Abstract: Interface engineering in complex oxide superlattices is a growing field, enabling manipulation of the exceptional properties of these materials, and also providing access to new phases and emergent physical phenomena. Here we demonstrate how interfacial interactions can induce a complex charge and spin structure in a bulk paramagnetic material. We investigate a superlattice (SLs) consisting of paramagnetic LaNiO3 (LNO) and highly spin-polarized ferromagnetic La2/3Ca1/3MnO3 (LCMO), grown on SrTiO3 (001) substrate. We observed emerging magnetism in LNO through an exchange bias mechanism at the interfaces in X-ray resonant magnetic reflectivity. We find non-symmetric interface induced magnetization profiles in LNO and LCMO which we relate to a periodic complex charge and spin superstructure. High resolution scanning transmission electron microscopy images reveal that the upper and lower interfaces exhibit no significant structural variations. The different long range magnetic order emerging in LNO layers demonstrates the enormous potential of interfacial reconstruction as a tool for tailored electronic properties.

Abstract: Pretreatment is crucial for the conversion of lignocellulose to biofuels. Unlike conventional chemical/physicochemical methods, fungal pretreatment uses white-rot fungi and mild reaction conditions. However, challenges, including substrate sterilization, long duration, and low sugar yields associated with this method, contribute to lower techno-economic performance, an aspect that has rarely been investigated. This study aimed to evaluate the feasibility of fungal pretreatment of nonsterilized poplar wood. Various factors, including inoculum types, fermentation supplements, and cultivation methods, were investigated to optimize the process. A techno-economic assessment of the optimized processes was performed at a full biorefinery scale. The scenario using nonsterilized wood as a substrate, precolonized wood as an inoculum, and a 4 week pretreatment showed a 14.5% reduction in sugar production costs (€2.15/kg) compared to using sterilized wood. Although the evaluation of nonsterilized wood pretreatment showed promising cost reductions, fungal pretreatment remained more expensive than conventional methods due to the significant capital investment required.

Abstract: A facile, “one-pot”, chemical approach to synthesize gold-based nanoparticles finely dispersed on porous activated carbon (Norit) was demonstrated in this work. The pH of the synthesis bath played a critical role in determining the optimal gold-carbon interaction, which enabled a successful deposition of the gold nanoparticles onto the carbon matrix with a maximized metal utilization of 93 %. The obtained AuNP/C nanocomposite was characterized using SEM, HAADF-STEM electron tomography and electrochemical techniques. It was found that the Au nanoparticles, with diameters between 5 and 20 nm, were evenly distributed over the carbon matrix, both inside and outside the pores. Electrochemical characterization indicated that the composite had a very large electroactive surface area (EASA), as high as 282.4 m2 gAu-1. By exploiting its very high EASA, the catalyst was intended to boost the productivity of glucaric acid in the electrooxidation of its precursor, gluconic acid. However, cyclic voltammetry experiments revealed a very limited reactivity towards gluconic acid oxidation, due to the spacial hindrance of gluconic acid molecule which prevented diffusion inside the catalyst nanopores. On the other hand, the as-synthesized nanocomposite promises to be effective towards the ORR, and might thus find potential application as anode catalyst for fuel cells as well as for the scalability of all those electrochemical reactions involving small molecules with high diffusivity and catalysed by noble metals (i. e. CO2, CH4, N2, etc..). Electrocatalysis: Gold nanoparticles with diameter between 5 and 20 nm evenly distributed onto porous activated carbon (Norit) were obtained using a facile “one-pot” chemical synthesis technique with very high metal utilization. The AuNP/C nanocomposite was characterized using SEM, HAADF-STEM electron tomography and electrochemical techniques, revealing a very large electroactive surface area (EASA). The figure shows the HAADF-STEM image (a) and the respective EDX elemental distribution (b) for the AuNP/C composite with 9.3 % Au-loading developed in this work (Au is marked in red and C in green).image

