Inverse Design Method Research Articles

Enhancement of Magnetic Shielding Based on Low-Noise Materials, Magnetization Control, and Active Compensation: A Review

Magnetic-shielding technologies play a crucial role in the field of ultra-sensitive physical measurement, medical imaging, quantum sensing, etc. With the increasing demand for the accuracy of magnetic measurement, the performance requirements of magnetic-shielding devices are also higher, such as the extremely weak magnetic field, gradient, and low-frequency noise. However, the conventional method to improve the shielding performance by adding layers of materials is restricted by complex construction and inherent materials noise. This paper provides a comprehensive review about the enhancement of magnetic shielding in three aspects, including low-noise materials, magnetization control, and active compensation. The generation theorem and theoretical calculation of materials magnetic noise is summarized first, focusing on the development of spinel ferrites, amorphous, and nanocrystalline. Next, the principles and applications of two magnetization control methods, degaussing and magnetic shaking, are introduced. In the review of the active magnetic compensation system, the forward and inverse design methods of coil and the calculation method of the coupling effect under the ferromagnetic boundary of magnetic shield are explained in detail, and their applications, especially in magnetocardiography (MCG) and magnetoencephalogram (MEG), are also mainly described. In conclusion, the unresolved challenges of different enhancement methods in materials preparation, optimization of practical implementation, and future applications are proposed, which provide comprehensive and instructive references for corresponding research.

Design and Optimization of an Origami Gripper for Versatile Grasping and Manipulation

Robotic grasping and manipulation demand the ability to handle a multitude of objects with different shapes, sizes, quantities, surface smoothness, vulnerability, and stiffness, which is challenging without prior knowledge about object properties. Herein, a novel origami‐inspired gripper for universal grasping is presented. The innovative structure seamlessly transforms a simple uniaxial pulling motion into a flexible and robust envelope or pinch grasp, enabling it to tackle various scenarios. The origami gripper offers distinctive advantages, including scalable and optimizable design, grasping compliance and robustness, providing material flexibility, and providing solutions to challenging manipulation tasks. The working principles of the origami gripper are characterized and analyzed. An optimization‐based inverse design method is presented to adjust gripper properties for various scenarios. Through comprehensive experimentation and evaluation, the gripper's capabilities to grasp various objects with a wide range of distinctive properties, including ultrasoft, slippery, granular, and multiple objects, which is a challenge for the existing robotic grippers, are demonstrated. The research holds promise for transformative applications in areas such as the food industry, waste handling, fine and fragile objects grasping, and environmental sampling.

Harnessing physics-guided neural networks for tailoring the orbital angular momentum spectrum in second harmonic generation

The management of orbital angular momentum (OAM) in frequency conversion processes is essential for numerous applications such as quantum and classical optical communications. This paper presents a wavefront modulation approach for the fundamental beam in second harmonic generation (SHG) to efficiently control the OAM spectrum. We employ an inverse design method to derive the necessary wavefront shape of the fundamental beam for achieving a desired SHG OAM spectrum. Specifically, we introduce an efficient inverse design technique based on physics-guided neural networks (PGNNs) that incorporates the coupled equations governing SHG, aimed at tailoring the OAM spectrum of SHG. Utilizing the proposed PGNN, we design the phase pattern for a spatial light modulator (SLM) to shape the wavefront of the fundamental beam. Furthermore, we present a novel loss function, to our knowledge, that effectively links the OAM of the SHG spectrum and efficiency to the SLM phase pattern and crystal temperature, independent of empirical weight coefficients. The proposed PGNN facilitates the purification of the SHG OAM spectrum, even when the fundamental beam comprises mixed Laguerre–Gaussian (LG) modes. Additionally, we demonstrate the generation of desired SHG spectra using the proposed PGNN framework. This study introduces what we believe to be a groundbreaking inverse design method for developing photonic devices with customized functionalities, addressing challenges associated with traditional data-driven deep learning techniques.

