1. Material Engineering Solutions toward Selective Redox Catalysts for Chemical-Looping-Based Olefin Production Schemes: A Review 

   Oing, Alexander; von Mueller, Elena; Donat, Felix; et al. (2024)

   Energy & Fuels

   Chemical looping (CL) has emerged as a promising approach in the oxidative dehydrogenation (ODH) of light alkanes, offering an opportunity for significant reductions in emissions and energy consumption in the ethylene and propylene production industry. While high olefin yields are achievable via CL, the material requirements (e.g., electronic and geometric structures) that prevent the total conversion of alkanes to CO x are not clearly ...

   Review Article

2. Geometry transition in spinfoams 

   Christodoulou, Marios; DAmbrosio, Fabio; Theofilis, Charalampos (2024)

   Classical and Quantum Gravity

   We show how the fixed-spin asymptotics of the EPRL model can be used to perform the spin-sum for spin foam amplitudes defined on fixed two-complexes without interior faces and contracted with coherent spin-network states peaked on a discrete simplicial geometry with macroscopic areas. We work in the representation given in (Han and Krajewski 2014 Class. Quantum Grav. 31 01500). We first rederive the latter in a different way suitable for ...

   Journal Article

3. Investigation of Irreversible CO₂ Interactions with Clay Minerals for the Passive Regulation of CO₂ in Indoor Environments 

   Arris-Roucan, Sofia; Du, Yi; Brumaud, Coralie; et al. (2024)

   RILEM Bookseries

   While the passive moisture buffering properties of earthen materials are well known, recent studies have explored their potential to improve indoor air quality by buffering indoor pollutants, particularly CO2. Previous research has shown that the material interacts with CO2, but that some of the adsorbed CO2 may not be fully released in a humid environment, which is investigated in this study. To investigate the physico-chemical interactions, ...

   Conference Paper

4. Enhancing Neural Architecture Search With Multiple Hardware Constraints for Deep Learning Model Deployment on Tiny IoT Devices 

   Burrello, Alessio; Risso, Matteo; Motetti, Beatrice Alessandra; et al. (2024)

   IEEE Transactions on Emerging Topics in Computing

   The rapid proliferation of computing domains relying on Internet of Things (IoT) devices has created a pressing need for efficient and accurate deep-learning (DL) models that can run on low-power devices. However, traditional DL models tend to be too complex and computationally intensive for typical IoT end-nodes. To address this challenge, Neural Architecture Search (NAS) has emerged as a popular design automation technique for co-optimizing ...

   Journal Article

5. Functional supraparticles produced by the evaporation of binary colloidal suspensions on superhydrophobic surfaces 

   Shneidman, Anna V.; Zhang, Cathy T. Y.; Mandsberg, Nikolaj K.; et al. (2024)

   Soft Matter

   Hierarchically structured supraparticles can be produced by drying droplets of colloidal suspensions. Using binary suspensions provides degrees of structural and functional control beyond those possible for single components, while remaining tractable for fundamental mechanistic studies. Here, we implement evaporative co-assembly of two distinct particle types - 'large' polystyrene microparticles and 'small' inorganic oxide nanoparticles ...

   Journal Article

Mehr anzeigen