Design Paradigm Research Articles

Reimagining public water: an intergenerational exploration of paradigms for future system design

ABSTRACT Due to the life-span of infrastructure, the complexity of components and the tendency of institutional structures to reproduce themselves, infrastructural systems as a whole are seldom reimagined. In addition, strategic thinking about possible system innovations is mainly done by the generations with extensive work experience. This whilst challenges such as climate change trigger the need for system innovation and are inherently intergenerational. This paper examines a method for “intergenerational reimagination”, facilitating reflexive learning within a generationally diverse subgroup of actors. This was done to explore paradigms for future system design. Building on the Advocacy Coalition Framework, descriptive, normative and explorative steps are developed. These steps include an intergenerational dialogue and carefully designed workshops, involving both young and senior professionals. The methodology was applied to reimagine the Dutch public water system, a design process which involved over 50 young professionals and resulted in three reimaginations. This process shows the potential for intergenerational development of possible paradigms for future system design. Moreover, throughout the process, policy-oriented learning was given substance. Finally, the study provided young professionals with a means to join strategic thinking at the semi-public level of water companies; a potential source of inspiration for other sectors and issues.

Diffusion-based generative drug-like molecular editing with chemical natural language

Recently, diffusion models have emerged as a promising paradigm for molecular design and optimization. However, most diffusion-based molecular generative models focus on modeling 2D graphs or 3D geometries, with limited research on molecular sequence diffusion models. The International Union of Pure and Applied Chemistry (IUPAC) names are more akin to chemical natural language than the Simplified Molecular Input Line Entry System (SMILES) for organic compounds. In this work, we apply an IUPAC-guided conditional diffusion model to facilitate molecular editing from chemical natural language to chemical language (SMILES) and explore whether the pre-trained generative performance of diffusion models can be transferred to chemical natural language. We propose DiffIUPAC, a controllable molecular editing diffusion model that converts IUPAC names to SMILES strings. Evaluation results demonstrate that our model outperforms existing methods and successfully captures the semantic rules of both chemical languages. Chemical space and scaffold analysis show that the model can generate similar compounds with diverse scaffolds within the specified constraints. Additionally, to illustrate the model's applicability in drug design, we conducted case studies in functional group editing, analogue design and linker design.

Rational design of Z-scheme configured polymeric carbon nitride-decorated ZnWO4 nanofibers for enhanced visible-light-driven photodegradation of antibiotics

In this study, a Z-scheme heterostructure was meticulously engineered between zinc tungstate (ZnWO4) nanofibers and polymeric carbon nitride (PCN) nanosheets to augment the photocatalytic degradation of tetracycline (TC) under visible light irradiation. A cohesively integrated PCN/ZnWO4 photocatalyst structure was synthesized through an in-situ gas-solid reaction. The quantity and spatial distribution of PCN nanosheets were modulated by fine-tuning the gas precursor and reaction parameters. Relative to pristine ZnWO4 nanofibers and PCN photocatalysts, the distinct three-dimensional PCN/ZnWO4 heterostructure manifests a notable enhancement in photocatalytic performance, attributed to its plethora of active sites and a Z-scheme configuration that bolsters charge separation efficiency, achieving a tetracycline degradation rate of 95.4% upon exposure to simulated sunlight for 160 minutes. The employment of gas-solid reaction as a design paradigm pioneers a fresh paradigm in the strategic assembly of Z-scheme heterostructured photocatalysts, thereby illuminating a promising pathway for advancements in environmental remediation technologies.

Construction of Smart Clothing Service System for the Health and Well-Being of the Aging Community in a Sustainable Society