Efficiency improvement and pressure pulsation reduction of volute centrifugal pump through diffuser design optimization

To investigate the effects of load distribution parameters of the diffuser vanes on the efficiency and pressure pulsation of the volute centrifugal pump, the diffuser shape was designed using an inverse design method, and an optimization method was proposed for the diffuser blade load distribution based on the combination of Latin hypercubic sampling, artificial neural network, and non-dominated sorting genetic algorithm-II. Steady and unsteady simulations were performed by solving the three-dimensional Reynolds-averaged Navier–Stokes equations using the shear stress transport k−ω turbulence model. The results obtained from Pearson correlation analysis revealed that the slope values Ks and Kh of the shroud and hub load distribution curves had the most significant effect on the pump head and efficiency. Compared with those of the original model, the efficiency and head of the optimized volute centrifugal pump under the design conditions increased by 3.8 and 3.5 %, respectively. The pressure pulsation intensities in the vaneless regions were effectively mitigated for the optimized volute centrifugal pump. The pressure pulsation coefficients at three times the diffuser vane frequency (3fDIF) reduced by 58.5 and 43.8 % at monitoring points M1 and M2, in the impeller outlet, respectively. The pressure pulsation coefficients at the impeller blade passing frequency (fBPF) reduced by 6.5 and 14.4 % at monitoring points M3 and M4 in the diffuser inlet, respectively. The results showed that the optimized diffuser improved the overall performance of the volute centrifugal pump, and demonstrated the feasibility of the optimization method.

Efficient Inverse Design of Large-Scale, Ultrahigh-Numerical-Aperture Metalens

Efficient design methods for large-scale metalenses are crucial for various applications. The conventional phase-mapping method shows a weak performance under large phase gradients, thus limiting the efficiency and quality of large-scale, high-numerical-aperture metalenses. While inverse design methods can partially address this issue, existing solutions either accommodate only small-scale metalenses due to high computational demands or compromise on focusing performance. We propose an efficient large-scale design method based on an optimization approach combined with the adjoint-based method and the level-set method, which first forms a one-dimensional metalens and then extends it to two dimensions. Taking fabrication constraints into account, our optimization method for large-area metalenses with a near-unity numerical aperture (NA = 0.99) has improved the focusing efficiency from 42% to 60% in simulations compared to the conventional design method. Additionally, it has reduced the deformation of the focusing spot caused by the ultrahigh numerical aperture. This approach retains the benefits of the adjoint-based method while significantly reducing the computational burden, thereby advancing the development of large-scale metalenses design. It can also be extended to other large-scale metasurface designs.

CVAE-Based Inverse Design of Two-Dimensional Honeycomb Pentamode Metastructure for Acoustic Cloaking

In this work, a method for inverse design of two-dimensional honeycomb pentamode metastructures (HPM) based on the Conditional Variational Auto-Encoder (CVAE) is proposed to achieve acoustic cloaking. The parameter distribution of the perfect acoustic cloak with two-dimensional cylindrical Kohn-Shen-Vogelius-Weinstein (KSVW) mapping is first derived. The CVAE model framework is then established along with its loss function in terms of the design parameters of the HPM. The inverse design performance of the deep generative model is evaluated using a large number of random test samples based on finite element simulations, showing that the equivalent mechanical parameters obtained from inverse design are highly consistent with the target parameters of the perfect acoustic cloak. For the HPM cloak design given by the trained deep generative model, the total scattering cross section (TSCS) is significantly reduced as compared to the case without a cloak, thereby demonstrating the effectiveness of the CVAE-based inverse design of acoustic cloak.

Fast inverse design of microwave and infrared Bi-stealth metamaterials based on equivalent circuit model

This work proposed a fast inverse design method for microwave and infrared (IR) bi-stealth metamaterials based on the equivalent circuit model (ECM). Using this method, we designed a microwave and IR bi-stealth metamaterial by deploying a multilayered structure of the indium tin oxide (ITO) film based metasurface. First, the IR emissivity of the ITO film was calculated in the framework of the ECM. Then, an ITO metasurface was proposed to implement low IR emission and high microwave transmission simultaneously. Based on the ECM of the square patch, the ECM of the whole metamaterial was established at the microwave band. An inverse design program was built by incorporating the ECM with genetic algorithm (GA). Structure parameters of the metamaterial were optimized by GA to achieve the broadest microwave stealth bandwidth for the given thickness. Finally, the sample of the optimized bi-stealth metamaterial was prepared and tested. The calculated, simulated, and measured results are in good agreement, showing that such a metamaterial has an IR emissivity of 0.18 in the band from 3 to 14 μm and an efficient microwave stealth band from 4.8 to 17 GHz with a thickness of 4.9 mm. The proposed method will benefit the design and application of microwave and IR bi-stealth metamaterials.

