192815 research outputs found
Sort by
Comparative analysis of waste heat capture technologies applied to battery energy storage systems
Get PDFWaste heat capture and reuse from battery storage systems for cogeneration of heat and power has the potential to both improve their energy efficiency and reduce the carbon footprint. This study performs a comparison of technologies capable of converting the waste heat extracted to a useful purpose. This analysis is accomplished using the literature data as a basis for an analytical hierarchy process (AHP) applying technological efficiency, cost effectiveness, footprint and integration, and safety and environmental concerns as the criteria. Of these, cost effectiveness was found to be dominant, with technological efficiency also showing high importance. Heat pumps were found to be the most effective based on the objective and criteria of this analysis. This study dictates a pathway that allows stakeholders and decision makers to determine a route by which site-specific comparisons may be made, aiding them to navigate the complex interplay of competing objectives
Small island developing states: emerging harmscapes and criminological directions
No full textThe chapter will argue that Small Island Developing States (SIDS) constitute the epicentre of diverse and converging ‘harmscapes’, associated with both new and old harms—from crime to climate change, to various developmental and everyday insecurities. We therefore propose theoretical and conceptual pathways or ‘lines of flight’ by which criminology can not only engage with converging harmscapes and the everyday insecurities and crises that inhabitants of SIDS face but also better engage with the challenges of operationalising often Western-centric and siloed criminal justice framings in these contexts. Furthermore, implementing the Sustainable Development Goals in these contexts provides a further challenge unless the realities of everyday security governance challenges are made visible. We therefore have to move beyond conventional criminological and policy approaches and to this effect, we present a research agenda towards uncovering and theorising converging harmscapes in SIDS
Micro-fabricated THz antenna for short-range wireless communication
Get PDFIn the rapidly evolving field of terahertz (THz) communications, the design and fabrication of efficient antennas pose significant challenges due to the inherent complexities of operating at such high frequencies. This paper presents a microfabricated THz antenna array featuring triangular-slot patches designed to enhance bandwidth, gain, and efficiency at THz frequencies from 0.70 to 0.95 THz. The design involves utilizing a coplanar waveguide (CPW) feed technique to simplify the microfabrication process, improving antenna integration by enhancing impedance matching and reducing transmission losses. To optimize the antenna geometry, a machine learning (ML)–assisted global optimization method, specifically the surrogate-assisted differential evolution algorithm, is used to improve bandwidth, gain, and tolerance to fabrication variations. The prototype is fabricated on a flexible polyimide substrate using electron beam lithography, with a titanium/gold (Ti/Au) metallization stack of 10/350 nm. The proposed design achieves a simulated impedance bandwidth of 37.5% (from 0.70 to 0.95 THz), a simulated radiation efficiency of 85%, and a simulated gain of 8.71 dBi, making it a potential candidate for short-range wireless communication applications. Owing to the unavailability of in-house measurement facilities at THz frequencies, the experimental validation could not be performed at this stage; however, the design process is supported by full-wave electromagnetic simulation along with an extensive optimization of every parameter using ML-enabled optimization, which are established as reliable and effective methods for antenna design and performance prediction. These results highlight its potential for compact, high data rate short-range THz systems
Feature, not bug: toward a theoretical framework for online incivility
No full textNo abstract available
Accelerating single-atom ORR catalyst discovery through theory and machine learning: a critical review
Get PDFThe oxygen reduction reaction (ORR) is an important efficiency-determining process in fuel cells and metal-air batteries, requiring highly efficient and low-cost electrocatalysts. Single-atom catalysts (SACs) have recently emerged as a revolutionary type of catalyst for ORR reaction due to their optimized atom use, precise coordination environment, and controlled electronic structure. Theoretical simulations, especially density functional theory (DFT), have been highly influential in understanding mechanisms of ORR reaction and defining structure-activity relationships of SACs during the last few years. Nevertheless, a very substantial number of possible SAC compositions and structures represents an intrinsic difficulty of solely theoretical catalyst research. In this context, synergy of machine learning (ML) with DFT results has emerged a new paradigm with high potential for speeding up the rational design of SACs for ORR. This review presents a compilation of the latest results on the theory-guided and ML-assisted investigations on ORR active SACs. First, basic concepts of ORR, theory-based descriptors for ORR activity, selectivity, and stability at isolated metallic sites are reviewed. Next, the latest approaches based on ML, including supervised machine learning, descriptor-based approaches, high-throughput techniques, and generative modeling, which use DFT-based data to quickly estimate the ORR energetics of promising SAC structures. Particular attention is given to M–N–C catalysts, coordination asymmetry, axial ligation, frameworks described by dual descriptors, and the role of graph neural networks for the local chemical environments. Finally, we also payed special attention to the challenges, such as the lack of sufficient data, interpretability, and the aforementioned transferability and dynamic effects. Concluding, we provided future perspectives on closed-loop autonomous catalyst discovery, the theory, machine learning, and experimental validation for the development of the next generation ORR electrocatalysts
