General Design Approach Research Articles

Lateral-Torsional Failure and DSM Design of CFS Lipped Channel Beams at Room and Elevated Temperatures

About a decade ago, in-depth investigations on the behaviour of cold-formed steel (CFS) single-span simply supported lipped channel beams failing in lateral-torsional modes at both room and elevated temperatures were reported at QUT (Queensland Technical University). They revealed a significant underestimation of the lateral-torsional (LT) failure moments by the Direct Strength Method (DSM) global design curve at room temperature, then codified in the Australian/New Zealand and North American specifications. In order to remedy this situation, these authors proposed two novel DSM-based beam strength curve sets, which were found to substantially improve the LT failure moment prediction quality, both at room and elevated temperatures. This work aims at extending the scope of the above investigations, by analysing a visibly larger set of CFS lipped channel beams at elevated temperatures (up to 800 °C), exhibiting (i) various cross-section dimensions and yield stresses, selected to cover wider LT slenderness ranges, (ii) two end support conditions, differing only in the end cross-section wall displacement/rotation and warping restraints (either fully free or fully prevented), and (iii) temperature-dependent steel material properties according with the model prescribed in Part 1-2 of Eurocode 3. The results presented and discussed consist of beam LT post-buckling equilibrium paths and failure moments, obtained through Abaqus shell finite element GMNIA that include critical-mode (LT) initial geometrical imperfections. Lastly, the numerical failure moment data obtained in this work and reported in the literature are used to develop and propose a new unified set of DSM-based strength curves capable of adequately handling beam LT failures at room or elevated temperatures. Since it is shown that the proposed strength curve set provides a quite good LT failure moment prediction quality, it is fair to argue that it constitutes a good starting point to search for an efficient general DSM-based design approach for CFS beams failing in LT modes at room and elevated temperatures.

A Scalable Multi-FPGA Platform for Hybrid Intelligent Optimization Algorithms

The Intelligent Optimization Algorithm (IOA) is widely focused due to its ability to search for approximate solutions to the NP-Hard problem. To enhance applicability to practical scenarios and leverage advantages from diverse intelligent optimization algorithms, the Hybrid Intelligent Optimization Algorithm (H-IOA) is employed. However, IOA typically requires numerous iterations and substantial computing resources, resulting in poor execution efficiency. In complex optimization scenarios, IOA traditionally relies on population partitioning and periodic communication, highlighting the feasibility and necessity of parallelization. To address the challenges above, this paper proposes a general hardware design approach for H-IOA based on multi-FPGA. The approach includes the hardware architecture of multi-FPGA, inter-board communication protocols, population storage strategies, complex hardware functions, and parallelization methodologies, which enhance the computing capabilities of H-IOA. To validate the proposed approach, a case study is conducted, in which an H-IOA integrating genetic algorithm (GA), a simulated annealing algorithm (SA), and a pigeon-inspired optimization algorithm (PIO) are implemented on a multi-FPGA platform. Specifically, the flexible job-shop scheduling problem (FJSP) is employed to verify the potential in industrial applications. Two Xilinx XC6SLX16 FPGA chips are used for hardware implementation, encoded in VHDL, and an AMD Ryzen 7 5800U was used for the software implementation of Python programs (version 3.12.4). The results indicate that hardware implementation is 13.4 times faster than software, which illustrates that the proposed approach effectively improves the execution performance of H-IOA.

Skin-inspired interlocked microstructures with soft-hard synergistic effect for high-sensitivity and wide-linear-range pressure sensing

Flexible pressure sensors have shown great application potential in intelligent robotics, healthcare monitoring, and human–machine interfaces. However, critical challenge exists in reconciling the trade-off between high sensitivity and wide linear sensing range. Here, inspired by the delicate microstructures of human skin, a piezoresistive pressure sensor with soft-hard synergistic interlocked (SHSI) microstructures is proposed to enhance the sensitivity while maintaining broad linear sensing range. The proposed SHSI sensor is face-to-face assembled by a soft sensing layer with spinosum microstructures and a hard interdigital electrode layer with dome microstructures. The design of SHSI microstructures enables efficient mechanical stimulus amplification and consistent compressibility of the sensor under pressure. Consequently, the as-prepared SHSI sensor simultaneously exhibits a maximum sensitivity as high as 67.1 kPa−1 and a wide linear working range up to 650 kPa. Meanwhile, low limit of detection (7 Pa), fast response (40 ms) and recovery (37 ms), as well as prominent stability and durability over 10,000 cycles of the sensor are realized. Owing to these outstanding sensing performances, the successful applications of the SHSI sensor in physiological signal monitoring and wearable human–machine interfaces are demonstrated. This work offers a general design approach to achieve coordination of high sensitivity and broad linear range of flexible pressure sensors.