Objective: The phenomenon of global aging is becoming more and more severe, and security services such as nursing and guardianship for the elderly have become the focus of social attention. According to the data released by the World Health Organization, by 2030, one out of every six people will be over 60 years old. By 2050, the world population will be 2.1 billion over 60 years old, and the number of people over 80 years old will reach 460 million. This paper aims to monitor the health and services of aging clothing intelligently for the health and well-being of the aging community in a sustainable society, starting from the physiological and psychological needs of the new elderly. Theoretical Framework: In the age-appropriate smart clothing service system, the critical link is to construct the human-computer interaction mode of clothing and wearable devices, establish a design paradigm from single interaction to multi-interaction, and form a service terminal based on smart wearable. Method: This paper designs an aging smart clothing design system using field research, questionnaires, interviews, etc., analyzes the aging smart wearable clothing evaluation system, and constructs aging smart clothing that meets the actual needs of health and well-being for the elderly in a sustainable society. Results and Discussion: In this research, The results obtained sustainable design theories and methods combined with interdisciplinary research tools as the basis of data analysis from the aging intelligent clothing product design system, age-appropriate smart clothing service system, and age-appropriate smart clothing evaluation system. Research Implications: Population aging has been the basic national condition of our country for quite a long time in the future, and "healthy aging" is a strategic measure put forward by the government around the intelligent care service system for the elderly, communities, and institutions. Important direction. Among them, how to build an age-appropriate smart wearable product service system has become the main development content. Therefore, its intelligence and synergistic combination with terminals such as communities, caregivers, and hospitals will become the trend of smart elderly care. Originality/Value: This study contributes to Construct a systematic design of a new intelligent wearable clothing service system for the elderly, which is a great of significance for improving the service quality index of the health and well-being of the elderly. At the same time, it is of great value to expand and deepen the concept of sustainable design.

Innovative Anode Design to Enhance Both Volumetric and Gravimetric Energy Densities of LiCoO2||Graphite Pouch Cells

AbstractThe ratio of the anode (negative electrode) and cathode (positive electrode) areal capacities (N/P ratio), is an important parameter for Lithium‐ion batteries. Considering the manufacturing tolerance and battery safety, almost all of the batteries keep the N/P ratio > 1. Deviating from this ratio can lead to lithium precipitation on the anode surface, which poses significant risks. Here, by using a gradient structured graphite (Gr) anode, a new design concept is proposed that the N/P ratio could be less than 1, which can effectively achieve higher energy density without sacrificing the battery safety. This is achieved by incorporating a small quantity of silver (Ag) nanoparticles into the bottom layer of the anode (Gr‐Agx), which effectively modulates the concentration polarization of lithium ions along the thickness of the electrode. Moreover, the volumetric energy density of 4 Ah LiCoO2||Gr‐Ag0.5 (N/P = 0.8) pouch cell increases by 14.5% compared with LiCoO2||Gr (N/P = 1.1). Furthermore, the universal applicability and efficacy of the N/P < 1 design paradigm in LiFePO4||Gr cells are validated.

Ambient Moisture-Induced Self Alignment of Polarization in Ferroelectric Hafnia.

The discovery of nanoscale ferroelectricity in hafnia (HfO2) has paved the way for next generation high-density, non-volatile devices. Although the surface conditions of nanoscale HfO2 present one of the fundamental mechanism origins, the impact of external environment on HfO2 ferroelectricity remains unknown. In this study, the deleterious effect of ambient moisture is examined on the stability of ferroelectricity using Hf0.5Zr0.5O2 (HZO) films as a model system. It is found that the development of an intrinsic electric field due to the adsorption of atmospheric water molecules onto the film's surface significantly impairs the properties of domain retention and polarization stability. Nonetheless, vacuum heating efficiently counteracts the adverse effects of water adsorption, which restores the symmetric electrical characteristics and polarization stability. This work furnishes a novel perspective on previous extensive studies, demonstrating significant impact of surface water on HfO2-based ferroelectrics, and establishes the design paradigm for the future evolution of HfO2-based multifunctional electronic devices.

The Geometric Scale of an Urban Space—Neuro-perceptual Limitations for Face-to-Face Driver Behavior

For the last century, the roadway design paradigm has been grounded in the physics of point masses, adjusted for human limitations. However, this is inadequate to assure pedestrian safety in complete streets where vehicle kinematics no longer control. Instead, social and psychological factors manage behavior. Unfortunately, the appropriate design critical psychological principles have yet to be elucidated. We posit that interpersonal perception governs drivers’ behavior, attentiveness and speed in streets. This is bounded by previously delineated human neurological and perceptual propensities. Using these perceptual limitations as postulates in a geometric style proof, we derive the person perception panorama (PPP): a window of interactivity around the moving driver that is continuously monitored for human presence, roughly 60 to 90 feet wide. In this area interpersonal interaction is implicit, functional, and has an impact on driver behavior. Validating evidence, additional governing principles, and an initial speed prediction formula are also included.

