Abstract: A growing body of literature has recognized the non-thermal effect of pulsed microwave radiation (PMR) on bacterial systems. However, its mode of action in deactivating bacteria has not yet been extensively investigated. Nevertheless, it is highly important to advance the applications of PMR from simple to complex biological systems. In this study, we first optimized the conditions of the PMR device and we assessed the results by simulations, using ANSYS HFSS (High Frequency Structure Simulator) and a 3D particle-in-cell code for the electron behavior, to provide a better overview of the bacterial cell exposure to microwave radiation. To determine the sensitivity of PMR,<italic>Escherichia coli</italic> and<italic>Staphylococcus aureus</italic>cultures were exposed to PMR (pulse duration: 60 ns, peak frequency: 3.5 GHz) with power density of 17 kW/cm²at the free space of sample position, which would induce electric field of 8.0 kV/cm inside the PBS solution of falcon tube in this experiment at 25 °C. At various discharges (D) of microwaves, the colony forming unit curves were analyzed. The highest ratios of viable count reductions were observed when the doses were increased from 20D to 80D, which resulted in an approximate 6 log reduction in <italic>E. coli</italic>and 4 log reduction in<italic>S. aureus.</italic>Moreover, scanning electron microscopy also revealed surface damage in both bacterial strains after PMR exposure. The bacterial inactivation was attributed to the deactivation of oxidation-regulating genes and DNA damage.

Abstract: Meeting rooms are reserved 30% of working hours but only used for 20% of that time. By implementing a strategy where the available capacity is leased to the wider market rather than just the building users, there is a positive impact on the economic, environmental, and social factors of the building and its surroundings. This study uses the building 'The Globe' in The Hague as a case study, and then projects the results to the entire city. In case of The Globe, implementing a lease out strategy achieves a reduction of 36% of the annual rent of the meeting rooms to the building's tenant. The owner benefits from a revenue increase of 12.5%, with the same operational expenses (except the reservation system), leading to a proportional higher valuation of the building. Annual energy consumption may be lowered by 6.2%. This study contributes to the literature by considering the total benefits that could be obtained by more efficient use of office space that is currently underused. The application of technology generates added value for economic, environmental, and social factors. These factors are important in real estate as they (among others) have a direct link to the Environmental, Social and Governance (ESG) analysis that investors make before proceeding with an investment.

Abstract: This publication introduces the audiovisual geometry database with Gielis transformations as initial records for a prototype of the database. A concise overview is given of the rationale behind the database and studying wave phenomena with Gielis transformations. First results on a form of timbral polyphony observed in Gielis curves and future work are briefly discussed.

Abstract: High-energy lithium-rich layered transition metal oxides are capable of delivering record electrochemical capacity and energy density as positive electrodes for Li-ion batteries. Their electrochemical behavior is extremely complex due to sophisticated interplay between crystal structure, electronic structure, and defect structure. Here we unravel an extra level of this complexity by revealing that the most typical representative Li1.2Ni0.13Mn0.54Co0.13O2 material, prepared by a conventional coprecipitation technique with Na2CO3 as a precipitating agent, contains abundant coherent (001) grain boundaries with a Na-enriched P2-structured block due to segregation of the residual sodium traces. The trigonal prismatic oxygen coordination of Na triggers multiple nanoscale twinning, giving rise to incoherent (104) boundaries. The cationic layers at the (001) grain boundaries are filled with transition metal cations being Mn-depleted and Co-enriched; this makes them virtually not permeable for the Li+ cations, and therefore they negatively influence the Li diffusion in and out of the spherical agglomerates. These results demonstrate that besides the mechanisms intrinsic to the crystal and electronic structure of Li-rich cathodes, their rate capability might also be depreciated by peculiar microstructural aspects. Dedicated engineering of grain boundaries opens a way for improving inherently sluggish kinetics of these materials.