Abstract: A portable and highly sensitive sensor was designed for the specific detection of 3,4-methyl-enedioxy-methamphetamine (MDMA), in a range of field-testing situations. The sensor can detect MDMA in street samples, even when other controlled substances drugs, or adulterants are present. In this work, we report for the first time a sensor using electroactive molecularly imprinted polymer nanoparticles computationally designed to recognize MDMA and then produced using solid phase synthesis. A composite comprising chitosan, reduced graphene oxide, and molecularly imprinted polymer nanoparticles synthesized for MDMA for the first time was immobilized on screen-printed carbon electrodes. The sensors displayed a satisfactory sensitivity (106.8 nA x mu M-1), limit of detection (1.6 nM; 0.31 ng/mL), and recoveries (92-99%). The accuracy of the results was confirmed through validation using Ultra-High Performance Liquid Chromatography coupled with tandem Mass Spectrometry (UPLC-MS/MS). This technology could be used in forensic analysis and make it possible to selectively detect MDMA in street samples. A highly sensitive and portable sensor has been developed to detect MDMA in street samples. It uses electroactive molecularly imprinted polymer nanoparticles computationally designed to recognize MDMA, which were immobilized on screen-printed carbon electrodes with chitosan and graphene. The sensor showed good sensitivity and satisfactory recoveries (92-99%), confirmed with UPLC-MS/MS validation. This technology has the potential to be used in forensic analysis.image

Abstract: This study examines five benzyl alcohol derivatives and three chemically similar compounds and compares them against benzyl alcohol in gelled emulsions for the removal of overpaint during cleaning of oil paintings. Comparative cleaning tests using xanthan gels, Pemulen® TR-2 gels, and neat solvent were made on overpaint on fragments of a seventeenth-century test painting. This approach demonstrated that molecular changes to a benzyl alcohol core resulted in enhanced control during the cleaning process. In some cases a benzyl alcohol derivative enabled selective removal of non-original material, when benzyl alcohol appeared to affect the original paint. Select derivatives were also tested in an area of overpaint on a sixteenth-century oil on panel painting by Jan van Scorel in the Rijksmuseum Collection through modifying the chemical activity of benzyl alcohol. Finally, two GC-MS-based methods were used to monitor benzyl alcohol retention and possible oxidation in paint layers post-treatment.

Abstract: Gian Giacomo Inchiocchio (1604-1656), better known as Barbelli, was one of the main exponents of Lombard painting of the seventeenth century. A large body of work is attributed to him, encompassing a wide range of drawings, murals, and oil paintings. However, despite his broad production, there are still many open questions regarding his painting techniques and materials. In this paper, a multi-analytical study of the cycle Stories of the life of Saint George that originally decorated the presbytery of the parish church of Casaletto Vaprio (Cremona, Italy) was performed, combining non-invasive techniques with the characterisation of selected micro samples. Results show that Barbelli used a very limited number of inorganic pigments, often mixing them together to create different colours and shades. Remains of caseinate and degradation products (i.e. weddellite and whewellite) related to the strappo intervention were also highlighted. The study helped to decipher the materials and technique of this painting, providing data that can be used as a reference to study his extensive production.

Abstract: Mixed-halide perovskites show promising applications in tandem solar cells owing to their adjustable bandgap. One major obstacle to their commercialization is halide phase segregation, which results in large open-circuit voltage deficiency and J-V hysteresis. However, the ambiguous interplay between structural origin and phase segregation often results in aimless and unspecific optimization strategies for the device's performance and stability. An atomic scale is directly figured out the abundant Ruddlesden-Popper anti-phase boundaries (RP-APBs) within a CsPbIBr2 polycrystalline film and revealed that phase segregation predominantly occurs at RP-APB-enriched interfaces due to the defect-mediated lattice strain. By compensating their structural lead halide, such RP-APBs are eliminated, and the decreasing of strain can be observed, resulting in the suppression of halide phase segregation. The present work provides the deciphering to precisely regulate the perovskite atomic structure for achieving photo-stable mixed halide wide-bandgap perovskites of high-efficiency tandem solar cell commercial applications. The phase segregation in mixed halide perovskite film predominantly occurs at Ruddlesden-Popper anti-phase boundaries (RP-APBs)-enriched interfaces due to the defect-mediated lattice strain. The RP-APBs defects can be eliminated by compensating for their structural lead halide deficiency, resulting in the suppression of halide phase segregation. image