Numerical study of low‐rise composite steel frame responses to blast loading using direct simulation method

AbstractThis paper investigated the blast behavior of a low‐rise composite steel structure of three stories subjected to internal and external explosions for the same explosive charge of 250 kg TNT. A comparison of three various blast scenarios is aimed at better understanding how blast waves propagate in confined risk zones and their damage effects on far and exposed elements to an explosive charge. Evaluation of the damage level and the overall response of the proposed numerical model is done by estimating the adequacy of structural members subjected to blast loading using general limits in attempting to check the structure's strength and regularity. The analysis was based on load combinations and damage criteria according to the Unified Facilities Criteria which are general design approaches suitable for civil design applications in forecasting blast loads and structural system responses. The overall behavior of this structure was simulated based on a dynamic analysis by the direct simulation approach, which was chosen for modeling blast loads using the Friedlander blast load equation, and the simpler, less expensive, more accurate, and realistic A.T.‐BLAST model to deduce the simplified blast‐wave overpressure profile. The material nonlinearity at a high strain rate using the Johnson‐Cook strength and concrete plasticity damage model is studied dynamically using ABAQUS finite element code to simulate the explicit dynamic nonlinear analysis. The overall response of the proposed numerical model was evaluated by estimating the adequacy of structural members, considering the blast load as the initial cause of failure, such as axial plastic strain, internal forces limits, maximum deformation, support rotation, demand‐capacity‐ratio (DCRshear/moment), drift index and material damage model. The position of the explosive charge played an important role in determining the rate at which the structural element begins to plastic strains, displacements, moments, or rotations beyond the limits, and then key elements should be considered in structural design against progressive collapse. Results showed that steel members exhibit early indicators of failure, such as buckling necking, shear tearing, or plastic hinges, whereas concrete slabs break up immediately due to brittleness. DCRmoment values successfully showed the columns in which the first plastic joint can occur, whereas DCRshear values signaled the onset of shear failure at connections. Besides, plastic hinges played an important role in dissipating energy and preventing total structural collapse via the Strong Column‐Weak Beam design concept, which appears repeatedly in this study. The structure is a well‐designed and ductile building capable of supporting higher loads and is considered to be repairable and intact.

Accelerated discovery of refractory high-entropy alloys for strength-ductility co-optimization: An exploration in NbTaZrHfMo system by machine learning

High temperature (HT) strength and room temperature (RT) ductility trade-offs are always unavoidable in the design of refractory high entropy alloys (RHEAs). Exploring the vast chemistry space to find optimally strong and ductile RHEAs remains a highly challenging task. Herein, we formulate a machine learning-based design strategy fusing uncertainty estimation and clustering analysis to explore a special alloy system (NbTaZrHfMo) for collaborative optimization of HT strength and RT ductility. Four non-equimolar alloys with a superior combination of HT strength, RT ductility and HT specific yield strength were discovered and synthetized. The influence of elements on mechanical properties are analyzed and an optimal composition range is identified based on model prediction. This work provides a general design approach enabling the concurrent optimization of conflicting properties with a small data-trained machine learning model, thereby producing a recipe to accelerate the discovery of desired RHEAs and other materials within a vast search space.

Inverse machine learning framework for optimizing gradient honeycomb structure under impact loading

In this study, an inverse design framework was constructed to explore gradient honeycomb structures (HCS) with high impact resistance. By establishing the relationship between the height of the cell and the cell-wall angle, HCS with different gradient modes were designed. The developed machine learning (ML) framework consisted of a forward regression model based on neural network (NN) and an inverse optimization model based on generative adversarial network (GAN). The regression model surrogated finite element analysis (FEA) to rapidly provide corresponding mechanical properties for the generated data of GAN. To ensure that the generated data met the desired design targets, additional physical constraints were incorporated into the generator of the GAN. This ensured that the network output not only consisted of valid data but also exhibited superior impact resistance. The results demonstrated that the trained ML model optimized both specific energy absorption (SEA) and initial peak stress of HCS. It even discovered high-performance gradient designs that outperformed the original data, with a maximum energy absorption 49.5% higher than that of uniform HCS. Moreover, the gradient modes and structural parameters of superior designs were identified, which is of great significance for the gradient design of HCS under impact loading. As a general design approach, this ML framework holds significant potential for the optimization design of metamaterials in other structures or with different mechanical properties.

