Energy saving potential of advanced dual-band electrochromic smart windows for office integration

Integrating dynamic transparent technologies into building envelopes is becoming crucial for tackling the challenges posed by climate change, improving energy efficiency, and enhancing occupant comfort. Nowadays, a range of dynamic glazing technologies exists, among which electrochromic glazing is notably effective in contributing to sustainability objectives in building design. This paper presents a comprehensive simulation analysis of the energy efficiency and interior comfort impacts of a novel class of spectrally selective dual-band electrochromic windows, also referred to as “Plasmochromic”. A simplified office model, oriented both south and west, was used to compare the performance of dual-band electrochromic glazing, using experimental data collected from a window-scale prototype, with that of commercially available advanced glazing systems. The comparison was conducted under two different control strategies: a rule-based and a model-based control algorithm. Five European climate zones have been considered to cover most of the continent's climatic conditions and provide a comprehensive evaluation of the glazing performances. The simulations demonstrate the superior capability of dual-band electrochromic windows, when coupled with an intelligent control strategy, in reducing total annual energy consumption for heating, cooling, and lighting by up to 27% compared to the best-performing static solar control glazing systems. Additionally, they achieve a reduction of up to 32% in visual discomfort, measured by the cumulative value of useful daylight illuminance

A New Approach to Assess the Building Energy Performance Gap: Achieving Accuracy Through Field Measurements and Input Data Analysis

The performance gap is defined as the difference between a calculated and measured quantity, and in buildings, it may refer to the energy performance or the indoor thermal conditions. According to the literature analysis, most studies start from simulation results and define methods and approaches to minimise the discrepancy against the measured values. This paper presents an alternative and innovative approach to the problem, starting with measurements in a fully instrumented and monitored living lab consisting of seven office rooms used to build and validate an accurate calculation model. The model is applied to observe how different input modes of the most relevant parameters affect the performance gap. The model exhibits high accuracy: the coefficient of variation of the root mean square error scores is 2.3% for thermal free-floating and 10% and 14% for final cooling and heating energies, respectively. Depending on the single input variations, overestimation above 50% and underestimation below 40% are calculated for a given energy service. Results show that the weather data, occupancy profiles, related internal gains, and ventilation rates can significantly affect the performance gap. The outcomes of this field study call for new analyses aimed at generalising the achieved results and developing appropriate modes to input the relevant parameters to minimise the performance gap with limited calculation efforts

KAN You See It? KANs and Sentinel for Effective and Explainable Crop Field Segmentation

Segmentation of crop fields is essential for enhancing agricultural productivity, monitoring crop health, and promoting sustainable practices. Deep learning models adopted for this task must ensure accurate and reliable predictions to avoid economic losses and environmental impact. The newly proposed Kolmogorov-Arnold networks (KANs) offer promising advancements in the performance of neural networks. This paper analyzes the integration of KAN layers into the U-Net architecture (U-KAN) to segment crop fields using Sentinel-2 and Sentinel-1 satellite images and provides an analysis of the performance and explainability of these networks. U-KAN performs comparable to or better than the full-convolutional U-Net in half of the GFLOPs. Furthermore, gradient-based explanation techniques show that U-KAN predictions are highly plausible and that the network has a very high ability to focus on the boundaries of cultivated areas rather than on the areas themselves. The per-channel relevance analysis also reveals which channels are critical for explaining model behavior and which have little to no impact, thus providing insights into the features the model relies on for the segmentation task

New insights in large-pores mesoporous silica microspheres for hemostatic application

Hemorrhages are still considered a common cause of death and despite the availability of different hemostatic agents it is still necessary to develop more effective hemostats for bleeding managements in emergency situations. Herein, large-pores mesoporous silica microspheres (MSM) were synthesized, and their surface was modified to enrich the hydroxyls population with the aim of achieving a material with enhanced water adsorption capacity and high hemostatic ability. The success of surface modification was investigated by Fourier Transform Infrared spectroscopy (FT-IR) and thermogravimetric analysis (TGA), which confirmed the increase in the amount of surface hydroxyl groups. A hemolysis assay as well as a clotting test were carried out to evaluate the hemocompatibility and hemostatic ability, respectively. It was found that the modified material presented the lowest hemolytic ratio and the lowest clotting time. The novelty of the paper is mainly due to the coupling of the hemostatic ability test with the adsorption microcalorimetry of water. In fact, being the water adsorption on the material surface a crucial factor in the hemostatic activity, microcalorimetry was used for the first time to study the adsorption of water and estimate its heat of adsorption. The data obtained showed that the modified MSM presents a surface able to adsorb a higher amount of water, compared to the pristine MSM, with a low molar heat of adsorption (about 35 kJ/mol), which renders the modified MSM presented in the present study an excellent candidate for producing novel hemostats