Inverse design of cellular structures with the geometry of triply periodic minimal surfaces using generative artificial intelligence algorithms

Triply periodic minimal surfaces (TPMS) exhibit excellent mechanical and energy absorption properties due to their structural advantages. However, existing porous TPMS structural design methods are constrained to a forward process from structural parameters to mechanical properties. This study proposed an inverse design method that combines bidirectional generative adversarial networks (BiGAN) and mechanical performance targets, resulting in a combined TPMS structure of Primitive and IWP types with superior buffering and energy absorption capabilities. The results show that under a single load value target condition of the designed structure, the minimum deviation index (R2) between the load value corresponding to the displacement point and the target load value is only 0.987, and the maximum mean absolute percentage error (MAPE) is only 5.92 %. When considering the elastic modulus target, the approach successfully conducts two sets of combined structural designs meeting the requirements of both high and low elastic moduli. When targeting the specified load-displacement curve conditions, specifically when combining high elastic modulus with ascending plasticity, the designed structures exhibit an error of only 2.2 % compared to the target property. Moreover, the quasi-static uniaxial compression experiments conducted on additively manufactured designed structures confirm that the experimental curves match the target curves in terms of deformation trends and load value ranges. The success of this inverse design approach for cellular TPMS structures has the potential to expedite new structural material development processes.

Inverse design of metamaterial for dual-band infrared camouflage along with dual-band thermal management

The optical metamaterial for infrared camouflage with thermal management is an artificial structure available to not only evade the detection of various thermal imagers operating in distinct infrared wavebands but also ensure the thermal stability of the target. However, designing such an optical metamaterial is challenging due to the necessity to optimize numerous structural parameters simultaneously, especially metamaterials that are compatible with multiple functions. Herein, this paper proposes a novel inverse design method, combining African vultures optimization algorithm (AVOA) with rigorous coupled-wave analysis (RCWA), to design an optical metamaterial capable of achieving infrared camouflage and thermal management compatibly. The proposed metamaterial enables dual-band infrared camouflage for mid-wave infrared (MWIR, 3–5 μm) and long-wave infrared (LWIR, 8–14 μm), along with thermal management through dual-band non-atmospheric windows of 5–8 μm and 14–17 μm. Comparing to other intelligent optimization algorithms, the AVOA is exceptionally efficient, which only takes less time than others to get better results. This work not only provides theoretical guidance to design an optical metamaterial for infrared camouflage with thermal management, but also has the potential to solve the multi-objective optimization problems of multi-band or wide-band radiative modulation.

A numerical-optimizing method of metasurface inverse design based on method of moment and particle swarm optimization for the scattering field modulation

A numerical-optimizing method of metasurface inverse design based on method of moment and particle swarm optimization for the scattering field modulation

Blade redesign based on inverse design method for energy performance improvement and hydro-induced vibration suppression of a multi-stage centrifugal pump

As the urgency of the global energy crisis escalates and environmental protection standards become more stringent, the industrial sector is placing increased emphasis on enhancing energy efficiency and advancing vibration control technologies. Within this context, multi-stage centrifugal pumps (MSCPs), pivotal in energy systems, play a crucial role in influencing both system performance and environmental impact. This paper embarked on employing an inverse design method (IDM) to innovate the redesign of MSCP blades, introducing a steady-state index for characterizing the intensity of unsteady pressure fluctuations, thereby streamlining optimization costs. Optimization techniques utilizing an artificial neural network model and a multi-objective evolutionary algorithm were employed to achieve an optimal balance between maximizing energy efficiency and reducing hydro-induced vibrations. The optimized MSCP enhanced not only boosting performance but also a 2.75 % increase in weighted efficiency, significantly widening the high-efficiency operation zone. The improvement in vibration characteristics was manifested by an average reduction of more than 25 % in the amplitude of the primary frequency of pressure pulsations within the double volute, with a maximum reduction reaching 50.9 %. Furthermore, the research delved into the analysis of the internal energy dissipation mechanisms of MSCPs, drawing upon the entropy production theory and the enstrophy concept. This analysis reveals that energy dissipation in the mainstream zones is predominantly affected by shear enstrophy, whereas, in the wall regions, it is primarily governed by fluid velocity. The comprehensive performance enhancement of the optimized model is significantly credited to the refinement of the blade profile.