Abstract: Coupling photosensitizers (PSs) with plasmonic nanoparticles increases the photocatalytic activity of PSs as the localized surface plasmon resonance (LSPR) of plasmonic nanoparticles leads to extreme concentration of light in their vicinity known as the near-field enhancement effect. To realize this in a colloidal phase, efficient conjugation of the PS molecules with the plasmonic nanoparticle surface is critical. In this work, we demonstrate the coupling of phthalocyanine (Pc) molecules with gold nanoparticles (AuNPs) in the colloidal phase via click chemistry. This conjugated Pc-AuNPs colloidal system is shown to enhance the photocatalytic singlet oxygen (1O2) production over non-conjugated Pcs and hence improve the photoelectrochemical detection of phenols. The plasmonic enhancement of the 1O2 generation by Pcs was clearly elucidated by complementary experimental and computational classical electromagnetic models. The dependence of plasmonic enhancement on the spectral position of the excitation laser wavelength and the absorbance of the Pc molecules with respect to the wavelength specific near-field enhancement is clearly demonstrated. A high similar to 8 times enhancement is obtained with green laser (532 nm) at the LSPR due to the maximum near-field enhancement at the resonance wavelength. Zinc phthalocyanine is covalently linked to plasmonic AuNPs via click chemistry to investigate the synergistic effect that boosts the overall activity toward the detection of HQ under visible light illumination. The 1O2 quantum yield of ZnPc improved significantly after conjugating with AuNPs, resulting in enhanced photoelectrochemical activity. image

Abstract: Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic-resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state-of-the-art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark-field scanning transmission electron microscopy enables the acquisition of ten high-resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allow resolving the real-time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions. Experimental and computational techniques are bridged to unveil atomic dynamics in gold nanoparticles (NPs), using annular dark-field scanning transmission electron microscopy and molecular dynamics simulations informed by machine learning. The approach provides unprecedented insights into the real-time structural behaviors of NPs, merging state-of-the-art techniques to accurately characterize their dynamics under realistic conditions. image

Abstract: Plasma medicine has attracted tremendous interest in a variety of medical conditions, ranging from wound healing to antimicrobial applications, even in cancer treatment, through the interactions of cold atmospheric plasma (CAP) and various biological tissues directly or indirectly. The underlying mechanisms of CAP treatment are still poorly understood although the oxidative effects of CAP with amino acids, peptides, and proteins have been explored experimentally. In this study, machine learning (ML) technology is introduced to efficiently unveil the interaction mechanisms of amino acids and reactive oxygen species (ROS) in seconds based on the data obtained from the reactive molecular dynamics (MD) simulations, which are performed to probe the interaction of five types of amino acids with various ROS on the timescale of hundreds of picoseconds but with the huge computational load of several days. The oxidative reactions typically start with H-abstraction, and the details of the breaking and formation of chemical bonds are revealed; the modification types, such as nitrosylation, hydroxylation, and carbonylation, can be observed. The dose effects of ROS are also investigated by varying the number of ROS in the simulation box, indicating agreement with the experimental observation. To overcome the limits of timescales and the size of molecular systems in reactive MD simulations, a deep neural network (DNN) with five hidden layers is constructed according to the reaction data and employed to predict the type of oxidative modification and the probability of occurrence only in seconds as the dose of ROS varies. The well-trained DNN can effectively and accurately predict the oxidative processes and productions, which greatly improves the computational efficiency by almost ten orders of magnitude compared with the reactive MD simulation. This study shows the great potential of ML technology to efficiently unveil the underpinning mechanisms in plasma medicine based on the data from reactive MD simulations or experimental measurements. In this study, since reactive molecular dynamics simulation can currently only describe interactions between a few hundred atoms in a few hundred picoseconds, deep neural networks (DNN) are introduced to enhance the simulation results by predicting more data efficiently. image

