Design Paradigm Research Articles

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

Digital Mechanical Metamaterial with Programmable Functionality.

Digitization has brought a new era to the world, liberating information from physical media. The material structure-property relation is high-dimensional and nonlinear, and the digitization of structure-property relations may bring unprecedented functional programmability and diversity. Here, a new concept of digital mechanical metamaterial (DMM) is presented, where property design is realized by programming the digital states of the DMM to decouple the design of the structure and property. Transforming the binary stable states of a curved beam to the digital bit, one unit cell of DMM manifests three distinct deformation responses under compression, i.e., compression-twist coupling (CTC), compression-shear coupling (CSC), and pure compression (PC). These deformation modes show notable differences in motion and stiffness, which, by digitally programming a series of DMM, can yield a spectrum of functionalities, including information encryption, stress-strain relation customization, energy absorption in cushioning, effective vibration isolation, and tunable force transmission. This study pioneers a versatile material design paradigm that provides much greater freedom for the property design of intelligent mechanical metamaterials.

Searching for thermal shutdown separators in lithium-ion batteries: Paradigm and practice

This paper focuses on the thermal shutdown separators for thermal runaway control in lithium-ion batteries (LIB). In electrical cars (EV), thermal runaway is the most catastrophic and life-threatening failure mode. Here we reexamined 17 reported phase-change-based thermal shutdown separators and suggested a new design paradigm for thermal shutdown separators of EV level batteries. Through accelerating rate calorimeter (ARC), we have obtained the thermal response curves of three typical EV level batteries: LFP 18,650 battery, NCM 18,650 battery and NCM pouch battery and summarized their critical temperatures. Taking NCM pouch battery as an example, we formed a searching zone for the 17 phase-change-based thermal shutdown separators and found that only 7 of them falling into the promising zone. After analysis on these 7 composite materials, we designed a new trial composite material PBS/PI, which turned out successful in all the following thermal and electrochemical tests. Moreover, we are aware from the beginning that all the reported materials are only tested in button batteries and may not as well apply to EV level batteries. Our own practice has also shown this discrepancy. Thereby we employed thermal simulation to help mapping the discrepancy between the button battery and pouch battery. The results shows that the thermal shutdown happens much earlier in the button battery when elevating the temperature, which tricks researchers into misjudging the material feasibility. This work offers avenues for the searching of thermal shutdown separators in EV level batteries.

A quality by design paradigm, novel, and fast LC-MS/MS method to quantify vortioxetine in rat brain homogenate and its assessment of greenness, whiteness, and blueness tools

Vortioxetine (VOR) is an antidepressant drug with multimodal mechanism of action. In this work a sensitive and simple bioanalytical LC-MS/MS method for analysis of VOR in spiked rat brain tissue was developed and validated. Chromatographic analyses were performed in isocratic mode, and Citalopram (CT) was found as a suitable internal standard. Supelco Ascentis® Express Phenyl-Hexyl column was used as stationary phase, and the mobile phase was 0.15 % formic acid in acetonitrile:water (55:45, v/v). A Box-Behnken Design − based method optimization was applied to explore the impact of analytical conditions on chromatographic separation of VOR and CT. Detection was realized via a triple quadrupole LC-MS/MS system; the mass transition ion-pair has been followed as m/z 299.05 → 149.90 for VOR, m/z 325.20 → 109.05 for CT. Analytical method validation was performed according to International Council for Harmonisation (ICH) guideline M10 on bioanalytical method validation. The calibration curve was within the range of 30 to 450 ng/mL. LOD and LLOQ were calculated at 10 and 30 ng/mL, respectively. Recovery was 90 % for the lower limit of quantification and between 98 % to 105 % for the other concentration levels. Total run time was 5 min, retention times of citalopram and vortioxetine were 2.4 and 3.1 min, respectively, and a good chromatographic separation was obtained under optimal conditions. The solvents used to make the method greener were evaluated with the Green Solvent Selection Tool and Green Index Spider chart. The AGREE score for the greenness of the developed method was calculated as 0.61 and was also evaluated with the ComplexGAPI pictogram. The BAGI score for blueness was calculated as 72.5, and the RGBfast score for whiteness was calculated as 50. The method was determined to be most green, white, and blue.