Designer spectrographs for applications in the advanced undergraduate instructional lab

In an advanced undergraduate instructional laboratory, it is often necessary to analyze the spectrum of light emitted from an experimental setup. There are numerous instruments that are used to accomplish this analysis, including spectrometers and spectrographs. In this report, we present 3D-printed, low-budget spectrographs (∼ US $200), which are specifically designed for different applications. For example, one can either observe a visible spectrum over a large range of wavelengths about a desired center wavelength or achieve more precise measurements by choosing a smaller part of the visible spectrum. Our generalized design approach is well within the knowledge base of advanced undergraduate physics majors and can be applied to a wide range of applications within the visible spectrum. To demonstrate the utility of these designer spectrographs, we provide examples of recording multiple doublets in the sodium spectrum (a determination of the fine structure spin-orbit splitting of the 3p energy level) as well as measuring the wavelength differences between the hydrogen and deuterium Balmer alpha lines (a measurement of an isotope shift).

A Generalized Residue Number System Design Approach for Ultralow-Power Arithmetic Circuits Based on Deterministic Bit-Streams

The peak power consumption has become an important concern in the hardware design process of some of today’s applications, such as Energy Harvesting (EH) and Bio-Implantable (BI) electronic devices. The limited peak harvested power in EH devices and heating concerns in BI devices are the main reasons for power control’s importance in these devices. This paper proposes a generalized design approach for ultra-low-power arithmetic circuits. The proposed circuits are based on Residue Number System (RNS) combined with deterministic bit-streams. The resulting circuits can be used in systems with a restricted power budget. We suggest several approaches to design generic hardware-efficient adders, multipliers, multiply-accumulate units (MAC), forward converters (FC), and reverse converters (RC). Using the proposed approach, designing these components for any moduli of the RNS can be performed through simple bit-width adjustments in the circuits. The synthesis results show that the proposed adder achieves, on average, 69% and 2% lower area compared to the bit-serial and a state-of-the-art RNS adder, respectively. Furthermore, the proposed multiplier outperforms the bit-serial, interleaved, and a state-of-the-art design for multiplying RNS numbers by, on average, 57%, 60%, and 77% in terms of power consumption, respectively. The efficiency of our approach is shown via two essential applications, digital signal processing and machine learning. We implement an FFT engine using the proposed method. Compared to prior RNS implementations, our design achieves 47% lower power consumption. We also implement a CNN accelerator’s Processing Element (PE) with the proposed computation elements. Our design provides considerable speedup and lower power consumption compared to a state-of-the-art ultra-lower-power design.

Ultrafast Detection of Monoamine Oxidase A in Live Cells and Clinical Glioma Tissues Using an Affinity Binding‐Based Two‐Photon Fluorogenic Probe

AbstractAbnormal expression of monoamine oxidase A (MAO−A) has been implicated in the development of human glioma, making MAO−A a promising target for therapy. Therefore, a rapid determination of MAO−A is critical for diagnosis. Through in silico screening of two‐photon fluorophores, we discovered that a derivative of N,N‐dimethyl‐naphthalenamine (pre‐mito) can effectively fit into the entrance of the MAO−A cavity. Substitutions on the N‐pyridine not only further explore the MAO−A cavity, but also enable mitochondrial targeting ability. The aminopropyl substituted molecule, CD1, showed the fastest MAO−A detection (within 20 s), high MAO−A affinity and selectivity. It was also used for in situ imaging of MAO−A in living cells, enabling a comparison of the MAO−A content in human glioma and paracancerous tissues. Our results demonstrate that optimizing the affinity binding‐based fluorogenic probes significantly improves their detection rate, providing a general approach for rapid detection probe design and optimization.

Ultrafast Detection of Monoamine Oxidase A in Live Cells and Clinical Glioma Tissues Using an Affinity Binding-Based Two-Photon Fluorogenic Probe.

