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From lab to building: Real-world integration of phase change materials for comfort, energy, and flexibility
No full textPhase change materials (PCMs) are widely promoted for improving thermal comfort and reducing energy demand in buildings. Yet, most studies remain laboratory- or simulation-based, offering limited insight into real-world performance. This paper bridges that gap by synthesizing evidence from eight full-scale, monitored buildings at Technology Readiness Levels (TRL) 6-9, complemented by insights from an expert focus group. Results show that PCM effectiveness is governed primarily by design integration, not material formulation, with placement depth, control strategy, and climate alignment proving decisive. Across cases, measured performance indicates consistent but conditional benefits: peak indoor temperature reductions of 1-3 degrees Celsius, heating or cooling load savings of 10-25 %, and emerging though under-reported contributions to demand-side flexibility. A typology of PCM integration strategies is proposed, mapping observed outcomes by building type, climate, placement, and control logic. KPI synthesis reveals a previously undocumented trend: a moderate negative correlation between areal storage capacity and comfort-hour improvement, suggesting that greater storage does not necessarily yield better results. The study also identifies structural barriers to deployment, including the regulatory invisibility of latent storage and the absence of standards for building-level PCM testing and certification. By reframing PCMs as integrated building-system components rather than niche materials, this work offers design guidance, performance benchmarks, and a roadmap to advance PCM adoption toward more flexible, resilient buildings
Global implications of a low soil moisture threshold for microbial hydrogen uptake
Get PDFThe impact of increasing anthropogenic hydrogen (H2) emissions on Earth’s radiative balance depends on the soil microbial H2 sink—the largest and most uncertain term in the global H2 budget. Soil moisture is a primary but poorly quantified control regulating the soil sink. Here, we assess the sensitivity of microbial H2 oxidation to soil moisture in laboratory experiments with temperate and arid soils spanning distinct textures. We report H2 oxidizer activity down to –70 to –100 MPa water potentials across soils, which are among the driest conditions reported for microbial activity and are much drier than assumed in global simulations of H2. Using genome-resolved meta-omics, we link H2 oxidation dynamics in temperate soils to specific desiccation-adapted microbial taxa that contribute differentially to H2 uptake along the moisture gradient. Through global simulations, we show that our observationally constrained drier moisture threshold increases the contribution of arid and semi-arid regions for soil H2 uptake by 4-7 percentage points (pp), while decreasing the contribution of temperate and continental regions (−7 pp). Our results highlight the importance of H2 uptake under extreme hydrological conditions, particularly the roles of desertification, dryland expansion, and H2-oxidizer ecophysiology in modulating long-term changes in H2 uptake
adabmDCA 2.0—A Flexible but Easy-to-Use Package for Direct Coupling Analysis
No full textIn this methods article, we provide a flexible but easy-to-use implementation of direct coupling analysis (DCA) based on Boltzmann machine learning, together with a tutorial on how to use it. The package adabmDCA 2.0 is available in different programming languages (C formula presented , Julia, Python) usable on different architectures (single-core and multicore CPU, GPU) using a common front-end interface. In addition to several learning protocols for dense and sparse generative DCA models, it allows to directly address common downstream tasks like residue-residue contact prediction, mutational-effect prediction, scoring of sequence libraries, and generation of artificial sequences for sequence design. It is readily applicable to protein and RNA sequence data
Anti-Slip Material-Based Strategies and Approaches
Get PDFSlip-related injuries and vehicle skids in low-friction environments highlight the urgent need for advanced anti-slip materialsto improve safety and prevent accidents. This review summarizes the fundamental mechanisms of slipping, drawing on contactmechanics and a proposed friction behavior model for surface interfaces. Strategies to enhance anti-slip performance such assurface texturing, chemical modification, and filler incorporation are discussed. Standardized evaluation methods, includingfriction testing, the British Pendulum Test, and the ramp test, are reviewed alongside other common assessment techniques. Thepractical applications of anti-slip materials are explored, with emphasis on high-risk areas like roadways and winter footwear.Challenges in achieving durable, high-performance solutions are outlined, and future research directions are suggested. Byintegrating current advancements and practical considerations, this review supports the development of next-generation anti-slipsystems aimed at enhancing safety and functionality across diverse application
A comprehensive formalism for air-gap membrane distillation applied to the design of full-scale modules with direct solar heating
Get PDFAir-gap membrane distillation (AGMD) is used to extract volatile compounds from a heated feed solution,
through a porous hydrophobic membrane, into a cooled compartment, then recovered by condensation. AGMD is
a promising technology for desalination and aqueous concentration, but its scale-up is limited by incomplete
physical descriptions of the module physics. This work proposes a new CFD-based multiphysics framework to
design AGMD full-scale plate-and-frame modules for freshwater extraction. The three physics features comprised
within an AGMD module are first formalized: (i) the flow of a solution in contact with a porous membrane; (ii)
gas mixture (vapor) transport through a porous membrane; (iii) vapor condensation on a (vertical) surface. They
are thus combined into a consistent formalism of the AGMD module physics, with a particular focus on gas
transport built upon the Maxwell-Stefan theory, which is here improved to account for medium vapor saturation.
