physics.app-ph

10 posts

arXiv:2404.10863v2 Announce Type: replace-cross Abstract: Hypo-elastoplasticity is a framework suitable for modeling the mechanics of many hard materials that have small elastic deformation and large plastic deformation. In most laboratory tests for these materials the Cauchy stress is in quasi-static equilibrium. Rycroft et al. discovered a mathematical correspondence between this physical system and the incompressible Navier-Stokes equations, and developed a projection method similar to Chorin's projection method (1968) for incompressible Newtonian fluids. Here, we improve the original projection method to simulate quasi-static hypo-elastoplasticity, by making three improvements. First, drawing inspiration from the second-order projection method for incompressible Newtonian fluids, we formulate a second-order in time numerical scheme for quasi-static hypo-elastoplasticity. Second, we implement a finite element method for solving the elliptic equations in the projection step, which provides both numerical benefits and flexibility. Third, we develop an adaptive global time-stepping scheme, which can compute accurate solutions in fewer timesteps. Our numerical tests use an example physical model of a bulk metallic glass based on the shear transformation zone theory, but the numerical methods can be applied to any elastoplastic material.

Jiayin Lu, Chris H. Rycroft1/22/2025

arXiv:2501.11323v1 Announce Type: new Abstract: Reconfigurable intelligent surface (RIS) is a two-dimensional periodic structure integrated with a large number of reflective elements, which can manipulate electromagnetic waves in a digital way, offering great potentials for wireless communication and radar detection applications. However, conventional RIS designs highly rely on extensive full-wave EM simulations that are extremely time-consuming. To address this challenge, we propose a machine-learning-assisted approach for efficient RIS design. An accurate and fast model to predict the reflection coefficient of RIS element is developed by combining a multi-layer perceptron neural network (MLP) and a dual-port network, which can significantly reduce tedious EM simulations in the network training. A RIS has been practically designed based on the proposed method. To verify the proposed method, the RIS has also been fabricated and measured. The experimental results are in good agreement with the simulation results, which validates the efficacy of the proposed method in RIS design.

Zhen Zhang, Jun Hui Qiu, Jun Wei Zhang, Hui Dong Li, Dong Tang, Qiang Cheng, Wei Lin1/22/2025

arXiv:2501.11553v1 Announce Type: new Abstract: Systemic drug administration often causes off-target effects limiting the efficacy of advanced therapies. Targeted drug delivery approaches increase local drug concentrations at the diseased site while minimizing systemic drug exposure. We present a magnetically guided microrobotic drug delivery system capable of precise navigation under physiological conditions. This platform integrates a clinical electromagnetic navigation system, a custom-designed release catheter, and a dissolvable capsule for accurate therapeutic delivery. In vitro tests showed precise navigation in human vasculature models, and in vivo experiments confirmed tracking under fluoroscopy and successful navigation in large animal models. The microrobot balances magnetic material concentration, contrast agent loading, and therapeutic drug capacity, enabling effective hosting of therapeutics despite the integration complexity of its components, offering a promising solution for precise targeted drug delivery.

Fabian C. Landers, Lukas Hertle, Vitaly Pustovalov, Derick Sivakumaran, Oliver Brinkmann, Kirstin Meiners, Pascal Theiler, Valentin Gantenbein, Andrea Veciana, Michael Mattmann, Silas Riss, Simone Gervasoni, Christophe Chautems, Hao Ye, Semih Sevim, Andreas D. Flouris, Josep Puigmart\'i-Luis, Tiago Sotto Mayor, Pedro Alves, Tessa L\"uhmann, Xiangzhong Chen, Nicole Ochsenbein, Ueli Moehrlen, Philipp Gruber, Miriam Weisskopf, Quentin Boehler, Salvador Pan\'e, Bradley J. Nelson1/22/2025