Application of quantum graph theory to metamaterial design: Negative refraction of acoustic waveguide modes

We leverage quantum graph theory to quickly and accurately characterize acoustic metamaterials comprising networks of interconnected pipes. Anisotropic bond lengths are incorporated in the model that correspond to space-coiled acoustic structures to exhibit dispersion spectra reminiscent of hyperbolic metamaterials. We construct two metasurfaces with embedded graph structure and, motivated by the graph theory, infer and fine-tune their dispersive properties to engineer nonresonant negative refraction of acoustic surface waves at their interface. Agreement between the graph model, full-wave simulations, and experiments bolsters quantum graph theory as a new paradigm for metamaterial design. Published by the American Physical Society 2024

Nature redux: interrogating biomorphism and soft robot aesthetics through generative AI

Artificial Intelligence (AI) has rapidly become a widespread design aid through the recent proliferation of generative AI tools. In this work we use generative AI to explore soft robotics designs, specifically Soft Biomorphism, an aesthetic design paradigm emphasizing the inherent biomorphic qualities of soft robots to leverage them as affordances for interactions with humans. The work comprises two experiments aimed at uncovering how generative AI can articulate and expand the design space of soft biomorphic robotics using text-to-image (TTI) and image-to-image (ITI) generation techniques. Through TTI generation, Experiment 1 uncovered alternative interpretations of soft biomorphism, emphasizing the novel incorporation of, e.g., fur, which adds a new dimension to the material aesthetics of soft robotics. In Experiment 2, TTI and ITI generation were combined and a category of hybrid techno-organic robot designs discovered, which combined rigid and pliable materials. The work thus demonstrates in practice the specific ways in which AI image generation can contribute towards expanding the design space of soft robotics.

Strikingly Facile Cleavage of N-H/N-O Bonds Induced by Surface Frustrated Lewis Pair on CeO2(110) to Boost NO Reduction by NH3.

Ceria with surface solid frustrated Lewis pairs (FLPs), formed by regulating oxygen vacancies, demonstrate remarkable ability in activating small molecules. In this work, we extended the application of FLPs on CeO2(110) to the selective catalytic reduction of NO by NH3 (NH3-SCR), finding a notable enhancement in performance compared to ordinary CeO2(110). Additionally, an innovative approach involving H2 treatment was discovered to increase the number of FLPs, thereby further boosting the NH3-SCR efficiency. Typically, NH3-SCR on regular CeO2 follows the Eley-Rideal (E-R) mechanism. However, density functional theory (DFT) calculations revealed a significant reduction in the energy barriers for the activation of N-O and N-H bonds under the Langmuir-Hinshelwood (L-H) mechanism with FLPs present. This transition shifted the reaction mechanism from the E-R pathway on regular R-CeO2 to the L-H pathway on FLP-rich FR-CeO2, as corroborated by the experimental findings. The practical application of FLPs was realized by loading MoO3 onto FLP-rich FR-CeO2, leveraging the synergistic effects of acidic sites and FLPs. This study provides profound insights into how FLPs facilitate N-H/N-O bond activation in small molecules, such as NH3 and NO, offering a new paradigm for catalyst design based on catalytic mechanism research.

Stability‐Enhanced Variable Stiffness Metamaterial with Controllable Force‐Transferring Path

AbstractSelf‐contact variable stiffness (SVS) metamaterial offers specific patterns of elastic strain energy storage by changing its force‐transferring path. The change of the elastic strain energy storage patterns further influences the stiffness variation of the SVS metamaterials. However, challenges still arise because typically fabricated SVS metamaterials inevitably contain structural irregularities, eccentricities, and defects. These microstructural imperfections impede the stable generation of designed strain energy storage patterns in the metamaterial, implying that the SVS metamaterials cannot achieve expected stiffness variations. To address this burning question, an SVS metamaterial/meta‐structure design paradigm with eccentric unit designs is proposed, which can realize both stable stiffness variations and high load‐bearing. The theoretical, simulation, and experimental results demonstrate that the SVS chain meta‐structure achieves ≈110 times stiffness variation between the low and high loading conditions. Its load‐bearing can reach more than 1500 N when the meta‐structure falls into the high stiffness stage. Furthermore, some typical functions are demonstrated using the stability‐enhanced SVS metamaterial, including customized mechanical protections for human joints and information transformation regulated by remote mechanical input signals. The results can provide a useful solution for generating a more feasible stability‐enhanced SVS metamaterial/meta‐structure and promote their potential applications in aerospace, medical devices, and robotics.