Flexible modular strategy for tailored, human–machine fusion wearable electronics

Over the past three decades, the field of wearable electronics has experienced significant growth, with future developments expected to lead to more seamless integration and a profound symbiosis between humans and electronic systems. However, current developments in wearable technology are constrained by traditional integrated circuit (IC) design paradigms and a limited range of form factors, predominantly manifesting as watches, glasses, and rings with fixed functionalities and performance capabilities. This study proposes a modular design method that leverages flexible electronics for tailoring wearable devices according to specific needs. This approach disperses and reinterprets the integrated device forms through the guidance of human body morphology and conformal design principles. The functional units within these wearable devices are constructed as physically isolated, flexible modules within a robust bus structure. These modules can be easily integrated using magnetic attachments and connectors, which allows for the creation of unconventional wearable devices with customised functionalities and forms. To validate this approach, a series of flexible functional modules were designed and prototyped. Demonstrations of some of these integrated wearable forms, including watches, headbands, and gloves, highlight the versatility of this approach. These devices can be rapidly assembled with selected flexible modules capable of monitoring vital signs, such as heart rate, peripheral capillary oxygen saturation (SpO2), barometric pressure, humidity, and temperature. The results suggest that the proposed modular method holds significant potential for advancing the development of future human–machine fusion wearable electronics.

Reconstruction of the surface Bi3+ oxide layer on Bi2O2CO3: Facilitating electron transfer for enhanced photocatalytic degradation performance of antibiotics in water

The advancement and meticulous design of functional photocatalysts exhibiting exceptional photocatalytic redox activity represent a pivotal approach to mitigating the dual challenges of environmental pollution and energy scarcity. In this study, we elucidate the construction of a Bi2O2CO3 catalytic system capable of inhibiting oxidative electron transfer through the attenuation of homogeneous Bi0 particle formation, achieved through the judicious modulation of solvent ratios. This innovative architecture possesses a distinctive active site and enhances interfacial Bi-O electron transfer pathways via exposure to oxidized Bi3+. Upon photoexcitation, the Bi2O2CO3 catalytic system undergoes structural distortions in its excited state that facilitate forbidden radiative relaxation, thereby fostering long-lived charge separation states. Remarkable catalytic activity was demonstrated in the remediation of pollutants, encompassing auto-oxidation and the catalytic degradation of superoxide radicals (•O2−) and holes (h+). Notably, the effective degradation of tetracycline hydrochloride (TCH) in aqueous media reached an impressive 86 % under simulated visible light irradiation, accompanied by a reaction rate constant 3.08 times superior to that of the 5-Bi/Bi2O2CO3 counterpart. Theoretical analyses revealed that the oxidized state of Bi2O2CO3 exhibits a crystal structure with significant electron trapping capability, undergoing pronounced apparent relaxation phenomena on its surface while demonstrating an enhanced adsorption affinity for H2O and O2. The potential degradation mechanisms were rigorously investigated through High-performance liquid chromatography (HPLC-MS), elucidating the photodegradation pathways and intermediates of TC. This work may serve as a distinct paradigm for the rational design of novel photocatalysts aimed at fostering sustainable environmental remediation and advancing energy innovation.

Exploiting reprogrammable nonlinear structural springs for enhancing the manoeuvrability of a vibro-impact capsule robot

Vibro-impact capsule robots, propelled by rhythmic collisions of an internal mass triggered by an external magnetic field, are emerging as promising tools for minimally invasive surgery. This innovative actuation mechanism allows for delicate interaction with tissues, making them ideal candidates for navigating confined surgical spaces. However, their limited manoeuvrability and controllability remain significant hurdles, restricting their ability to navigate complex anatomies and perform precise interventions, ultimately hindering their broader clinical applications. This paper investigates the integration of reprogrammable structural springs in capsule robots, demonstrating how dynamic tuning can tailor the interaction between the inner mass and the capsule, thereby unlocking enhanced manoeuvrability and precise control of the capsule robot. A mathematical model describing the dynamic response of a vibro-impact capsule robot integrated with von Mises trusses (VMT), which are used to tailor the interaction between the inner mass and the capsule, is developed and verified using finite element modelling. Using the verified mathematical model, we explore how the transition between mono-stability and bi-stability of VMTs affects the capsule robot’s propelling performance. Our findings demonstrate that this state switch enables four distinct propulsion modes of the capsule robot. This work paves the way for a new paradigm in small-scale robot design by incorporating reprogrammable nonlinear structures. These structures empower the robots with unprecedented manoeuvrability and controllability within a compact, deployable form factor.