Inverse design method for tailoring the deflection of beams with functionally graded metamaterials

Abstract Functionally graded metamaterials represent a cutting-edge approach to designing structures with cellular materials. By manipulating parameters in specific regions, a customized mechanical response is achieved, optimizing material utilization. Despite various proposed methods to generate functionally graded structures, the challenge of high computational costs persists. This study introduces a novel and computationally efficient inverse design method for beams featuring segment-wise graded metamaterials. Using a semi-analytical approach based on Castigliano’s second theorem, this method significantly reduces computational demands. The approach leverages prior experimental and computational characterizations of the transverse deflection in rectangular, reentrant, and hexagonal honeycombs. Validation through finite element models and experimental tests on additively manufactured beams confirms the adequate performance of the method. The proposed framework successfully generates beams with targeted deflections, demonstrating the method’s capability for inverse design under specific loading and boundary conditions. This approach not only optimizes material utilization but also broadens the application scope of functionally graded metamaterials in structural design.

Data-driven inverse design of the perforated auxetic phononic crystals for elastic wave manipulation

Abstract In addition to the distinctive features of tunable Poisson’s ratio from positive to negative and low stress concentration, the perforated auxetic metamaterials by peanut-shaped cuts have exhibited excellent phononic crystal (PNC) behavior as well for elastic wave manipulation. Thus they have attracted much attention in vibration suppression for dynamic applications. However, traditional structural designs of the auxetic PNCs considerably depend on designers’ experience or inspiration to fulfill the desired multi-objective bandgap properties through extensive trial and error. Hence, developing a more efficient and robust inverse design method remains challenging to accelerate the creation of auxetic PNCs and improve their performance. To shorten this gap, a new machine learning (ML) framework consisting of double back propagation neural network (BPNN) modules is developed in this work to produce desired configurations of the auxetic PNCs matching the customized bandgap. The first inverse BPNN module is trained to establish a logical mapping from the bandgap properties to the structural parameters, and then the second forward BPNN module is introduced to give the new property prediction by using the design configurations generated from the former. The error between the new predictions and the desired target properties is minimized through a limited number of iterations to produce the final optimal objective configurations. The results indicate that the perforated auxetic metamaterials behave relatively wide complete bandgap and the present ML model is effective in designing them with specific bandgaps within or beyond the given dataset. The study provides a powerful tool for designing and optimizing the perforated auxetic metamaterials in dynamic environment.

Analysis on dual Fano resonance in a coupled-resonator waveguide

Dual Fano resonance was demonstrated in a compact coupling system without additional large footprint tunable devices consisting of a grating-coupled waveguide and a micro-racetrack resonator on thin film lithium niobate. A multimode interference model was proposed for the dual Fano resonance system. The inverse design method was used to realize model fitting, validate our model, and analyze our model. Based on the parameters obtained by the inverse design, we further analyzed the influence of different parameters. Our research also shows that through the interaction of two Fano resonance modes, tunable line shape and enhanced extinction ratio can be realized in the transmission spectrum, which has potential applications in optical sensing.

Inverse design of nonlinear phononic crystal configurations based on multi-label classification learning neural networks

Abstract Phononic crystals, as artificial composite materials, have sparked significant interest due to their novel characteristics that emerge upon the introduction of nonlinearity. Among these properties, second-harmonic features exhibit potential applications in acoustic frequency conversion, non-reciprocal wave propagation, and non-destructive testing. Precisely manipulating the harmonic band structure presents a major challenge in the design of nonlinear phononic crystals. Traditional design approaches based on parameter adjustments to meet specific application requirements are inefficient and often yield suboptimal performance. Therefore, this paper develops a design methodology using Softmax logistic regression and multi-label classification learning to inversely design the material distribution of nonlinear phononic crystals by exploiting information from harmonic transmission spectra. The results demonstrate that the neural network-based inverse design method can effectively tailor nonlinear phononic crystals with desired functionalities. This work establishes a mapping relationship between the band structure and the material distribution within phononic crystals, providing valuable insights into the inverse design of metamaterials.