Fluorine-Doped Carbon Support Enables Superfast Oxygen Reduction Kinetics by Breaking the Scaling Relationship.

It is well-established that Pt-based catalysts suffer from the unfavorable linear scaling relationship (LSR) between *OOH and *OH (ΔG(*OOH)=ΔG(*OH)+3.2±0.2 eV) for the oxygen reduction reaction (ORR), resulting in a great challenge to significantly reduced ORR overpotentials. Herein, we propose a universal and feasible strategy of fluorine-doped carbon supports, which optimize interfacial microenvironment of Pt-based catalysts and thus significantly enhance their reactive kinetics. The introduction of C-F bonds not only weakens the *OH binding energy, but also stabilizes the *OOH intermediate, resulting in a break of LSR. Furthermore, fluorine-doped carbon constructs a local super-hydrophobic interface that facilitates the diffusion of H2O and the mass transfer of O2. Electrochemical tests show that the F-doped carbon-supported Pt catalysts exhibit over 2-fold higher mass activities than those without F modification. More importantly, those catalysts also demonstrate excellent stability in both rotating disk electrode (RDE) and membrane electrode assembly (MEA) tests. This study not only validates the feasibility of tuning the electrocatalytic microenvironment to improve mass transport and to break the scaling relationship, but also provides a universal catalyst design paradigm for other gas-involving electrocatalytic reactions.

Fluorine‐Doped Carbon Support Enables Superfast Oxygen Reduction Kinetics by Breaking the Scaling Relationship

AbstractIt is well‐established that Pt‐based catalysts suffer from the unfavorable linear scaling relationship (LSR) between *OOH and *OH (ΔG(*OOH)=ΔG(*OH)+3.2±0.2 eV) for the oxygen reduction reaction (ORR), resulting in a great challenge to significantly reduced ORR overpotentials. Herein, we propose a universal and feasible strategy of fluorine‐doped carbon supports, which optimize interfacial microenvironment of Pt‐based catalysts and thus significantly enhance their reactive kinetics. The introduction of C−F bonds not only weakens the *OH binding energy, but also stabilizes the *OOH intermediate, resulting in a break of LSR. Furthermore, fluorine‐doped carbon constructs a local super‐hydrophobic interface that facilitates the diffusion of H2O and the mass transfer of O2. Electrochemical tests show that the F‐doped carbon‐supported Pt catalysts exhibit over 2‐fold higher mass activities than those without F modification. More importantly, those catalysts also demonstrate excellent stability in both rotating disk electrode (RDE) and membrane electrode assembly (MEA) tests. This study not only validates the feasibility of tuning the electrocatalytic microenvironment to improve mass transport and to break the scaling relationship, but also provides a universal catalyst design paradigm for other gas‐involving electrocatalytic reactions.

Lightweight Detection of Broccoli Heads in Complex Field Environments Based on LBDC-YOLO

Robotically selective broccoli harvesting requires precise lightweight detection models to efficiently detect broccoli heads. Therefore, this study introduces a lightweight and high-precision detection model named LBDC-YOLO (Lightweight Broccoli Detection in Complex Environment—You Look Only Once), based on the improved YOLOv8 (You Look Only Once, Version 8). The model incorporates the Slim-neck design paradigm based on GSConv to reduce computational complexity. Furthermore, Triplet Attention is integrated into the backbone network to capture cross-dimensional interactions between spatial and channel dimensions, enhancing the model’s feature extraction capability under multiple interfering factors. The original neck network structure is replaced with a BiFPN (Bidirectional Feature Pyramid Network), optimizing the cross-layer connection structure, and employing weighted fusion methods for better integration of multi-scale features. The model undergoes training and testing on a dataset constructed in real field conditions, featuring broccoli images under various influencing factors. Experimental results demonstrate that LBDC-YOLO achieves an average detection accuracy of 94.44% for broccoli. Compared to the original YOLOv8n, LBDC-YOLO achieves a 32.1% reduction in computational complexity, a 47.8% decrease in parameters, a 44.4% reduction in model size, and a 0.47 percentage point accuracy improvement. When compared to models such as YOLOv5n, YOLOv5s, and YOLOv7-tiny, LBDC-YOLO exhibits higher detection accuracy and lower computational complexity, presenting clear advantages for broccoli detection tasks in complex field environments. The results of this study provide an accurate and lightweight method for the detection of broccoli heads in complex field environments. This work aims to inspire further research in precision agriculture and to advance knowledge in model-assisted agricultural practices.