SOI asymmetrical directional coupler based photonic biosensor for 1550nm optical range
Get PDFPoint-of-care testing is essential for providing rapid and cost-effective medical diagnostics close to the patient. Current devices, however, often face limitations in sensitivity and practicality, motivating the development of advanced optical biosensors. This study presents the design and simulation of an asymmetrical directional coupler-based biosensor, analysed in both the frequency and time domains. The device employs a Silicon-on-Insulator substrate, comprising a straight optical waveguide positioned alongside a slotted waveguide. Detection is achieved via selective mode coupling and evanescent field sensing, which respond to changes in the surrounding refractive index. The sensor achieved a sensitivity of 624 nm/RIU, a Figure of merit of 31.6 RIU⁻¹, an estimated detection limit of 1.15 × 10^(-3) RIU and an effective quality factor of 108. These findings demonstrate the potential of the device for rapid, affordable refractive index sensing in healthcare environments. With further modifications, the sensor could support on-chip spectrometry, enhancing its versatility, portability, and suitability for POCT
Homogenised balance equations for nematic liquid crystal flow in elastic porous media
Get PDFWe derive a new mathematical model for the macroscopic behaviour of a linear elastic porous medium weakly interacting with an incompressible, slowly flowing, nematic liquid crystal under the one elastic constant approximation and a simplified hypothesis concerning the fluid viscosities for which the stress tensor remains dependent on the nematic director, which is the average fluid molecular orientation, but is symmetric. In this situation, the angular momentum equation, which governs the dynamics of the nematic director, decouples from the linear momentum equations of the fluid. As such, whilst the nematic anisotropy affects the flow profile, the fluid flow no longer affects the configuration of the nematic director. We assume that the typical pore dimension (the microscale) is significantly smaller than the average size of the whole domain (the macroscale), and exploit this sharp length-scale separation in our use of the asymptotic homogenisation technique to derive new macroscale governing equations by upscaling the fluid–structure interaction problem between the porous elastic structure and the nematic liquid crystal fluid phase. The resulting novel anisotropic macroscale viscoelastic model describes the overall system representing a nematic liquid crystal flowing through an elastic porous solid and could therefore be termed an anisotropic poro-viscoelastic model. This system of partial differential equations incorporates the nematic director, its spatial variations, and the underlying microstructure through coefficients that are computed by solving appropriate microscale cell problems. The homogenised constitutive relationships account for the roles of the nematic director field, the elastic response of the solid phase, and their interplay with the underlying microstructural configuration. We then focus on the particular case in which the role of the elastic porous structure is negligible. In this case, the fluid flow is no longer affected by the deformations of the porous medium and is solely driven by a volume load, which depends on macroscale spatial variations of the nematic director and its interplay with the underlying microscale geometry. The resulting theoretical framework opens up new modelling possibilities for a wide range of potential applications for nematic liquid crystals encapsulated in a complex porous network
Portable system for flexible micro-endoscopy using a multi-mode fibre
No full textAdvances in imaging through a single multi-mode fiber (MMF) have made it a strong competitor to conventional endoscopic imaging technologies. However, these advancements have predominantly remained confined to laboratory environments. The transition to real-world applications has been hindered by several challenges. In this work, we address three of these challenges: device size and portability, speed and simplicity of calibration, and the robustness of the imaging to fiber flexing. We have developed a fully integrated, compact imaging system housed in a
15
cm
×
25
cm
×
35
cm
unit. This portable system accommodates power management, serial communication, and optical components, making it suitable for practical deployment outside the laboratory. We use far-field diffuse-reflection imaging through a custom-built dual-fiber needle with a graded-index illumination fiber. We have incorporated a fast fixed-point arithmetic graphics processing unit (GPU) for calculating binary holograms. This enables a setup and calibration in 40 s. Finally, we demonstrate real-time image streaming using a dynamic calibration library, which maintains image quality even under continuous fiber bending. This image quality can be maintained without monitoring or knowledge of the fiber bend. Our innovations in calibration speed, portability, and fiber flexibility open new avenues for MMF use in minimally invasive imaging applications, ranging from minimally invasive medical imaging to the industrial inspection of complex structures
Data sources:
Access Repository Dashboard
Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