Femtosecond laser direct nanolithography of perovskite hydration for temporally programmable holograms

Modern nanofabrication technologies have propelled significant advancement of high-resolution and optically thin holograms. However, it remains a long-standing challenge to tune the complex hologram patterns at the nanoscale for temporal light field control. Here, we report femtosecond laser direct lithography of perovskites with nanoscale feature size and pixel-level temporal dynamics control for temporally programmable holograms. Specifically, under tightly focused laser irradiation, the organic molecules of layered perovskites (PEA)2PbI4 can be exfoliated with nanometric thickness precision and subwavelength lateral size. This creates inorganic lead halide capping nanostructures that retard perovskite hydration, enabling tunable hydration time constant. Leveraging advanced inverse design methods, temporal holograms in which multiple independent images are multiplexed with low cross talk are demonstrated. Furthermore, cascaded holograms are constructed to form temporally holographic neural networks with programmable optical inference functionality. Our work opens up new opportunities for tunable photonic devices with broad impacts on holography display and storage, high-dimensional optical encryption and artificial intelligence.

Design of Ultra-Compact and Multifunctional Optical Logic Gate Based on Sb2Se3-SOI Hybrid Platform.

Optical logic devices are essential functional devices for achieving optical signal processing. In this study, we design an ultra-compact (4.92 × 2.52 μm2) reconfigurable optical logic gate by using inverse design method with DBS algorithm based on Sb2Se3-SOI integrated platform. By selecting different amorphous/crystalline distributions of Sb2Se3 via programmable electrical triggers, the designed structure can switch between OR, XOR, NOT or AND logic gate. This structure works well for all four logic functions in the wavelength range of 1540-1560 nm. Especially at the wavelength of 1550 nm, the Contrast Ratios for XOR, NOT and AND logic gate are 13.77 dB, 11.69 dB and 3.01 dB, respectively, indicating good logical judgment ability of the device. Our design is robust to a certain range of fabrication imperfections. Even if performance weakens due to deviations, improvements can be obtained by rearranging the configurations of Sb2Se3 without reproducing the whole device.

Integration of Fano resonances with inverse-designed power splitter

Computer-aided intelligent algorithms are beneficial to realize miniaturized devices with ultra-low energy consumption. In this paper, a single-channel Fano structure is designed and the maximum peak-to-valley contrast 0.973 is achieved. A power splitter with the size of 1 μm × 3 μm is proposed by using inverse design method based on topology optimization, whose average transmittance for each port is about 0.489 within the wavelength range of 1450–1650 nm. Finally, the double-channel outputs with the same and different Fano resonances are achieved by integrating with the optimized Fano structures. Our study is conducive to realize efficient and multi-functional photonic integrated circuits.

The active magnetic compensation coil.

The active magnetic compensation coil is of great significance for extensive applications, such as fundamental physics, aerospace engineering, national defense industry, and biological science. The magnetic shielding demand is increasing over past few decades, and better performances of the coil are required. To maintain normal operating conditions for some sensors, active magnetic compensation coils are often used to implement near-zero field environments. Many coil design methods have been developed to design the active compensation coil for different fields. It is opportune to review the development and challenges associated with active magnetic compensation coils. Active magnetic compensation coils are reviewed in this paper in terms of design methods, technology, and applications. Furthermore, the operational principle and typical structures of the coil are elucidated. The developments of the forward design method, inverse design method, and optimization algorithm are presented. Principles of various design methods and their respective advantages and disadvantages are described in detail. Finally, critical challenges in the active magnetic compensation coil techniques and potential research directions have been highlighted.

Effect of free and compound vortex designs on the energy characteristics and operational stability of mixed flow pumps

The effectiveness of the inverse design method has been widely proven in previous studies, but research on the effect of different vortex designs on the performance of mixed flow pumps is relatively scarce. In this paper, the performances of models I1 and I2, which were designed with free and compound vortex designs, respectively, are compared to study the effect of different vortex designs on the energy characteristics and operational stability of mixed flow pumps. The results show that the efficiency of the compound vortex design at 0.8Qdes, 1.0Qdes, and 1.2Qdes is improved by 0.54%, 0.95%, and 5.91%, respectively, compared to that of the free vortex design, and the velocity and pressure pulsations under the design conditions are also significantly reduced. The internal flow analysis shows that the increased efficiency in the compound vortex design is mainly related to the reduction in the local entropy production from the hub to the mid-span and the wall entropy production from the mid-span to the shroud within the diffuser due to the improvement in the jet-wake structure near the hub. The increased operational stability is mainly related to the suppression of low-momentum fluid aggregation and H-S secondary flow caused by the increase in axial velocity near the hub and the spanwise uniformity of the total pressure.