Algorithm and Tool Development for Creative Generation of Graphic Design of Folk Houses and Ancient Buildings Integrating Cultural and Creative Elements

This study presents an innovative approach called CNN-GA for graphic design for folk houses and ancient buildings, which integrates Convolutional Neural Networks (CNN) with Genetic Algorithms (GA) to foster the creation of culturally rich and aesthetically appealing graphic designs in architecture. Our research focuses on capturing the essence of folk houses and ancient buildings, deeply rooted in cultural heritage, and reimagining them through a modern computational lens. The CNN component of our model is trained on a diverse array of architectural imagery, enabling it to effectively recognize and categorize key elements such as motifs, textures, and structural forms inherent to various architectural styles. This neural network acts as an intelligent extractor of cultural and aesthetic features, providing a nuanced understanding of traditional architectural elements. The extracted features are then input into a GA, which embarks on an evolutionary process of design generation. This process iteratively combines and refines the architectural elements, fostering a creative exploration of design possibilities that maintain cultural integrity while introducing innovative interpretations. The synergy of CNN and GA in our CNN-GA framework allows for an automated yet insightful design process, yielding graphic designs that are not only architecturally sound but also resonate with the rich cultural narratives of folk houses and ancient buildings. This research holds significant potential in revolutionizing architectural graphic design, offering a novel tool for architects and designers to merge traditional aesthetics with contemporary design paradigms.

The transformational dive of nanophotonics inverse design from deep learning to artificial general intelligence

The swift development of artificial intelligence (AI) is significantly transforming the paradigm of nanophotonics. Leveraging universal approximation abilities, AI models sidestep time-consuming electromagnetic simulations, opening the inverse design of photonics systems with millions of design features while offering ample stability and practical scalability compared to traditional optimization methods. This perspective discusses inverse design paradigms enabled by recent advances in AI models, discussing their roles, challenges, and opportunities envisioned by the approaching era of artificial general intelligence.

Priming of cancer-immunity cycle by alleviating hypoxia-induced ferroptosis resistance and immunosuppression

Stimulating a robust cancer-immunity cycle (CIC) holds promising potential for eliciting potent and enduring immune responses for cancer immunotherapy. However, designing a therapeutic nanomaterial capable of both enhancing tumor immunogenicity and mitigating immunosuppression is challenging and often associated with complicated design paradigms and immune-related adverse effects. Herein, a multienzyme-mimetic alloy nanosheet incorporating palladium (Pd) and iron (Fe) is developed, which can prime effective CIC by overcoming ferroptosis resistance for enhancing tumor immunogenicity and reprograming the tumor microenvironment for enhanced second near-infrared (NIR-II) photoimmunotherapy. The nanosheets accumulate in tumors when administered intravenously and counteract hypoxia through catalase-like oxygen production and subsequent reduction of hypoxia-inducible factor-1α, M2-like macrophages, regulatory T-cell, and programmed death-ligand 1 (PD-L1) expression. The surface plasmon resonance of the nanosheets enables NIR-II phototherapy and photoacoustic imaging, coupling with its ferroptosis and tumor microenvironment reprogram properties to synergize with anti-PD-L1 checkpoint blockade therapy to achieve satisfactory antitumor outcome. This study offers a strategy for localized tumor treatment and boosting the CIC through a straightforward and inexpensive nanomaterial design.

Incremental Inverse Design of Desired Soybean Phenotypes.

We present an application of computational inverse design, which reverses the conventional trial-and-error forward design paradigm, optimizes biological phenotype by directly modifying genotype. The limitations of inverse design in genotype-to-bulk phenotype (G-BP) mapping can be addressed via an established design paradigm: "design, build, test, learn" (DBTL), where computational inverse design automates both the design and learn phases. In any context, inverse design is limited by the fundamental "one-to-many" nature of the inverse function. G-BP inverse design is further limited by the number of single nucleotide polymorphisms that can be made to a member of the population while maintaining feasibility of genotype creation and biological viability. Considering these limitations, we propose a design paradigm based on incremental optimization of phenotype through a combined computational and experimental approach. We intend this work to be a foundational synthesis of well-known techniques applied to the context of genotype-to-bulk phenotype inverse design, which has not yet been performed in the literature. The design pipeline can optimize phenotype by either directly proposing genotypic changes, or simply by suggesting parents to be used for selective breeding. The soybean nested association matrix data set is used to present an in silico case study of the design pipeline by performing optimization that maximizes protein content while constraining other phenotypes. A random forest (RF) is used to model the genotype-to-phenotype relationship, and a genetic algorithm is used to query the RF until a feasible genotype with desired phenotype is discovered. After 20 in silico DBTL cycles, a final population of individuals with a mean protein content of 36.13%, an increase of three standard deviations above the original mean is suggested.