Targeting circadian transcriptional programs through a cis-regulatory mechanism in triple negative breast cancer.

Circadian clock genes are emerging targets in many types of cancer, but their mechanistic contributions to tumor progression are still largely unknown. This makes it challenging to stratify patient populations and develop corresponding treatments. In this work, we show that in breast cancer, the disrupted expression of circadian genes has the potential to serve as biomarkers. We also show that the master circadian transcription factors (TFs) BMAL1 and CLOCK are required for the proliferation of metastatic mesenchymal stem-like (mMSL) triple-negative breast cancer (TNBC) cells. Using currently available small molecule modulators, we found that a stabilizer of cryptochrome 2 (CRY2), the direct repressor of BMAL1 and CLOCK transcriptional activity, synergizes with inhibitors of proteasome, which is required for BMAL1 and CLOCK function, to repress a transcriptional program comprising circadian cycling genes in mMSL TNBC cells. Omics analyses on drug-treated cells implied that this repression of transcription is mediated by the transcription factor binding sites (TFBSs) features in the cis-regulatory elements (CRE) of clock-controlled genes. Through a massive parallel reporter assay, we defined a set of CRE features that are potentially repressed by the specific drug combination. The identification of cis -element enrichment might serve as a new concept of defining and targeting tumor types through the modulation of cis -regulatory programs, and ultimately provide a new paradigm of therapy design for cancer types with unclear drivers like TNBC.

Designing Contact Independent High-Performance Low-Cost Flexible Electronics.

Organic semiconductors enable low-cost solution processing of optoelectronic devices on flexible substrates. Their use in contemporary applications, however, is sparse due to persistent challenges in achieving the requisite performance levels in a reliable and reproducible manner. A critical bottleneck is the inefficiency associated with charge injection. Here, large-scale simulations are employed to identify operational windows where key device parameters that are difficult to control experimentally, such as the contact resistance, become less consequential to overall device functionality. This design methodology overcomes injection barrier limitations in organic field-effect transistors (OFETs), leading to high charge carrier mobility and significantly expanding the range of suitable electrode materials. Leveraging this new understanding, all-organic, solution-deposited OFETs are successfully fabricated on flexible substrates. These devices incorporate printed contacts and showcase mobilities exceeding 5cm2Vs-1. These results provide a route for accessing the fundamental limits of material properties even in the absence of ideal contacts - a critical step in establishing reliable structure/property relationships and optimal material design paradigms. While reducing the injection barrier and contact resistance remains critical for achieving high OFET performance, this work demonstrates a path toward consistently achieving high charge carrier mobility through device geometry design, ultimately reducing processing complexity and cost.

Placement Flow Study and Detailed Placement for Hybrid-Row-Height Designs

At the 3 nm node, a hybrid-row-height design paradigm has emerged for better power efficiency and performance optimization. A diverse cell library that includes multiple variants of a cell with different fin counts is available. Instead of using cells with the same fin count for the entire chip, a design may combine cells with two different fin counts. Cells with the same fin count can be laid down in the same row resulting in a chip with hybrid row heights. With this brand-new design paradigm, revisiting and revamping the conventional VLSI placement flow becomes necessary. There were attempts that addressed the placement problem associated with hybrid-row-height design at the global placement stage or the placement legalization stage. In this work, we first propose an effective detailed placement approach suitable for hybrid-row-height designs and then conduct a comprehensive study to evaluate the different options of forming a complete hybrid-row-height design placement flow. For the first time, the advantage of considering the row configuration early on in the global placement stage is confirmed. Besides, our proposed detailed placement approach can improve the final half-perimeter wirelength by over 7% on average which more than double the improvement obtainable by a basic detailed placement algorithm similar to the well-known FastDP.

