Robust Design Scheme Research Articles

Designing Robust Single Atom Catalysts by Three-in-One Strategy: Sub-1-nm Space Confining, Bimetallic Bonding and Reaction-Induced Forming Active Sites.

It is imperative to design robust single atom catalysts (SACs) that maintain the stability of the active component under diverse reaction conditions and prevent aggregation or deactivation. Confining the single atom active site within sub-nanometer (sub-1-nm) spaces has proven effective in enhancing the stability and activity of the catalyst, owing to the strong constraints and regulations imposed on atomic behavior at this scale. Bimetallic bond atomic sites, comprising two distinct metal compositions, often exhibit unique electronic structures and catalytic properties. Designing SACs under reaction-induced conditions, such as varying temperatures, pressures, and atmospheres, can facilitate a deeper understanding of the formation and migration behavior of active sites in real reactions, as well as the optimization mechanisms for performance enhancement. The objective of this review is to promote a robust SAC design strategy that encapsulates bimetallic bonding active sites within sub-1-nm spaces and investigates catalyst preparation and performance under reaction-induced conditions. This design strategy is anticipated to bolster the catalytic activity and stability of the catalyst while also offering fresh perspectives and optimization avenues for the catalytic processes involved in practical chemical reactions.

Numerical simulation and structural optimization of forced convection oven

Temperature uniformity is a fundamental parameter for a forced convection oven to guarantee food baking quality. In this study, computational fluid dynamics (CFD) simulation is employed to analyze the air flow and heat transfer within a forced convection oven. Subsequent experimental measurements were conducted to explore the temperature variations inside the oven. The maximum deviation between the numerical simulation results and the experimental data was 2.70%, demonstrating the high accuracy of the simulation model. Based on the established simulation model, we can meticulously investigate the impact of fan structures on the airflow and temperature fields. Carefully designing the fan structure can significantly enhance temperature uniformity across the oven’s baking racks, reducing the standard deviation of temperatures on the second and third baking racks from 5.46°C and 6.69°C to 2.26°C and 2.46°C, respectively. This study provides a robust design strategy for forced convection ovens, yielding tangible benefits for practical application and market competitiveness.

Multiwavelength Achromatic Deflector in the Visible Using a Single-Layer Freeform Metasurface.

Deflectors are essential for modulating beam direction in optical systems but often face form factor issues or chromatic aberration with conventional optical elements, such as prisms, mirrors, and diffractive/holographic optical elements. Despite recent efforts to address such issues using metasurfaces, their practicality remains limited due to operation wavelengths in the near-infrared or the fabrication difficulties inherent in the multilayer scheme. Here, we propose a novel single-layer metasurface achieving multiwavelength chromatic aberration-free deflection across the visible spectrum by employing the robust freeform design strategy to simplify the fabrication process. By properly selecting diffraction orders for red, green, and blue wavelengths to achieve identical wavelength-diffraction-order products, the metasurface deflects light at a consistent angle of 41.3° with a high efficiency. The coupled Bloch mode analysis explains the physical properties, and experimental fabrication and characterization confirm its effectiveness. This approach holds potential for various applications such as AR/VR, digital cameras, and high-quality optical systems.

Optimizing the design of spatial genomic studies

Spatial genomic technologies characterize the relationship between the structural organization of cells and their cellular state. Despite the availability of various spatial transcriptomic and proteomic profiling platforms, these experiments remain costly and labor-intensive. Traditionally, tissue slicing for spatial sequencing involves parallel axis-aligned sections, often yielding redundant or correlated information. We propose structured batch experimental design, a method that improves the cost efficiency of spatial genomics experiments by profiling tissue slices that are maximally informative, while recognizing the destructive nature of the process. Applied to two spatial genomics studies—one to construct a spatially-resolved genomic atlas of a tissue and another to localize a region of interest in a tissue, such as a tumor—our approach collects more informative samples using fewer slices compared to traditional slicing strategies. This methodology offers a foundation for developing robust and cost-efficient design strategies, allowing spatial genomics studies to be deployed by smaller, resource-constrained labs.