Abstract: Gold nanoparticles (Au NPs) with surface plasmonic resonance (SPR) effect and excellent internal electron transfer ability have widely been combined with semiconductors for photocatalysis. However, the in-depth effects of Au NPs in multicomponent photocatalysts have not been completely understood. Herein, ternary titanium oxide-gold-cadmium sulfide (TiO2-Au-CdS, TAC) photocatalysts, based on hierarchical TiO2 inverse opal photonic crystal structure with different Au NPs sizes have been designed to reveal the SPR effect and internal electron transfer of Au NPs in the presence of slow photon effect. It appears that the SPR effect and internal electron transfer ability of Au NPs, depending on their sizes, play a synergistic effect on the photocatalytic enhancement. The ternary TAC-10 photocatalyst with – 10 nm Au NPs demonstrates an unprecedented hydrogen evolution rate of 47.6 mmolh-1g 1 under visible-light, demonstrating- 48% enhancement comparing to the sample without slow photon effect. In particular, a 9.83% apparent quantum yield under 450 nm monochromatic light is achieved for TAC-10. A model is proposed and finite-difference time-domain (FDTD) simulations reveal the size influence of Au NPs in ternary TAC photocatalysts. This work suggests that the rational design of bifunctional Au NPs coupling with slow photon effect could largely promote hydrogen production from visible-light driven water splitting. (c) 2021 Elsevier Inc. All rights reserved.

Abstract: Fluorophores functionalized with heavy elements show enhanced intersystem crossing due to increased spin-orbit coupling, which in turn shortens the fluorescence decay lifetime (tau(PL)). This phenomenon is known as the heavy-atom effect (HAE). Here, we report the observation of increased tau(PL) upon functionalisation of near-infrared photoluminescent gold nanoclusters with iodine. The heavy atom-mediated increase in tau(PL) is in striking contrast with the HAE and referred to as inverse HAE. Femtosecond and nanosecond transient absorption spectroscopy revealed overcompensation of a slight decrease in lifetime of the transition associated with the Au core (ps) by a large increase in the long-lived triplet state lifetime associated with the Au shell, which contributed to the observed inverse HAE. This unique observation of inverse HAE in gold nanoclusters provides the means to enhance the triplet excited state lifetime.

Abstract: Filamentous cable bacteria display long-range electron transport, generating electrical currents over centimeter distances through a highly ordered network of fibers embedded in their cell envelope. The conductivity of these periplasmic wires is exceptionally high for a biological material, but their chemical structure and underlying electron transport mechanism remain unresolved. Here, we combine high-resolution microscopy, spectroscopy, and chemical imaging on individual cable bacterium filaments to demonstrate that the periplasmic wires consist of a conductive protein core surrounded by an insulating protein shell layer. The core proteins contain a sulfur-ligated nickel cofactor, and conductivity decreases when nickel is oxidized or selectively removed. The involvement of nickel as the active metal in biological conduction is remarkable, and suggests a hitherto unknown form of electron transport that enables efficient conduction in centimeter-long protein structures.

Abstract: 3D real-space analysis of thick nanoparticle crystals is non-trivial. Here, the authors demonstrate the structural analysis of a bulk-like Laves phase by imaging an off-stoichiometric binary mixture of hard-sphere-like nanoparticles in spherical confinement by electron tomography, enabling defect analysis on the single-particle level. Assembling binary mixtures of nanoparticles into crystals, gives rise to collective properties depending on the crystal structure and the individual properties of both species. However, quantitative 3D real-space analysis of binary colloidal crystals with a thickness of more than 10 layers of particles has rarely been performed. Here we demonstrate that an excess of one species in the binary nanoparticle mixture suppresses the formation of icosahedral order in the self-assembly in droplets, allowing the study of bulk-like binary crystal structures with a spherical morphology also called supraparticles. As example of the approach, we show single-particle level analysis of over 50 layers of Laves phase binary crystals of hard-sphere-like nanoparticles using electron tomography. We observe a crystalline lattice composed of a random mixture of the Laves phases. The number ratio of the binary species in the crystal lattice matches that of a perfect Laves crystal. Our methodology can be applied to study the structure of a broad range of binary crystals, giving insights into the structure formation mechanisms and structure-property relations of nanomaterials.

