset) and 1 min rest between supersets. Data were analyzed for validity (Mean Absolute Percent Error [MAPE] and Lin’s Concordance Coefficient [CCC]), with predetermined thresholds of MAPE\u3c10% and CCC\u3e0.70. A one-way repeated measures ANOVA with Sidak post-hoc test was used to determine differences (p\u3c0.05). RESULTS: The identical Garmin Instinct devices were not considered valid for average HR (MAPE range: 36.5-81.6%; CCC range: 0.07-0.18), maximal HR (MAPE range: 18.6-18.8%; CCC range: 0.15-0.31), or estimated EE (MAPE range: 14.0-16.4%; CCC range: 0.08-0.32) compared to the criterion references. The devices were significantly different than each other for average HR (p=0.005), maximal HR (p\u3c0.001), and estimated EE (p\u3c0.0001). CONCLUSION: The wearable wrist-worn devices tested herein should not be utilized for accurate measurements of HR or EE during RT, and there are even differences between identical devices. People who RT while using these devices should do so with caution if wishing to utilize them for physiological measures