Analysis Seismic Behavior of Structures with Planar Imperfections: A Comprehensive Numerical Analysis

This paper presents a comprehensive approach to the seismic analysis and design of a tall hospital building, accounting for horizontal irregularities and employing equivalent static analysis (ESA) methodology. The study initiates with the collection of relevant site data and building specifications, including the identification and characterization of horizontal irregularities such as setbacks, mass distribution variations, and irregular floor plans. Equivalent static lateral loads are calculated based on applicable building codes and standards, taking into account the effects of horizontal irregularities on seismic response. Structural modeling and analysis are then conducted using sophisticated software to evaluate the building's behavior under seismic forces, considering the influence of irregularities on structural performance. Design criteria, encompassing drift limits, strength requirements, and detailing considerations for mitigating irregularity effects, are rigorously adhered to ensure compliance with safety regulations and performance objectives. The iterative process of evaluation and adjustment ensures optimal seismic performance and adherence to design criteria despite the presence of horizontal irregularities. Documentation of the analysis and design process, coupled with meticulous construction oversight, guarantees the implementation of a robust seismic design strategy tailored to the unique characteristics of the tall hospital building. Post-construction evaluations are carried out to validate predicted seismic performance, accounting for the influence of horizontal irregularities. Through collaborative efforts and adherence to best practices, the seismic design of the tall hospital building prioritizes safety and resilience, even in the face of horizontal irregularities, aiming to safeguard occupants and critical healthcare infrastructure during seismic events.

Strategies to Diversification of the Mechanical Properties of Organic Crystals

AbstractStructurally ordered soft materials that respond to complementary stimuli are susceptible to control over their spatial and temporal morphostructural configurations by intersectional or combined effects such as gating, feedback, shape‐memory, or programming. In the absence of general and robust design and prediction strategies for their mechanical properties, at present, combined chemical and crystal engineering approaches could provide useful guidelines to identify effectors that determine both the magnitude and time of their response. Here, we capitalize on the purported ability of soft intermolecular interactions to instigate mechanical compliance by using halogenation to elicit both mechanical and photochemical activity of organic crystals. Starting from (E)‐1,4‐diphenylbut‐2‐ene‐1,4‐dione, whose crystals are brittle and photoinert, we use double and quadruple halogenation to introduce halogen‐bonded planes that become interfaces for molecular gliding, rendering the material mechanically and photochemically plastic. Fluorination diversifies the mechanical effects further, and crystals of the tetrafluoro derivative are not only elastic but also motile, displaying the rare photosalient effect.

Strategies to Diversification of the Mechanical Properties of Organic Crystals.

Structurally ordered soft materials that respond to complementary stimuli are susceptible to control over their spatial and temporal morphostructural configurations by intersectional or combined effects such as gating, feedback, shape-memory, or programming. In the absence of general and robust design and prediction strategies for their mechanical properties, at present, combined chemical and crystal engineering approaches could provide useful guidelines to identify effectors that determine both the magnitude and time of their response. Here, we capitalize on the purported ability of soft intermolecular interactions to instigate mechanical compliance by using halogenation to elicit both mechanical and photochemical activity of organic crystals. Starting from (E)-1,4-diphenylbut-2-ene-1,4-dione, whose crystals are brittle and photoinert, we use double and quadruple halogenation to introduce halogen-bonded planes that become interfaces for molecular gliding, rendering the material mechanically and photochemically plastic. Fluorination diversifies the mechanical effects further, and crystals of the tetrafluoro derivative are not only elastic but also motile, displaying the rare photosalient effect.

Dynamic increase factors for progressive collapse analysis of steel structures considering column buckling

Progressive or disproportionate collapse of structures may have severe socio-economic consequences. Aiming at buildings that can withstand such events, one solution is to prevent or minimize the propagation of damage that may lead to progressive collapse by means of robust design strategies. As a typical approach to model progressive collapse and assess robustness, the Alternate Path Method (APM) allows for static analyses, in which the dynamic effects induced by a sudden column loss are taken into account by amplifying loads through a Dynamic Increase Factor. Current recommendations for Dynamic Increase Factors to be used within non-linear static analyses have mainly considered beam-type collapse, overlooking other failure mechanisms, e.g., column buckling. The present paper investigates the dynamic effects of steel structures subjected to progressive collapse when buckling of columns is relevant. Five low- to high-rise case study building structures are considered together with three different column loss scenarios. A numerical procedure is introduced to evaluate the Dynamic Increase Factors considering two different Engineering Demand Parameters (EDPs), suited for describing beam- and column-type mechanisms, respectively. As Dynamic Increase Factors are typically assessed by increasing the loads on all the spans (DIF), a procedure was proposed for deriving factors that apply only on the spans above the removal (DIF*), consistently with UFC guidelines. The obtained DIF and DIF* are compared with the current literature and with values recommended in the UFC guidelines, highlighting the limits of current recommendations. Relevant considerations on the derived Dynamic Increase Factors and failure mechanisms involved are provided.