Emerging Zinc‐Ion Capacitor Science: Compatible Principle, Design Paradigm, and Frontier Applications

AbstractThe development of high energy/power density and long lifespan device is always the frontier direction and attracts great research attention in the energy storage fields. Zinc‐ion capacitors (ZICs), as an integration of zinc‐ion batteries and supercapacitors, have been widely regarded as one of the viable future options for energy storage, owing to their variable system assembly method and potential performance improvement. However, the research of ZICs still locate at initial stage until now, and how to construct the suitable systems for different condition is still challenging. Herein, the recent advance in the rational design of ZICs is reviewed in order to construct related theory including compatible principle and design paradigm. It starts with a systematically summary of the fundamental theory as well as the motivation. Then, the electrode materials are classified into capacitor‐type and battery‐type based on the storage mechanism, and the design strategies and progress of these two‐type candidates are comprehensively discussed, aiming to reveal the inherent relationship between the performance of devices and the component as well as architecture of electrode materials. Beyond that, the future perspectives in this emerging field are also given, expecting to guide the construction of high‐performance ZICs for practical applications and boost its development.

3D Light-Direction Sensor Based on Segmented Concentric Nanorings Combined with Deep Learning.

High-precision, ultra-thin angular detectable imaging upon a single pixel holds significant promise for light-field detection and reconstruction, thereby catalyzing advancements in machine vision and interaction technology. Traditional light-direction angle sensors relying on optical components like gratings and lenses face inherent constraints from diffraction limits in achieving device miniaturization. Recently, angle sensors via coupled double nanowires have demonstrated prowess in attaining high-precision angle perception of incident light at sub-wavelength device scales, which may herald a novel design paradigm for ultra-compact angle sensors. However, the current approach to measuring the three-dimensional (3D) incident light direction is unstable. In this paper, we propose a sensor concept capable of discerning the 3D light-direction based on a segmented concentric nanoring structure that is sensitive to both elevation angle (θ) and azimuth angle (ϕ) at a micrometer device scale and is validated through simulations. Through deep learning (DL) analysis and prediction, our simulations reveal that for angle scanning with a step size of 1°, the device can still achieve a detection range of 0∼360° for ϕ and 45°∼90° for θ, with an average accuracy of 0.19°, and DL can further solve some data aliasing problems to expand the sensing range. Our design broadens the angle sensing dimension based on mutual resonance coupling among nanoring segments, and through waveguide implementation or sensor array arrangements, the detection range can be flexibly adjusted to accommodate diverse application scenarios.

Tailoring Light–Matter Interactions in Overcoupled Resonator for Biomolecule Recognition and Detection

HighlightsProposed a new paradigm for nanoantenna design using coupled-mode theory.Designed an OC-Hµ resonator with excellent sensing performance.Using OC-Hµ resonators for biomolecule recognition and detection.

A class-oriented architecture for designing learning apps

ABSTRACT In the age of Apps, where almost everyone is fast becoming accustomed to using apps in almost every walk of life. Such widespread production, consumption, and burgeoning proliferation of Apps are also frequently seen in the various educational pitches and we call them “Learning Apps” (LAs). Now, approximately everyone is believing in and engaging through these apps as the mandatory future of our educational-organizations. However, their overwhelming nature surprised everyone including learners, parents, and other stockholders. Every day, a thousand apps get published, and continuously adding in educational categories of various app stores. Significantly, most LA developers are targeting preschoolers. And, who knows if they contain true educational values or not? Nevertheless, this scenario seems elusive. We observe the emergence of several de facto design paradigms, having no or little theoretical basis. Moreover, their design features do not scientifically connect with evidence-based teaching practices. Despite the expansion of enterprises and the development of new tools and technology, there is a lack of a sound app design strategy grounded in established didactics. Realizing this, we developed A Class-oriented Architecture of LAs to facilitate the content experts’ design.

Protein language models are performant in structure-free virtual screening.

Hitherto virtual screening (VS) has been typically performed using a structure-based drug design paradigm. Such methods typically require the use of molecular docking on high-resolution three-dimensional structures of a target protein-a computationally-intensive and time-consuming exercise. This work demonstrates that by employing protein language models and molecular graphs as inputs to a novel graph-to-transformer cross-attention mechanism, a screening power comparable to state-of-the-art structure-based models can be achieved. The implications thereof include highly expedited VS due to the greatly reduced compute required to run this model, and the ability to perform early stages of computer-aided drug design in the complete absence of 3D protein structures.