Abnormal expression of monoamine oxidase A (MAO-A) has been implicated in the development of human glioma, making MAO-A a promising target for therapy. Therefore, a rapid determination of MAO-A is critical for diagnosis. Through in-silico screening of two-photon fluorophores, we discovered that a derivative of N,N-dimethyl-naphthalenamine (pre-mito) can effectively fit into the entrance of MAO-A cavity. Substitutions on the N-pyridine not only further explore the MAO-A cavity, but also enable mitochondrial targeting ability. The aminopropyl substituted molecule, CD1, showed the fastest MAO-A detection (within 20 s), high MAO-A affinity and selectivity. It was also used for in situ imaging of MAO-A in living cells, enabling a comparison of the MAO-A content in human glioma and paracancerous tissues. Our results demonstrate that optimizing the affinity binding-based fluorogenic probes significantly improves their detection rate, providing a general approach for rapid detection probe design and optimization.

Impact analysis and optimization of notched high-gain Antipodal Vivaldi antenna using machine learning

Optimizing antenna parameters without knowing their impact on the gain is a time-consuming and iterative process. This article shows how the Classification and Regression Tree (CART) technique, the Random Forest (RF) algorithm, and the Principal Component Analysis (PCA) method is used to study the effect of geometrical parameters of rectangular notches of the Antipodal Vivaldi antenna on gain. Carving out the notches is a general approach for end-fire antenna design. Integrating the EM simulation with machine learning could reduce the time spent on AVA design. In this approach, the gain category of the antenna under design: Low, Medium, and High, is first classified by the three multiclass machine learning models, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN), and Support Vector Machine (SVM). When the predicted category of gain belongs to the High class, in that case, the four regression models, Polynomial, SVM, ANN, and RF, predict the gain value to anticipate the antenna gain according to the notch dimensions to reduce the optimization time of the simulation-driven antenna. In this work, the band-limited approach of notches on gain is also been validated using simulation before fabrication. Machine learning models are optimized the antenna parameters to achieve a high gain within the frequency range of 20 to 40 GHz. A peak simulated gain of 19 dB is achieved at the frequency of 27 GHz. The proposed structure is fabricated utilizing a single-layer Rogers substrate (RO4003C) with a dielectric constant of 3.38 and compact dimensions of 96 mm × 174 mm × 0.508 mm, i.e., 0.32 × 0.58 × 0.0017 λ03; here the symbol λ0 denotes the wavelength of free space at the minimum operating frequency.

Spatially-aware group interaction design framework for collaborative room-oriented immersive systems

Room-oriented immersive systems are human-scale built environments that enable collective multi-sensory immersion in virtual space. Although such systems are currently seeing increasing applications in public realms, limited understanding remains regarding how humans interact with the virtual environments displayed within. Synthesizing virtual reality ergonomics and human-building interaction (HBI) knowledge allows us to investigate these systems meaningfully. In this work, we develop a model of content analysis based on hardware components of the Collaborative-Research Augmented Immersive Virtual Environment Laboratory (CRAIVE-Lab) and the Cognitive Immersive Room (CIR) at Rensselaer Polytechnic Institute. Situating ROIS as a joint cognitive system, this model consists of five categories of qualitative factors: 1) general design approach; 2) topological relationships; 3) features of tasks; 4) hardware-specific design modalities; and 5) interactive qualities. We probe the comprehensiveness of this model using existing design scenarios at the CRAIVE-Lab and the CIR featuring both application-based and experience-based designs. Through these case studies, the robustness of this model in its representation of design intention is observed, with limitations on temporal constraints. In creating this model, we establish foundations for more detailed assessments of the interactive qualities of systems alike.

A Tandem-Locked Fluorescent NETosis Reporter for the Prognosis Assessment of Cancer Immunotherapy.