arXiv:2501.11947v1 Announce Type: new Abstract: We propose a modeling framework for finite viscoelasticity, inspired by the kinematic assumption made by Green and Naghdi in plasticity. This approach fundamentally differs from the widely used multiplicative decomposition of the deformation gradient, as the intermediate configuration, a concept that remains debated, becomes unnecessary. The advent of the concept of generalized strains allows the Green-Naghdi assumption to be employed with different strains, offering a flexible mechanism to separate inelastic deformation from total deformation. This leads to a constitutive theory in which the kinematic separation is adjustable and can be calibrated. For quadratic configurational free energy, the framework yields a suite of finite linear viscoelasticity models governed by linear evolution equations. Notably, these models recover established models, including those by Green and Tobolsky (1946) and Simo (1987), when the Seth-Hill strain is chosen with the strain parameter being -2 and 2, respectively. It is also related to the model of Miehe and Keck (2000) when the strain is of the Hencky type. We further extend the approach by adopting coercive strains, which allows us to define an elastic deformation tensor locally. This facilitates modeling the viscous branch using general forms of the configurational free energy, and we construct a micromechanical viscoelastic model as a representative instantiation. The constitutive integration algorithms of the proposed models are detailed. We employ the experimental data of VHB 4910 to examine the proposed models, which demonstrate their effectiveness and potential advantages in the quality of fitting and prediction. Three-dimensional finite element analysis is also conducted to assess the influence of different strains on the viscoelastic behavior.

Ju Liu, Chongran Zhao, Jiashen Guan1/22/2025

arXiv:2402.13436v2 Announce Type: replace-cross Abstract: Planar electromagnetic actuators based on the principle of linear motors are widely employed for micro and nano positioning applications. These actuators usually employ a planar magnetic platform driven by a co-planar electromagnetic coil. While these actuators offer a large motion range and high positioning resolution, their actuation bandwidth is limited due to relatively small electromagnetic stiffness. We report optimization of the design parameters of the electromagnetic coil and the magnetic assembly to maximize the electromagnetic force and stiffness. Firstly, we derive closed-form expressions for the electromagnetic forces and stiffness, which enable us to express these quantities in terms of the design parameters of the actuator. Secondly, based on these derived expressions, we estimate the optimum values of the design parameters to maximize force and stiffness. Notably, for the optimum design parameters, the force and stiffness per unit volume can be increased by two and three orders of magnitude, respectively by reducing the pitch of the electromagnetic coil by a factor of 10. Lastly, we develop an electromagnetic actuator and evaluate its performance using a Microelectromechanical system (MEMS) based force sensor. By operating the force sensor in a feedback loop, we precisely measure the generated electromagnetic forces for different design parameters of the actuator. The experimental results obtained align closely with the analytical values, with an error of less than 15%.

K. S. Vikrant, D. Dadkhah, S. O. Reza Moheimani1/22/2025

arXiv:2404.19602v2 Announce Type: replace-cross Abstract: In this article, we investigate some issues related to the quantification of uncertainties associated with the electrical properties of graphene nanoribbons. The approach is suited to understand the effects of missing information linked to the difficulty of fixing some material parameters, such as the band gap, and the strength of the applied electric field. In particular, we focus on the extension of particle Galerkin methods for kinetic equations in the case of the semiclassical Boltzmann equation for charge transport in graphene nanoribbons with uncertainties. To this end, we develop an efficient particle scheme which allows us to parallelize the computation and then, after a suitable generalization of the scheme to the case of random inputs, we present a Galerkin reformulation of the particle dynamics, obtained by means of a generalized Polynomial Chaos approach, which allows the reconstruction of the kinetic distribution. As a consequence, the proposed particle-based scheme preserves the physical properties and the positivity of the distribution function also in the presence of a complex scattering in the transport equation of electrons. The impact of the uncertainty of the band gap and applied field on the electrical current is analysed.