Model predictions are validated experimentally against lab-scale AGMD data for feed temperature up to 60 ◦C.
The model is then employed to assess full-scale flat-sheet modules, connected in series, and enhanced with direct
solar heating. Simulations reveal that system productivity is highly sensitive to configuration (single vs. multi-
module; bulk solar vs. direct solar heating), with optimal productivity achieved with considerably different
module compartment design and process parameters. When enhanced with direct solar heating, system optimal
productivity can increase by up to 230 % compared to standard configurations. This formalism provides a robust
basis for AGMD modules design and prior to their effective integration into real-world desalination system
Composite Materials: New Technology Applications
Get PDFL'abstract è presente nell'allegato / the abstract is in the attachmen
Computational Optimization Techniques to Design RF Circuits
Get PDFWe present a comprehensive review of computational optimization techniques for the design of RF circuits. Important design techniques used to optimize RF circuits, such as genetic algorithms (GAs), particle swarm optimization (PSO), reinforcement learning (RL), Bayesian optimization (BO), and space mapping (SM), are discussed. The basics of the techniques, their merits, and their drawbacks are covered so that new researchers can understand the relevant theories of the techniques. A comparative analysis of design techniques is included. This article also provides insights into the present state and future directions of the optimization techniques
Rethinking Eco-Compatible Tourist Accommodations: A Case Study in the Delta Del Po Natural Park
No full textAs defined by the World Tourism Organization, sustainable tourism seeks to balance environmental preservation, respect for local cultures, and economic viability. In protected natural areas, such as the UNESCO-designated Delta del Po Natural Park, this balance requires careful consideration of environmental resources, the cultural identity of hosting communities, and long-term socio-economic benefits. The design of outdoor accommodations in these areas is particularly critical, as it directly influences ecological impacts and visitor experiences. This research addresses the challenge of developing eco-compatible constructions for the Delta del Po Natural Park, by combining site and microclimatic analysis and user-needs. Key principles include the integration of passive bioclimatic strategies, the use of bio-based materials, and the reversibility of structures. A pilot project was analysed and optimisation strategies were proposed to enhance environmental performance. Interventions included improving the building envelope implementing passive strategies, and material substitution with bio-based options. Preliminary findings show potential reductions in environmental impact highlighting the role of bio-based materials and eco-compatible technologies in achieving sustainable construction in biodiverse areas
Compact Photostorage Systems: New Materials and Designs for Integrated Energy Harvesting and Storage
Get PDFThe growing demand for flexible and autonomous electronics hasaccelerated the development of compact energy systems capable of both harvesting and storing solar energy. Photobatteries and photocapacitorsrepresent a new generation of self-charging devices that merge photovoltaic and electrochemical functions within a single structure. These systems overcome the conversion losses and bulkiness of conventional solar-battery combinations, enabling miniaturized, efficient, and sustainable power sources. This review summarizes recent progress in materials, architectures, and design strategies for compact photostorage systems. This work will focus, in particular, on two-terminal (2T) monolithic configurations that provide the highest integration level. Advances in inorganic semiconductors such as transition-metal oxides, sulfides, and lead-free perovskites, as well as organic materials including conductive polymers, dyes, and carbon nanostructures, have greatly enhanced photo-charge generation, mobility, and retention. Furthermore, innovations in gel and solid-state electrolytes have improved flexibility, safety, and long-term stability. Despite significant progress, major challenges remain in mitigating charge recombination, optimizing energy density and standardizing performance evaluation. By integrating recent results and emerging trends, this review outlines key directions for the rational design of next-generation self-powered photostorage systems that could underpin the future of portable, wearable, and sustainable energy technologies
Bayesian Goal Inference Engine for Intent Prediction in Human-Robot Interaction
No full textThis paper presents a robust approach for enhancing Human-Robot Interaction (HRI) through short-term human hand motion prediction, enabling robots to better anticipate human intentions in shared spaces. By leveraging real-time body tracking for monitoring human motion, the system integrates model-based hand path generation into a Bayesian inference framework to predict reaching goals. Incorporating both hand and shoulder data, the approach improves the accuracy and responsiveness of the proposed Bayesian recursive classifier, supporting seamless and intuitive collaboration. A comprehensive testing phase using offline tracking data demonstrates the method’s superior performance compared to state-of-the-art approaches. A collaborative assembly use case designed to validate the applicability and effectiveness of the approach in a real-world setting further demonstrated increased efficiency and fluency in HRI. By enabling robots to interpret and reactively respond to fast-changing human intentions in real-time, this research contributes to the advancement of social robotics, promoting natural and effective interactions in various contexts, such as domestic assistance, healthcare, and industrial environments, where trust, timing, and coordination are key to successful human-robot teamwork