We present the detection of electrons with kinetic energy in the 100 eV range with transition-edge sensors (TESs). This has been achieved with a (100×100)-μm2 Ti/Au bilayer TES, with a critical temperature of about 84 mK. The electrons are produced directly in the cryostat by an innovative cold source based on field emission from vertically aligned multiwall carbon nanotubes. We obtain a Gaussian energy resolution between 0.8 and 1.8 eV for fully absorbed electrons in the (90–101)eV energy range, which is found to be compatible with the resolution of this same device for photons in the same energy range. This work opens possibilities for high-precision energy measurements of low-energy electrons. Published by the American Physical Society 2024

Adjoint methods have been the pillar of gradient-based optimization for decades. They enable the accurate computation of a gradient (sensitivity) of a quantity of interest with respect to all system parameters in one calculation. When the gradient is embedded in an optimization routine, the quantity of interest can be optimized for the system to have the desired behavior. Adjoint methods, however, require the system's governing equations and their Jacobian. In this paper, we propose a computational strategy to infer the adjoint sensitivities from data when the governing equations might be unknown (or partly unknown), and noise might be present. The key component of this strategy is an echo state network, which learns the dynamics of nonlinear regimes with varying parameters, and it evolves dynamically via a hidden state. Although the framework does not make assumptions on the dynamical system, we focus on thermoacoustics, which are governed by nonlinear and time-delayed systems. First, we show that a parameter-aware echo state network (ESN) infers the parametrized dynamics. Second, we derive the adjoint of the ESN to compute two types of sensitivity: (i) parameter sensitivity, which is the gradient of a time-averaged cost functional with respect to physical or design parameters of the system, and (ii) initial condition sensitivity, which is the gradient of a cost functional of the final state with respect to the initial condition. Third, we propose the thermoacoustic echo state network (T-ESN), which embeds the physical knowledge in the network architecture for improved generalization. Fourth, we apply the framework to a variety of nonlinear thermoacoustic regimes of a prototypical system. We show that the T-ESN accurately infers the correct adjoint sensitivities of the acoustic energy with respect to the flame parameters and initial conditions. The results are robust to noisy data, from periodic, through quasiperiodic, to chaotic regimes. The inferred adjoint sensitivities are employed to suppress an instability via steepest descent. We show that a single network predicts the nonlinear bifurcations on unseen scenarios, which allows it to converge to the minimum of the acoustic energy. This work opens new possibilities for gradient-based data-driven design optimization. Published by the American Physical Society 2024

Understanding whether a droplet adheres to or detaches from a flexible filament upon axial impact is of significant interest, particularly in the context of raindrop impact on natural surfaces. This process involves dynamic buckling followed by mode coarsening, dissipating the initial droplet kinetic energy and converting the remaining into elastic energy of the filament. To elucidate this phenomenon, we construct two phase diagrams, one while fixing the filament height and the other the droplet diameter. Notably, we observe that the energy conversion rate is inversely proportional to a Cauchy number, defining the transition between attached and detached droplet in the filament length–falling height diagram. This enables us to derive an expression for the critical falling height as a function of the filament parameters, accounting for the energy conversion rate, which emerges as a key factor for droplet detachment. Published by the American Physical Society 2024

Increasing the operating temperature while enhancing detectivity is paramount for the advancement of HgCdTe infrared detectors. In this context, the integration of plasmonic nanostructures emerges as one of the most intriguing avenues, promising breakthroughs in infrared sensing capabilities. Multiphysics TCAD simulations of pin nanostructured focal plane photodetector arrays unveil the potential benefits of submicron absorber thicknesses, that promise detectivities more than twice as large as those provided by conventional 5μm-thick absorbers, besides enabling operating temperatures up to 260 K. Such performance increase is discussed through the combination of numerical simulations and quantum mechanical treatment based on the occupation number formalism, describing the interaction between plasmonic and optical cavity modes responsible for the spectral broadening of the optical response, allowing for good coverage of the entire mid-infrared band (λ∈[3,5]μm).

A current flowing through a superconductor induces a spatial modulation in its superconducting order parameter, characterized by a wave vector Q related to the total momentum of a Cooper pair. Here we investigate this phenomenon in a p-wave topological superconductor, described by a one-dimensional Kitaev model. We demonstrate that, by treating Q as an extra synthetic dimension, the current-carrying nonequilibrium steady state can be mapped into the ground state of a half-filled two-dimensional Weyl semimetal, whose Fermi surface exhibits Lifshitz transitions when varying the model parameters. Specifically, the transition from type-I to type-II Weyl phases corresponds to the emergence of a gapless p-wave superconductor, where Cooper pairs coexist with unpaired electrons and holes. Such a transition is signaled by the appearance of a sharp cusp in the Q-dependence of the supercurrent, at a critical value Q* that is robust to variations of the chemical potential μ. We determine the maximal current that the system can sustain in the topological phase, and we discuss possible implementations. Published by the American Physical Society 2024