A Least-Square Unified Framework for Spatial Filtering in SSVEP-Based BCIs.

The steady-state visual evoked potential (SSVEP) has become one of the most prominent BCI paradigms with high information transfer rate, and has been widely applied in rehabilitation and assistive applications. This paper proposes a least-square (LS) unified framework to summarize the correlation analysis (CA)-based SSVEP spatial filtering methods from a machine learning perspective. Within this framework, the commonalities and differences between various spatial filtering methods appear apparent, the interpretation of computational factors becomes intuitive, and spatial filters can be determined by solving a generalized optimization problem with non-linear and regularization items. Moreover, the proposed LS framework provides the foundation of utilizing the knowledge behind these spatial filtering methods in further classification/regression model designs. Through a comparative analysis of existing representative spatial filtering methods, recommendations are made for the superior and robust design strategies. These recommended strategies are further integrated to fill the research gaps and demonstrate the ability of the proposed LS framework to promote algorithmic improvements, resulting in five new spatial filtering methods. This study could offer significant insights in understanding the relationships between various design strategies in the spatial filtering methods from the machine learning perspective, and would also contribute to the development of the SSVEP recognition methods with high performance.

Consensus docking aid to model the activity of an inhibitor of DNA methyltransferase 1 inspired by de novo design

The structure-activity relationships data available in public databases of inhibitors of DNA methyltransferases (DNMTs), families of epigenetic targets, plus the structural information of DNMT1, enables the development of a robust structure-based drug design strategy to study, at the molecular level, the activity of DNMTs inhibitors. In this study, we discuss a consensus molecular docking strategy to aid in explaining the activity of small molecules tested as inhibitors of DNMT1. The consensus docking approach, which was based on three validated docking algorithms of different designs, had an overall good agreement with the experimental enzymatic inhibition assays reported in the literature. The docking protocol was used to explain, at the molecular level, the activity profile of a novel DNMT1 inhibitor with a distinct chemical scaffold whose identification was inspired by de novo design and complemented with similarity searching.

Complex uncertainty-oriented robust topology optimization for multiple mechanical metamaterials based on double-layer mesh

With the continuous improvement of structural performance requirements of advanced equipment, the multiscale design of materials and structures is increasingly developing towards refinement and multi-function. Metamaterials have broad application prospects due to their superior mechanical properties. In this paper, a robust topology optimization design strategy for mechanical metamaterials with multiple properties including modulus and Poisson's ratio is proposed. This method considers the manufacturing size uncertainty on properties of metamaterials and adopts a double-layer mesh technology to improve the efficiency of topology optimization. In addition, a topology optimization model for metamaterials with different mechanical properties is established, and mechanical metamaterials with various properties and configurations have been designed and validated. These can provide technical support and design references for the engineering application of mechanical metamaterials.

Robust design strategy using a scaffold based Turing machine model--- Application to PDI based dyes

This study turns the design and screen of new compounds into a computer integer crunch of the control arrays using a scaffold based Turing machine model. If small organic fragments are stored in a fragment database (FDB) in which each fragment is labelled by an integer in an array, the position and frequency of the integer control how the fragment clicks on a scaffold (template compound). This method can robustly screen a large number of candidate fragments for solar cells and other applications such as drug design with minimal human assistance. As a proof of concept, we consider terminal imide substituents on the core perylene diimide (PDI) to develop PDI derivatives capable of absorbing UV–vis light for solar cell applications. Time dependent-density functional theory (TD-DFT) method was employed in the calculations. When the imide substituents are electron donors such as azobenzene (DPI-7), they produce a larger bathochromic shift (Δλmax) from the core DPI band position. The UV–vis absorption transitions of these DPI derivatives have more charge transfer (CT) character, as the highest occupied molecular orbitals (HOMO) are located on the fragments rather than the core DPI region. Our study presents a robust and efficient high-performance organic dye screen design strategy, and further research in DPI-based solar cell design will focus on promoting the HOMO to LUMO transitions of the optical spectra.