NETosis, the peculiar type of neutrophil death, plays important roles in pro-tumorigenic functions and inhibits cancer immunotherapy. Non-invasive real-time imaging is thus imperative for prognosis of cancer immunotherapy yet remains challenging. Herein, we report a Tandem-locked NETosis Reporter 1 (TNR1 ) that activates fluorescence signals only in the presence of both neutrophil elastase (NE) and cathepsin G (CTSG) for the specific imaging of NETosis. In the aspect of molecular design, the sequence of biomarker-specific tandem peptide blocks can largely affect the detection specificity towards NETosis. In live cell imaging, the tandem-locked design allows TNR1 to differentiate NETosis from neutrophil activation, while single-locked reporters fail to do so. The near-infrared signals from activated TNR1 in tumor from living mice were consistent with the intratumoral NETosis levels from histological results. Moreover, the near-infrared signals from activated TNR1 negatively correlated with tumor inhibition effect after immunotherapy, thereby providing prognosis for cancer immunotherapy. Thus, our study not only demonstrates the first sensitive optical reporter for noninvasive monitoring of NETosis levels and evaluation of cancer immunotherapeutic efficacy in tumor-bearing living mice, but also proposes a generic approach for tandem-locked probe design.

Design Trade-Off Between Torque Density and Power Factor in Surface-Mounted PM Vernier Machines Through Closed-Form Per-Unit Equations

Benefited from flux modulation effects, surface-mounted permanent magnet vernier machines (SPMVMs) present the high-torque low-speed properties, which can become the potential candidates for direct-drive applications. However, their power factor is inferior to conventional PM machines due to the large inductance caused by parasitic no-working harmonics. This paper is devoted to propose some design considerations of SPMVMs to make a good compromise between torque density and power factor. Via constructing closed-from per-unit equations, the cross-coupling influences of slot/pole combinations and normalized geometric variables on machine performances are revealed. It is found that there is a tradeoff between torque density and power factor. The high magnet thickness to air-gap length ratio is beneficial to decrease inductance, while the flux modulation effect under the large equivalent air-gap length would be impaired. Moreover, the pole-pair ratio, i.e., the PM pole-pair to armature winding pole-pair, should be carefully selected, where the SPMVMs with high pole-pair ratio have the relatively high magnetic loading owing to the strong flux modulation effects, whereas they suffer from the low power factor due to serious harmonic leakage inductance. In particular, taking the end-winding length into consideration, the high torque advantages of high pole-pair ratio SPMVMs under the same copper losses can be well performed with high length-radius ratio. Combined with the analysis, the preferable selections of critical parameters to satisfy various technical indexes are determined. Then, the general design approach is proposed, and two design examples are built and compared. Meanwhile, finite element analysis (FEA) and prototype experiments are carried out to verify the feasibility.

Longitudinal evolution from scalar to vector beams assembled from all-dielectric metasurfaces.

Vector vortex beams (VVBs) with non-uniform polarization states have a wide range of applications, from particle capture to quantum information. Here, we theoretically demonstrate a generic design for all-dielectric metasurfaces operating in the terahertz (THz) band, characterized as a longitudinal evolution from scalar vortices carrying homogeneous polarization states to inhomogeneous vector vortices with polarization singularities. The order of the converted VVBs can be arbitrarily tailored by manipulating the topological charge embedded in two orthogonal circular polarization channels. The introduction of the extended focal length and the initial phase difference effectively guarantees the smoothness of the longitudinal switchable behavior. A generic design approach based on vector-generated metasurfaces can assist in the exploration of new singular properties of THz optical fields.

Towards Delphi Rigor: An Investigation in the Context of Maturity Model Development

The maturity model (MM) and Delphi research areas are extensive and diverse, leading to numerous approaches. This study addresses the Delphi method regarding its rigor requirements within the IS literature. To this end, the example of maturity model development is investigated. Hence, Delphi studies for MM development are identified and analyzed regarding their rigorous application and design. The examination focuses on the connections between maturity model aspects and the Delphi methodology. Hence, relevant aspects of maturity model and Delphi literature are elaborated, and criteria for methodological rigor are derived. A key challenge is linking the method to the specific design objective (in this study example, the development of a maturity model). After conducting a literature search to identify studies that use the Delphi method for MM development, these criteria are used as a basis for deductive content analysis. The results indicate a lack of clarity regarding the methodology, as different aspects are reported, although the general demands, starting points, and goals were similar. A need for design guidelines for planning and conducting Delphi studies is emphasized and addressed in this paper. Hence, guidelines for designing Delphi studies are developed and presented, considering relevant aspects for ensuring rigorous implementation. The focus lies on the linkage between study design and intended model elements, as this demonstrates the complexity of the study design and the relevance of the design decisions through an example. The guidelines integrate the different methodological aspects of maturity model development and the Delphi methodology, providing an orientation framework for the design process of such research projects. Therefore, this study contributes to existing research by proposing design guidelines for Delphi studies to foster rigor in the specific context of maturity model development. Although the presented guidelines focus on the maturity model context, the general design approach and decisions are transferable and applicable to other domains. Hence, this research contributes to the Delphi literature by providing insights into how relevant elements should be addressed in the designing process of a Delphi Study. Scholars should investigate how the presented guidelines must be adapted for other domains in future research.