Biomimetic Layered Hydrogel Coating for Enhanced Lubrication and Load-Bearing Capacity

Biomimetic hydrogel lubrication coatings with high wettability and low friction show great promise in tissue engineering, wound dressing, drug delivery, and intelligent sensing. Inspired by the hierarchical structure of natural cartilage, a layered hydrogel coating was constructed to functionalize rigid polyetheretherketone (PEEK). The layered hydrogel coating features a structural design comprising a top soft layer and a middle robust layer. The porous structure of the top soft hydrogel layer stores water molecules, providing surface lubrication, while the dense structure of the middle robust hydrogel layer offers load-bearing capacity. These synergistic effects of the gradient hydrogel layer endow the PEEK substrate with an ultra-low coefficient of friction (COF~0.010 at 5 N load), good load-bearing capacity (COF~0.031 at 10 N load), and excellent wear resistance (COF < 0.05 at 5 N load after 20,000 sliding cycles). This study introduces a novel design paradigm for robust hydrogel coatings with exceptional lubricity, displaying the potential application in cartilage replacement materials.

“Guiding University Students towards Sustainability”: A Training to Enhance Sustainable Careers, Foster a Sense of Community, and Promote Sustainable Behaviors

Professional development involves facing numerous challenges. It is a complex process, susceptible to personal aspects (e.g., health, happiness, productivity), but also contextual aspects (e.g., recognition of the complexity and unpredictability of the labor market, and of the need to have a positive impact on the community). The life design paradigm views individuals as active agents in their career construction. Although this approach strongly emphasizes individual agency, it also underscores the importance of addressing broader issues related to sustainability. Indeed, career counselling can stimulate actions that favor sustainable development, benefiting society and enhancing the well-being of all people. To this end, we developed a training to stimulate reflections on sustainable careers, sense of community, and sustainable behavior. The study involved 44 university students divided into an experimental (n = 22) and a control group (n = 22). The first group participated in 16 online activities, interspersed with three in-person meetings. After the training, the experimental group exhibited improvements in sustainable careers, sense of community, self-efficacy in implementing sustainable behavior, and the perceived importance of promoting sustainability. These findings suggest that career counselling activities can significantly increase the personal resources of university students, equipping them to contribute to society and promote a sustainable world.

Needle-Plug/Piston-Based Modular Mesoscopic Design Paradigm Coupled With Microfluidic Device for Point-of-Care Pooled Testing.

Emerging diagnostic scenarios, such as population surveillance by pooled testing and on-site rapid diagnosis, highlight the importance of advanced microfluidic systems for in vitro diagnostics. However, the widespread adoption of microfluidic technology faces challenges due to the lack of standardized design paradigms, posing difficulties in managing macro-micro fluidic interfaces, reagent storage, and complex macrofluidic operations. This paper introduces a novel modular-based mesoscopic design paradigm, featuring a core "needle-plug/piston" structure with versatile variants for complex fluidic operations. These structures can be easily coupled with various microfluidic platforms to achieve truly self-contained microsystems. Incorporated into a "3D extensible" design architecture, the mesoscopic design meets the demands of function integration, macrofluid manipulations, and flexible throughputs for point-of-care nucleic acid testing. Using this approach, an ultra-sensitive nucleic acid detection system is developed with a limit of detection of ten copies of SARS-CoV-2 per mL. This system efficiently conducts large-scale pooled testing from 50 pharyngeal swabs in a tube with an uncompromised sensitivity, enabling a truly "sample-in-answer-out" microsystem with exceptional performance.

Light‐Activated Nanocatalyst for Precise In‐Situ Antimicrobial Synthesis via Photoredox‐Catalytic Click Reaction

AbstractThe excessive and prolonged use of antibiotics contributes to the emergence of drug‐resistant S. aureus strains and potential dysbacteriosis‐related diseases, necessitating the exploration of alternative therapeutic approaches. Herein, we present a light‐activated nanocatalyst for synthesizing in situ antimicrobials through photoredox‐catalytic click reaction, achieving precise, site‐directed elimination of S. aureus skin infections. Methylene blue (MB), a commercially available photosensitizer, was encapsulated within the CuII‐based metal–organic framework, MOF‐199, and further enveloped with Pluronic F‐127 to create the light‐responsive nanocatalyst MB@PMOF. Upon exposure to red light, MB participates in a photoredox‐catalytic cycle, driven by the 1,3,5‐benzenetricarboxylic carboxylate salts (BTC−) ligand presented in the structure of MOF‐199. This light‐activated MB then catalyzes the reduction of CuII to CuI through a single‐electron transfer (SET) process, efficiently initiating the click reaction to form active antimicrobial agents under physiological conditions. Both in vitro and in vivo results demonstrated the effectiveness of MB@PMOF‐catalyzed drug synthesis in inhibiting S. aureus, including their methicillin‐resistant strains, thereby accelerating skin healing in severe bacterial infections. This study introduces a novel design paradigm for controlled, on‐site drug synthesis, offering a promising alternative to realize precise treatment of bacterial infections without undesirable side effects.