Abstract: Direct experimental measurement of thermal expansion coefficient without substrate effects is a challenging task for two-dimensional (2D) materials, and its accurate estimation with large-scale ab initio molecular dynamics is computationally very expensive. Machine learning-based interatomic potentials trained with ab initio data have been successfully used in molecular dynamics simulations to decrease the computational cost without compromising the accuracy. In this study, we investigated using Gaussian approximation potentials to reproduce the density functional theory-level accuracy for graphene within both lattice dynamical and molecular dynamical methods, and to extend their applicability to larger length and time scales. Two such potentials are considered, GAP17 and GAP20. GAP17, which was trained with pristine graphene structures, is found to give closer results to density functional theory calculations at different scales. Further vibrational and structural analyses verify that the same conclusions can be deduced with density functional theory level in terms of the reasoning of the thermal expansion behavior, and the negative thermal expansion behavior is associated with long-range out-of-plane phonon vibrations. Thus, it is argued that the enabled larger system sizes by machine learning potentials may even enhance the accuracy compared to small-size-limited ab initio molecular dynamics.

Abstract: The manipulation of fast domain wall motion in magnetic nanostructures could form the basis of novel magnetic memory and logic devices. However, current approaches for reading and writing domain walls require external magnetic fields, or are based on conventional magnetic tunnel junctions (MTJs) that are not compatible with high-speed domain wall motion. Here we report domain wall devices based on perpendicular MTJs that offer electrical read and write, and fast domain wall motion via spin-orbit torque. The devices have a hybrid free layer design that consists of platinum/cobalt (Pt/Co) or a synthetic antiferromagnet (Pt/Co/Ru/Co) into the free layer of conventional MTJs. We show that our devices can achieve good tunnelling magnetoresistance readout and efficient spin-transfer torque writing that is comparable to current magnetic random-access memory technology, as well as domain wall depinning efficiency that is similar to stand-alone materials. We also show that a domain wall conduit based on a synthetic antiferromagnet offers the potential for reliable domain wall motion and faster write speed compared with a device based on Pt/Co. Domain wall devices based on perpendicular magnetic tunnel junctions with a hybrid free layer design can offer electrical read and write, and fast domain wall motion driven via spin-orbit torque.

Abstract: The adsorption of various environmental gas molecules, including H-2, N-2, CO, CO2, O-2, NO, NO2, SO2 H2O, H2S, NH3 and CH4, on the surface of the recently synthesized two dimensional MoSi2N4 (MSN) monolayer has been investigated by means of spin-polarized first-principles calculations. The most stable adsorption configuration, adsorption energy, and charge transfer have been computed. Due to the weak interaction between molecules studied with the MSN monolayer surface, the adsorption energy is small and does not yield any significant distortion of the MSN lattice, i.e., the interaction between the molecules and MSN monolayer surface is physisorption. We find that all molecules are physisorbed on the MSM surface with small charge transfer, acting as either charge acceptors or donors. The MSN monolayer is a semiconductor with an indirect band gap of 1.79 eV. Our theoretical estimations reveal that upon adsorption of H-2, N-2, CO, CO2, NO, H2O, H2S, NH3 and CH4 molecules, the semiconducting character of MSN monolayer is preserved and the band gap value is decreased to similar to 1.5 eV. However, the electronic properties of the MSN monolayer can be significantly altered by adsorption of O-2, NO and SO2, and a spin polarization with magnetic moments of 2, 1, 2 mu(B), respectively, can be introduced. Furthermore, we demonstrate that the band gap and the magnetic moment of adsorbed MSN monolayer can be significantly modulated by the concentration of NO and SO2 molecules. As the concentration of NO2 molecule increases, the magnetic moment increase from 1 mu(B) to 2 and 3 mu(B). In the case of the SO2 molecule with increasing of concentration, the band gap decreases from 1.2 eV to 1.1 and 0.9 eV. Obviously, our theoretical studies indicate that MSN monolayer-based sensor has a high application potential for O-2, NO, NO2 and SO2 detection.