Mesostructures Engineering to Promote Selective Nitrate‐to‐Ammonia Electroreduction

AbstractThe electroreduction of nitrate into green ammonia (NO3−‐to‐NH3) in aqueous solution represents a sustainable route applicable to green NH3 electrosynthesis and nitrogen balance. However, the NO3−‐to‐NH3 electroreduction undergoes a complex eight electron (8e−) transfer pathway and results in unsatisfying activity and selectivity. Here, mesostructures engineering is presented as a new and robust design strategy for producing high‐performance multimetallic electrocatalysts that remarkably promote selective NO3−‐to‐NH3 electroreduction. 1D PdCuAg mesoporous nanotubes (MTs) are facilely prepared by a one‐step galvanic replacement‐assisted surfactant‐templating method in an aqueous solution. The electrocatalyst shows remarkable NO3−‐to‐NH3 performance with high NH3 Faradaic efficiency (FENH3) of 95.2%, superior NH3 yield rate of 17.7 mg h−1 mg−1, impressive NH3 energy efficiency of 29.8%, and outstanding stability (50 cycles), all of which are much better than the performance of counterpart electrocatalysts. The promotion of NO3−‐to‐NH3 performance comes from the electron‐rich surface and nanoconfinement microenvironment of mesostructured synergies that enrich nanozyme‐like chemisorption of key intermediates and thus facilitates electroreduction of NO3− into NH3 through an 8e− reaction pathway. Meanwhile,1D PdCuAg MTs are practically explored in a Zn‐NO3− battery, delivering a superior NH3 yield rate of 25.85 µmol h−1 cm−2 and a high FENH3 of 92.4%.

A robust design strategy for active control of scattered sound based on virtual sensing.

Combining virtual sensing (VS) with scattered sound control enables active acoustic cloaking when there are limitations in sensor configurations. The remote microphone method and additional filter method (AFM) are two common VS methods, and both can be divided into the training and control stages; the consistency of the environments in these two stages is essential for the control system. This paper investigates the effects of uncertainties in the incidence angle of the detection wave on these two VS-based scattered sound control methods. Following the analysis, we propose a robust design strategy based on the optimal layout of physical sensors, and the placement scheme is chosen by minimax optimization. The feasibility of the proposed strategy is verified by numerical simulations of a finite-length cylindrical scattering model. The results demonstrate that the proposed strategy can effectively reduce the degradation of system performance over the examined range of variations in the detection waves. In particular, the AFM-based method, combined with optimal placement, shows a remarkable improvement in robustness. It improves the worst noise reduction by approximately 14.5 and 10.8 dB on average, respectively, compared with the uniform placement and the direct control method based on the Wiener solution.

Robust alarm design strategy for medical devices: Application to air-in-line detection and occlusion management

Alarm fatigue in the hospital environment is a recurring problem that can be solved through technical, human, or organizational considerations. The use of technical factors to get a robust alarm management system is illustrated here by two case studies related to air-in-line detection in peritoneal dialysis and insulin pump occlusion management. Air-in-line sensors are usually very sensitive to the presence of small bubbles stuck on tubing and may therefore deliver false alarms. To provide a reliable estimate of the cumulated air volume pumped an IR sensor technology that is insensitive to small bubbles was implemented and tested. Another strategy was used to limit false occlusion alarms in an insulin patch pump. The piezoelectric actuator of this micropump was servo-controlled to the pressure sensor signal to allow insulin to flow into the patient despite the presence of a partial occlusion. The false alarm rate is thus reduced by using a self-adaptive occlusion detection threshold that has been evaluated using numerical simulations.

Full-Duplex MIMO Relay-Assisted Interference Alignment Algorithm in K-user Interference Channels

In this paper, we investigate the transceiver design schemes for the full-duplex multiple-input multiple-output relay-assisted K-user single-input multiple-output interference channels. Firstly, we propose an iterative optimized reference vector for IA (IORV-IA) algorithm in the perfect channel state information (CSI) scenario. The proposed IORV-IA algorithm not only achieves the alignment of interference signals at each receiver, but also iteratively optimizes the IA reference vector by orthogonalizing the directions of the interference signals and the desired signal. With the optimized IA reference vector, the relay processing matrix and the receiving filter vectors are designed to further improve the system performance. Considering that the relay cannot obtain perfect CSIs in practice due to many factors, and the performance of the IA scheme is very sensitive to this error. Furthermore, we propose a robust transceiver design scheme based on mean square error (MSE) in the imperfect CSI scenario, which minimizes the sum of MSEs in the worst case through iteration. The proposed algorithms are evaluated in terms of the average sum rate and bit error rate performance and the simulation results show the advantages of the proposed algorithms over existing centralized IA and centralized zero-forcing algorithms.