A Data-Driven Process for Optimal Incentive Sharing in Collective Self-Consumption Groups of Residential Users

With the widespread adoption of renewable energy systems in residential buildings, particularly in the context of collective self-consumption groups (CSC) and Renewable Energy Communities (REC), understanding user behavior becomes pivotal for enhancing energy efficiency and increasing the energy share among participants for an optimal use of renewable resources. Regardless of which configuration is adopted (CSC or REC), a key aspect is how to share the generated economic benefits from the self-produced energy and identify the fairest way to distribute the incentive derived from the shared energy among users. In this context, the aim of this work is to introduce a data-driven energy benchmarking process that leverages the analysis of long-term monitoring data of residential buildings to i) characterize energy consumption patterns of users over time, ii) support the development of an optimal incentive sharing mechanism among users involved in such legal entities. The proposed approach is tested on a monitored residential building, located in Northern Italy, which includes 13 flats and is equipped with a centralized photovoltaic system

Tensile Response and Durability of Flax-TRMs

Textile Reinforced Mortar (TRM) systems are currently among the most effective retrofitting solutions for masonry structures, thanks to their high compatibility with the substrate, and reversibility. Recently, the adoption of natural textiles as reinforcement in TRM systems has attracted the interest of researchers and industry, due to their great potential of providing a cost effective and sustainable solution while ensuring adequate structural performance. Despite the increasing number of studies focusing on the characterisation of short-term tensile properties, the long-term durability performance of natural TRMs, which is fundamental to ensure their viability in construction applications, has not been examined in detail. This paper aims to investigate the tensile behaviour of flax textiles and flax-TRM composites and assess their residual performance after exposure to accelerated ageing. Composites consisting of two and three layers of a bi-directional flax fabric embedded in a lime-based mortar were conditioned in water for 1000 h and 2000 h at controlled temperatures of 23°C and 40°C. Bare textiles were also aged in an alkaline solution for equivalent exposure times and temperatures, to replicate the conditions within the lime-based matrix environment. Both unconditioned and aged textiles and composites were tested under uniaxial tension to determine their tensile behaviour. The complete load-deformation response was assessed employing both contact and non-contact methods (i.e. 2D Digital Image Correlation). It is shown that ageing strongly affects the textile reinforcement, resulting in a significant strength loss of the composite system

Unfolding Potential and Challenges in Molecular Field-Coupled Nanocomputing

Molecular Field-Coupled Nanocomputing (MolFCN) represents a revolutionary approach to computational technology, exploiting single molecules for encoding and processing logical information. MolFCN permits zero-current logical operations to achieve ultra-low power and hyper-miniaturized computing units. This perspective article explores the current state and future potential of MolFCN, highlighting recent technological advancements, potential applications, and the significant challenges that lie ahead. Despite the challenges, the pathway to practical implementation holds significant promise, with obstacles such as scalability, stability, integration, and practical considerations offering opportunities for innovation and advancement. MolFCN can shape the future of nanocomputing and contribute to current major challenges in nanoelectronics by opening key research directions

Experimental investigation of a novel modular multi-purpose floating structure concept

Modular multi-purpose floating structures (MMFS) provide a possible solution to the growing need for space resulting not only from the rapidly growing global population but also from the emerging blue economy and specifically offshore renewables sector. The desired space is generated in a more sustainable way than traditional land reclamation methods, by interconnecting together modular floating platforms, making this technology adaptable and suited to a broad range of possible offshore activities. This study experimentally investigates the hydrodynamic response of a novel concept of modular multi-purpose floating structure, composed by floating modules connected with semi-rigid connectors and moored at the seabed using a taut mooring system solution. The 1:50 model consists of three hexagonal floating platforms, linked together by a semi-rigid connector system that emulate the mechanical behaviour of the full-scale system. The model has been tested under representative sea state conditions at the wave basin of the Laboratory of Hydraulic Engineering (LIDR) of Università degli Studi di Bologna. This paper describes the experimental setup and preliminary results of the dynamic behaviour of the MMFS system, with particular focus on platforms kinematics, mooring and connectors loads