Abstract: The (photo)catalytic properties of metal–organic frameworks (MOFs) can be enhanced by post-synthetic inclusion of metallic species in their porosity. Due to their extraordinarily high surface area and well defined porous structure, MOFs can be used for the stabilization of metal nanoparticles with adjustable size within their porosity. Originally, we present here an optimized ultrafast photoreduction protocol for the<italic>in situ</italic>synthesis of tiny and monodisperse silver nanoclusters (AgNCs) homogeneously supported on a photoactive porous titanium carboxylate MIL-125-NH₂MOF. The strong metal–framework interaction between –NH₂and Ag atoms influences the AgNC growth, leading to the surfactant-free efficient catalyst AgNC@MIL-125-NH₂with improved visible light absorption. The potential use of AgNC@MIL-125-NH₂was further tested in challenging applications: (i) the photodegradation of the emerging organic contaminants (EOCs) methylene blue (MB-dye) and sulfamethazine (SMT-antibiotic) in water treatment, and (ii) the catalytic hydrogenation of<italic>p</italic>-nitroaniline (4-NA) to<italic>p</italic>-phenylenediamine (PPD) with industrial interest. It is noteworthy that compared with the pristine MIL-125-NH₂, the composite presents an improved catalytic activity and stability, being able to photodegrade 92% of MB in 60 min and 96% of SMT in 30 min, and transform 100% of 4-NA to PPD in 30 min. Aside from these very good results, this study describes for the first time the use of a MOF in a visible light continuous flow reactor for wastewater treatment. With only 10 mg of AgNC@MIL-125-NH₂, high SMT removal efficiency over 70% is maintained after >2 h under water flow conditions found in real wastewater treatment plants, signaling a future real application of MOFs in water remediation.

Abstract: Metal-halide perovskites have rapidly emerged as one of the most promising materials of the 21st century, with many exciting properties and great potential for a broad range of applications, from photovoltaics to optoelectronics and photocatalysis. The ease with which metal-halide perovskites can be synthesized in the form of brightly luminescent colloidal nanocrystals, as well as their tunable and intriguing optical and electronic properties, has attracted researchers from different disciplines of science and technology. In the last few years, there has been a significant progress in the shape-controlled synthesis of perovskite nanocrystals and understanding of their properties and applications. In this comprehensive review, researchers having expertise in different fields (chemistry, physics, and device engineering) of metal-halide perovskite nanocrystals have joined together to provide a state of the art overview and future prospects of metal-halide perovskite nanocrystal research.

Abstract: The valuable properties of carbon steel slag are currently underexploited. To date, research mainly focusses on valorising a single property of the slag. In this study an ex-ante life cycle assessment (LCA) was applied to evaluate the environmental profile of a novel technological pathway aimed at the extraction of chromium from carbon steel slag in combination with high quality valorisation of the residual matrix material. A comparison with current practice was made, not only by calculating the environmental impact of the lab scale observations, but more importantly by estimating the impact on an industrial scale. Practical guidance on ex-ante LCA is limited, so this study contributes by incorporating simulations on thermodynamic behaviour, complemented with empirical calculation rules and including information derived from similar technologies to perform the upscaling. These principles of ex-ante LCA were applied to the lab results of two consecutive research iterations. Substantial improvements of the environmental profile were observed: ex-ante results turned out to be a factor 20 lower compared to the results from the lab observations after the first iteration and had decreased by a factor 2 compared to the small pilot scale of the second iteration. All upscaled results are better than those from the worst case reference scenario (landfill). Based on the experience gained after this iterative research cycle, a practical recommendation is that at a low technology readiness level using more simple calculation rules in combination with a flowsheet based on elementary design principles for processes at an industrial scale is a more efficient way of modelling compared to a fully-fledged process design from the start.

Abstract: Bridging the gap between complex signal data output and clear interpretation by non-expert end-users is a major challenge many scientists face when converting their scientific technology into a real-life application. Currently, pattern recognition algorithms are the most frequently encountered signal data interpretation algorithms to close this gap, not in the least because of their straight-forward implementation via convenient software packages. Paradoxically, just because their implementation is so straight-forward, it becomes cumbersome to integrate the expert's domain-specific knowledge. In this work, a novel signal data interpretation approach is presented that uses this domain-specific knowledge as its fundament, thereby fully exploiting the unique expertise of the scientist. The new approach applies data preprocessing in an innovative way that transcends its usual purpose and is easy to translate into a software application. Multiple case studies illustrate the straight-forward application of the novel approach. Ultimately, the approach is highly suited for integration in various (bio)analytical applications that require interpretation of signal data.