A GAN-based stepwise full-field mechanical prediction model for architected metamaterials

The exploration of mechanical metamaterials, characterized by unique unit cells with significant macroscopic mechanical properties, is of crucial importance. Traditional methods relying on bioinspired structures lack broad design space and controllability to some extent, especially when practical requirements have no biological counterparts. Hence, there is a pressing need to advance methodologies for the expansive design of unit cells, catering to diverse practical demands. Inspired by architected material, a latent design paradigm gains prominence for its extensive possibilities and unique distribution. However, wide design space faces challenges in accurately assessing the deformation history and stress states of diverse units, requiring validation through experiments or simulations, and imposing efficiency constraints on design. Using patterns generated by a mimetic corrosion algorithm and computational simulations, a GAN-based machine learning surrogate model is constructed to predict the history of deformation and stress fields of architected unit cells with accuracy and efficiency, in which a stepwise mapping strategy is proposed to augment comprehension of mechanical information in image processing. In distinct cases covering both explored domains and several unexplored domains, the model achieves effective predictions, demonstrating the robustness and adaptability of the model in extrapolating predictions of both time domain and design space. The proposed method demonstrates efficacy, stability, and generalizability, pioneering a solution for the mechanical history prediction of architected metamaterials in a sparse data setting, thereby overcoming the limitations of the training set.

Paradigm shift in mechanical system design: toward automated and collaborative design with digital twin web

AbstractAnalyzing multi-vendor mechanical system designs requires a significant amount of manual work, resulting in a design paradigm where analysis is conducted only after the design is locked and components are selected. This leads to a suboptimal design with compatibility issues, over-dimensioned components, inferior performance, poor energy efficiency, and a lack of collaboration between OEMs (original equipment manufacturers) and system integrators. To overcome these issues, this paper proposes Co-Des (collaborative design) framework for automated and collaborative multi-vendor system design. The framework relies on standardized digital twin documents (DTD) of system designs, components, and analyses. The discoverability and distribution of these DTDs are enabled with digital twin web (DTW). Co-Des framework allows for finding suitable components for the design task by automatically running selected analyses employing component digital twins. In addition, OEMs can provide customized components for system integrators using the initial system design defined in the system design DTD. The use of the Co-Des framework was demonstrated with a windmill powertrain design use case, and the applicability of the automated assembly analysis for component selection was verified with performance measurements. The adoption of the proposed framework will lead to a paradigm shift from manual and siloed work relying on the exchange of PDFs to a more automated and collaborative design of mechanical systems. The adoption rate is defined by the willingness of system integrators to publish their initial system designs and OEMs their components as public digital twins.

The impact of quantum computing on the development of algorithms and software

Introduction: There is a great potential that the quantum computing can change the way of algorithms and software development more than classical computers. Thus, this article will try to focus on how algorithm design and software development can be affected by quantum computing as well as what possibilities could appear when quantum principles are implemented into traditional paradigms. This paper aims at identifying the impact of quantum computing on algorithm and software advancement, through a discussion of essential quantum algorithms, quantum languages, as well as the opportunities and challenges of quantum technologies. Method: An extensive literature review and theoretical investigation was also performed to investigate the foundational concepts of quantum computing and subsequent effects on algorithm and software engineering. Some of the research questions included exploring the contrast between classical and quantum algorithms, reviewing current literature on quantum programming languages, and delving into examples of real-life deployments of quantum algorithms cross numerous domains. Results: This paper shows that quantum computing brings qualitatively new paradigms in the algorithm design and function while the quantum algorithms such as Shor’s and Grover’s perform exponentially faster certain problems. Software development for quantum has brought the need to devise new frameworks of coding in light of probability in quantum circuit. It is also comforting to note that there is still effort being made although in its most embryonic form to create quantum programming languages like Qiskit and Cirq. Some of challenges include quantum decoherence; limited number of quantum hardware; and need for strong error correction processes.Conclusion: While there are currently relatively few quantum algorithms it is believed that the findings in this field have the ability to revolutionize algorithm and software design and subjects like cryptography, optimization and AI. However, trends in quantum computing show that the constraints to computational capabilities are likely to be lifted to allow creativity to develop the most powerful software solutions