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We introduce a novel framework for optimization based on energy-conserving Hamiltonian dynamics in a strongly mixing (chaotic) regime and establish its key properties analytically and numerically. The prototype is a discretization of Born-Infeld dynamics, with a squared relativistic speed limit depending on the objective function. This class of frictionless, energy-conserving optimizers proceeds unobstructed until slowing naturally near the minimal loss, which dominates the phase space volume of the system. Building from studies of chaotic systems such as dynamical billiards, we formulate a specific algorithm with good performance on machine learning and PDE-solving tasks, including generalization. It cannot stop at a high local minimum, an advantage in non-convex loss functions, and proceeds faster than GD+momentum in shallow valleys. 

In this study, a suite of natural wastewater sources is tested to understand the effects of wastewater composition and source on electrochemically driven nitrogen and phosphorus nutrient removal. Kinetics, electrode behavior, and removal efficiency were evaluated during electrochemical precipitation, whereby a sacrificial magnesium (Mg) anode was used to drive precipitation of ammonium and phosphate. The electrochemical reactor demonstrated fast kinetics in the natural wastewater matrices, removing up to 54% of the phosphate present in natural wastewater within 1 min, with an energy input of only 0.04 kWh.m−3. After 1 min, phosphate removal followed a zero-order rate law in the 1 min - 30 min range. The zero-order rate constant (k) appears to depend upon differences in wastewater composition, where a faster rate constant is associated with higher Cl− and NH4+ concentrations, lower Ca2+ concentrations, and higher organic carbon content. The sacrificial Mg anode showed the lowest corrosion resistance in the natural industrial wastewater source, with an increased corrosion rate (vcorr) of 15.8 mm.y−1 compared to 1.9–3.5 mm.y−1 in municipal wastewater sources, while the Tafel slopes (β) showed a direct correlation with the natural wastewater composition and origin. An overall improvement of water quality was observed where important water quality parameters such as total organic carbon (TOC), total suspended solids (TSS), and turbidity showed a significant decrease. An economic analysis revealed costs based upon experimental Mg consumption are estimated to range from 0.19 $.m−3 to 0.30 $.m−3, but costs based upon theoretical Mg consumption range from 0.09 $.m−3 to 0.18 $.m−3. Overall, this study highlights that water chemistry parameters control nutrient recovery, while electrochemical treatment does not directly produce potable water, and that economic analysis should be based upon experimentally-determined Mg consumption data. 

Xenon dual-phase time projections chambers (TPCs) have proven to be a successful technology in studying physical phenomena that require low-background conditions. With$$40\,\textrm{t}$$$40\text{t}$of liquid xenon (LXe) in the TPC baseline design, DARWIN will have a high sensitivity for the detection of particle dark matter, neutrinoless double beta decay ($$0\upnu \upbeta \upbeta $$$0\nu \beta \beta$), and axion-like particles (ALPs). Although cosmic muons are a source of background that cannot be entirely eliminated, they may be greatly diminished by placing the detector deep underground. In this study, we used Monte Carlo simulations to model the cosmogenic background expected for the DARWIN observatory at four underground laboratories: Laboratori Nazionali del Gran Sasso (LNGS), Sanford Underground Research Facility (SURF), Laboratoire Souterrain de Modane (LSM) and SNOLAB. We present here the results of simulations performed to determine the production rate of$${}^{137}$$${}^{137}$Xe, the most crucial isotope in the search for$$0\upnu \upbeta \upbeta $$$0\nu \beta \beta$of$${}^{136}$$${}^{136}$Xe. Additionally, we explore the contribution that other muon-induced spallation products, such as other unstable xenon isotopes and tritium, may have on the cosmogenic background.

 

Small molecule guests influence the functional properties of supramolecular hydrogels. Molecular-level understanding of such sol-gel compositions and structures is challenging due to the lack of long-range order and inherently heterogeneous sol-gel interface. In this study, insight into the uptake process of biologically relevant small molecules into guanosine-quartet(G4) borate hydrogels is obtained by gel-state magic-angle spinning (MAS) NMR spectroscopy. G4∙K + borate hydrogel can absorb up to 0.3 equivalent of cationic methylene blue (MB) without a significant disruption of the G4 fibrils that make up the gel, whereas the addition of over 0.3 equivalents of MB to the same gel leads to a gel-to-sol transition. The gel-to-sol transition process is characterized ex situ by analyzing and comparing the 1 H and 11 B MAS NMR spectra acquired before and after the MB uptake. In particular, 11 B isotropic chemical shifts and quadrupole interactions were determined by analyzing the 11 B MAS NMR spectra acquired at different magnetic fields, 11.7 T, 14.1 T and 20 T, which enable the different local bonding environments of borate anions in sol- and gel domains to be distinguished and identified. By comparison, uptake of heterocyclic molecules such as adenine, cytosine and 1-methylthymine into G4∙Na + borate hydrogels lead to stiff and clear gels while increasing the solubility of the nucleobases as compared to the solubility of the same compounds in water. G4∙Na + gel can uptake one equiv. of adenine with minimal disruption to the sol-gel framework, thus enhancing the adenine solubility up to an order of magnitude as compared to water. Combined multinuclear ( 1 H, 11 B and 23 Na) NMR spectroscopy analysis and vial inversion tests revealed that the nucleobases are embedded into pores of the sol phase rather than being closely interacting with the G-4 fibrils that make up the gel phase. These results indicate that G-4 hydrogels have potential applications as carrier systems for small molecules. Gel-state MAS NMR spectroscopy can be used to gain insight into host-guest interactions in complex heterogeneous sol-gel systems, which is often difficult to obtain from the conventional techniques such as X-ray scattering, electron microscopy and optical spectroscopy. 

Abstract The XENONnT detector uses the latest and largest liquid xenon-based time projection chamber (TPC) operated by the XENON Collaboration, aimed at detecting Weakly Interacting Massive Particles and conducting other rare event searches.The XENONnT data acquisition (DAQ) system constitutes an upgraded and expanded version of the XENON1T DAQ system.For its operation, it relies predominantly on commercially available hardware accompanied by open-source and custom-developed software.The three constituent subsystems of the XENONnT detector, the TPC (main detector), muon veto, and the newly introduced neutron veto, are integrated into a single DAQ, and can be operated both independently and as a unified system.In total, the DAQ digitizes the signals of 698 photomultiplier tubes (PMTs), of which 253 from the top PMT array of the TPC are digitized twice, at ×10 and ×0.5 gain.The DAQ for the most part is a triggerless system, reading out and storing every signal that exceeds the digitization thresholds.Custom-developed software is used to process the acquired data, making it available within ∼30 s for live data quality monitoring and online analyses.The entire system with all the three subsystems was successfully commissioned and has been operating continuously, comfortably withstanding readout rates that exceed ∼500 MB/s during calibration.Livetime during normal operation exceeds 99% and is ∼90% during most high-rate calibrations.The combined DAQ system has collected more than 2 PB of both calibration and science data during the commissioning of XENONnT and the first science run.