Perspective on Meta-Boundaries

The judicious design of the electromagnetic boundary provides a crucial route to control light–matter interactions, and it is thus fundamental to basic science and practical applications. General design approaches rely on the manipulation of bulk properties of the superstrate or substrate and on the modification of boundary geometries. Due to the recent advent of metasurfaces and low-dimensional materials, the boundary can be flexibly featured with a surface conductivity, which can be rather complex but provide an extra degree of freedom to regulate the propagation of light. In this Perspective, we denote the boundary with a nonzero surface conductivity as the meta-boundary. The meta-boundaries are categorized into four types, namely, isotropic, anisotropic, biisotropic, and bianisotropic meta-boundaries, according to the electromagnetic boundary conditions. Accordingly, the latest developments for these four kinds of meta-boundaries are reviewed. Finally, an outlook on the research tendency of meta-boundaries is provided, particularly on the manipulation of light–matter interactions by simultaneously exploiting meta-boundaries and metamaterials.

Design and Detailing Recommendations of Slotted-Hidden-Gap Connection for Square HSS Brace Members

The slotted-hidden-gap (SHG) connection eliminates the need to reinforce the slot region of hollow structural sections (HSS) braces of concentrically braced frames (CBFs). However, the existing design approach for SHG connections is rather empirical and limited by the range of the connection geometries and materials that had previously been tested. A general design approach based on the findings of a large-scale parametric study is presented in this paper, where the most critical parameters of the connection were varied. Different weld configurations were investigated to examine the effect of shear lag on the overall performance of the brace. The inelastic performance of SHG-connected braces designed using the proposed approach was validated by means of numerically simulating the resulting braces and connections and subjecting them to a reversed-cyclic loading protocol. The simulated braces were able to attain their yield tensile resistance and fracture away from the connection region while sustaining an axial deformation corresponding to an average story drift of 5.43%. The proposed design and detailing method was, as such, found to be effective in the design of square HSS SHG connection braces ranging in size and steel grade.

Strain engineering a persistent spin helix with infinite spin lifetime

Persistent spin textures (PSTs) in solid-state materials arise from a unidirectional spin-orbit field in momentum space and offer a route to deliver long carrier spin lifetimes sought for future quantum microelectronic devices. Nonetheless, few three-dimensional materials are known to host PSTs owing to crystal symmetry and chemical requirements. There are even fewer examples demonstrated experimentally. Here we report that high-quality persistent spin textures can be obtained in the polar point groups containing an odd number of mirror operations. We use representation theory analysis and electronic structure calculations to formulate general discovery principles to identify PSTs hidden in known complex ternary layered and perovskite structures with large electric polarizations. We then show some of these materials exhibit PSTs without requiring any special crystalline symmetries. This finding removes the limitation imposed by mirror-symmetry protected PSTs that has limited compound discovery. Our general design approach enables the pursuit of persistent spin helices in materials exhibiting the $C_{3v}$ crystal class adopted by many quantum materials exhibiting large Rashba coefficients.

Enriching Metasurface Functionalities by Fully Employing the Inter‐Meta‐Atom Degrees of Freedom for Double‐Key‐Secured Encryption

AbstractCreating new functionalities has long been the driving impetus for the development of metasurfaces and meta‐devices. This has routinely been achieved by exploiting the intrinsic degrees of freedom (DoFs) of their building blocks—meta‐atoms, such as searching for new materials or increasing geometric variations. However, these approaches are ultimately bottlenecked by the limited species of natural materials, and often incur additional design or fabrication difficulties. In this work, the authors resort to the relative and absolute structural DoFs at the inter‐meta‐atom (IMA) level to circumvent the above‐mentioned limitations. Eventually, a novel double‐key‐secured encryption system with increased image storage capacity approaching the theoretical limit is successfully devised by fully employing all the IMA DoFs. The generic design approach, which provides a new means to enrich the metasurface functionalities by expanding the capacity of meta‐devices, can be readily adapted in the design of other nanophotonic systems.