Robust Transceiver Optimization Against Echo Eclipsing via Majorization-Minimization

The actual target range is unknown during the radar search process, which suggests that an elaborate transceiver synthesis should be concerned, also considering various number of missed target echo samples. This paper focuses on the joint robust synthesis of the radar code and filter bank to improve target detection capability against target echo eclipsing and clutter interference. For several practical considerations, two robust design strategies for transceiver optimization are considered. A majorization-minimization (MM) approach (Section III) is developed to deal with the average signal to interference plus noise ratio (SINR) design problem considering energy and similarity requirements on the waveforms. Then, the MM technique is extended to the max-min case. An accelerated MM-based procedure (Section IV) is presented for solving the worst-case SINR design problem under energy and peak-to-average ratio (PAR) requirements. Both the proposed algorithms can be ensured to converge to a B(oulingand)-stationary point. Finally, simulation results display that two proposed optimization strategies realize better target detection performance and a higher convergence rate compared with the existing approaches.

In situ visualization of apoptosis process and modulation of cancer cell ablation based on a monocomponent multi-functional smart nanozyme

Nanozymes have exhibited an excellent prospect in cancer ablation. However, the real-time sensing of anticancer efficacy in catalytic process is often neglected. Designing the smart nanozymes for in situ visualizing treatment efficacy at subcellular level during catalytic therapy is crucial for precise cancer treatment, but hampered owing to the lack of a robust design strategy and efficient synthesis method. Herein, a monocomponent multi-functional photo-responsive carbon dots-based (CDs) nanozyme for instant self-predicting therapy efficacy and synchronous cancer cell ablation is developed through a direct microwave-assisted method. The CDs nanozyme can significantly induce cancer cell ablation due to its unique dual enzyme-mimic activities (oxidase-mimic and peroxidase-mimic), mitochondria-targeting ability, light-response feature improved synergistic therapy and high spatiotemporal selection. More importantly, the excessive reactive oxygen species (ROS) generated from catalytic treatment induces mitochondrial oxidative stress, accompanied by decreased mitochondrial membrane potential (MMP), which results in the transfer of CDs nanozyme from the mitochondrion to the nucleolus and thus enables the in situ real-time detection of therapy efficiency via fluorescent signal migration. This work not only represents an emerging paradigm with the self-predicting function for precise cancer treatment but also inspires the future design of the new generation of nanozyme.

Robust nonlinear elastic metamaterial enabled by collision damping

ABSTRACT Nonlinear elastic metamaterials are attracting increasing attention owing their unusual properties of wave manipulation. However, the robustness of these benefits under varying amplitude should be increased and the challenge lies in the design. Here, we demonstrate a robust design strategy of nonlinear metamaterial via combining collision and damping. The damping will not interfere but enhance the nonlinear effects for broadband vibration reduction. The design presents low-frequency, broadband, efficient vibration reduction under varying amplitude. The effect can be activated by a small input amplitude. The performance remains high in a large amplitude range, i.e., high robustness is achieved. This property is systematically demonstrated with simulations and experiments on a nonlinear metamaterial beam. This article can offer an effective method to realize robust vibration suppression.

Toward Balancing Dynamic Performance and System Stability for DC Microgrids: A New Decentralized Adaptive Control Strategy

In the primary control layer of DC microgrids, engineers usually select the control gains with a robust design strategy (i.e., the worst case study), aiming to ensure stable operation of the system with the presence of large-signal disturbances. However it will inevitably result in degraded nominal control performance. To this end, a compromise between dynamic performance and system stability appears and how to reconcile it is a challenging task. In this context, we propose a novel adaptive control strategy aiming to pursue a balance between the above two properties. Firstly, a higher-order sliding mode observation technique is employed to estimate the disturbance variations within a finite time. Secondly, an adaptive gain regulation mechanism is designed in an easy-implementable fashion. Finally, by combing the feedforward decoupling procedure and the adaptive feedback scheme, the control performance of the DC microgrids can be adjusted adaptively in different working conditions. Through the above design produces, the proposed controller will bring the following new features: 1) The robustness redundancy of existing robust control strategies can be essentially avoided. 2) The balance between dynamic performance and system stability is achieved. 3) The self-tuning regulation facilitates the process of gain selection and the concise adaptive structure can be easily utilized in practical implementation. The efficacy of the proposed controller is verified by both simulation and experiment results.