Andrea Medaglia, Giovanni Nastasi, Vittorio Romano, Mattia Zanella1/14/2025

arXiv:2409.12483v2 Announce Type: replace-cross Abstract: Numerical methods of the ADER family, in particular finite-element ADER-DG and finite-volume ADER-WENO methods, are among the most accurate numerical methods for solving quasilinear PDE systems. The internal structure of ADER-DG and ADER-WENO numerical methods contains a large number of basic linear algebra operations related to matrix multiplications. The main interface of software libraries for matrix multiplications for high-performance computing is BLAS. This paper presents an effective method for integration the standard functions of the BLAS interface into the implementation of these numerical methods. The calculated matrices are small matrices; at the same time, the proposed implementation makes it possible to effectively use existing JIT technologies. The proposed approach immediately operates on AoS, which makes it possible to efficiently calculate flux, source and non-conservative terms without need to carry out transposition. The obtained computational costs demonstrated that the effective implementation, based on the use of the JIT functions of the BLAS, outperformed both the implementation based on the general BLAS functions and the vanilla implementations by several orders of magnitude. At the same time, the complexity of developing an implementation based on the approach proposed in this work does not exceed the complexity of developing a vanilla implementation.

I. S. Popov1/14/2025

arXiv:2412.16803v1 Announce Type: new Abstract: Electroadhesion is an electrically controllable switchable adhesive commonly used in soft robots and haptic user interfaces. It can form strong bonds to a wide variety of surfaces at low power consumption. However, electroadhesive clutches in the literature engage to and release from substrates several orders of magnitude slower than a traditional electrostatic model would predict, limiting their usefulness in high-bandwidth applications. We develop a novel electromechanical model for electroadhesion, factoring in polarization dynamics and contact mechanics between the dielectric and substrate. We show in simulation and experimentally how different design parameters affect the engagement and release times of electroadhesive clutches to metallic substrates. In particular, we find that higher drive frequencies and narrower substrate aspect ratios enable significantly faster dynamics. We demonstrate designs with engagement times under 15 us and release times as low as 875 us, which are 10x and 17.1x faster, respectively, than the best times found in prior literature.

Ahad M. Rauf, Sean Follmer12/24/2024

arXiv:2412.16099v1 Announce Type: cross Abstract: Tantalum (Ta) has recently received considerable attention in manufacturing robust superconducting quantum circuits. Ta offers low microwave loss, high kinetic inductance compared to aluminium (Al) and niobium (Nb), and good compatibility with complementary metal-oxide-semiconductor (CMOS) technology, which is essential for quantum computing applications. Here, we demonstrate the fabrication engineering of thickness-dependent high quality factor (high-Q_i) Ta superconducting microwave coplanar waveguide resonators. All films are deposited on high-resistivity silicon substrates at room temperature without additional substrate heating. Before Ta deposition, a niobium (Nb) seed layer is used to ensure a body-centred cubic lattice ({\alpha}-Ta) formation. We further engineer the kinetic inductance (L_K) resonators by varying Ta film thicknesses. High L_K is a key advantage for applications because it facilitates the realisation of high-impedance, compact quantum circuits with enhanced coupling to qubits. The maximum internal quality factor Q_i of ~ 3.6 * 10^6 is achieved at the high power regime for 100 nm Ta, while the highest kinetic inductance is obtained to be 0.6 pH/sq for the thinnest film, which is 40 nm. This combination of high Q_i and high L_K highlights the potential of Ta microwave circuits for high-fidelity operations of compact quantum circuits.

Shima Poorgholam-Khanjari, Valentino Seferai, Paniz Foshat, Calum Rose, Hua Feng, Robert H. Hadfield, Martin Weides, Kaveh Delfanazari12/23/2024

arXiv:2403.10990v3 Announce Type: replace-cross Abstract: Quantum noise plays a pivotal role in understanding quantum transport phenomena, including current correlations and wave-particle duality. A recent focus in this domain is $\Delta_T$ noise, which arises due to a finite temperature difference in the absence of charge current at zero voltage bias. This paper investigates $\Delta_T$ noise in mesoscopic hybrid junctions with insulators, where the average charge current is zero at zero voltage bias, through the measurement of quantum shot noise, i.e., $\Delta_T$ noise. Notably, we find that the $\Delta_T$ noise in metal-insulator-superconductor junctions is significantly larger than in metal-insulator-metal junctions. Furthermore, our results reveal that $\Delta_T$ noise initially increases with barrier strength, peaks, and then decreases, while it shows a steady increase with temperature bias, highlighting the nuanced interplay between barrier characteristics and thermal gradients.

Sachiraj Mishra, A Rajmohan Dora, Tusaradri Mohapatra, Colin Benjamin12/23/2024