Abstract: Farmers should increasingly adopt more water‐efficient irrigation technologies—such as drip irrigation—as a result of climate warming and aggravating water scarcity. We analyze how Italian farmers adapt to climate change by changing their irrigation technology mix. We apply a two‐stage econometric model to data from 5876 Italian farms. We find that farmers' initial reaction to increasing temperatures is reducing their surface‐irrigated fractions. When temperatures increase further, farmers switch toward more sprinkler irrigation. Our results show that farmers are not autonomously moving to drip irrigation in response to climate change, suggesting that government incentives are needed to encourage this transition.

Abstract: New Cinema History broadened film studies by emphasising the complexity of cinema as a multifaceted phenomenon that includes the socio-economic context in which films were made, circulated, shown and received. As part of the digital turn, the discipline adopted computational methods and created quantitative research data to research this socio-economic context at scale. However, not all datasets created in this context adhere to FAIR principles, decreasing their reusability. By reconciling 14 cinema-related datasets, Cinema Belgica facilitates research into the history of Belgian cinema. This research paper documents and critically reflects on the choices made when selecting, modelling and reconciling information for the Cinema Belgica database.

Abstract: This study introduces solid-state tuning of a mesostructured cellular foam (MCF) to enhance hydrogen (H-2) storage in clathrate hydrates. Grafting of promoter-like molecules (e.g., tetrahydrofuran) at the internal surface of the MCF resulted in a substantial improvement in the kinetics of formation of binary H-2-THF clathrate hydrate. Identification of the confined hydrate as sII clathrate hydrate and enclathration of H-2 in its small cages was performed using XRD and high-pressure H-1 NMR spectroscopy respectively. Experimental findings show that modified MCF materials exhibit a similar to 1.3 times higher H-2 storage capacity as compared to non-modified MCF under the same conditions (7 MPa, 265 K, 100% pore volume saturation with a 5.56 mol% THF solution). The enhancement in H-2 storage is attributed to the hydrophobicity originating from grafting organic molecules onto pristine MCF, thereby influencing water interactions and fostering an environment conducive to H-2 enclathration. Gas uptake curves indicate an optimal tuning point for higher H-2 storage, favoring a lower density of carbon per nm(2). Furthermore, a direct correlation emerges between higher driving forces and increased H-2 storage capacity, culminating at 0.52 wt% (46.77 mmoles of H-2 per mole of H2O and 39.78% water-to-hydrate conversions) at 262 K for the modified MCF material with fewer carbons per nm(2). Notably, the substantial H-2 storage capacity achieved without energy-intensive processes underscores solid-state tuning's potential for H-2 storage in the synthesized hydrates. This study evaluated two distinct kinetic models to describe hydrate growth in MCF. The multistage kinetic model showed better predictive capabilities for experimental data and maintained a low average absolute deviation. This research provides valuable insights into augmenting H-2 storage capabilities and holds promising implications for future advancements.

Abstract: Appropriate use of agricultural technologies and diversifying the farming activities is critical to addressing food security problems in Africa, including Ethiopia. The country is experimenting with the new Agricultural Innovation System (AIS) approach alongside the well-established Transfer of Technology (ToT) approach. This paper analyzes the gaps between policy discourses (as reflected in policy documents and strategic orientation documents) and extension practices (as reflected in the daily exchanges between farmers and the frontline staff of the Ethiopian extension system). It provides insights into the challenges faced and emphasizes the need for better coordination between policy formulation and implementation to enhance extension services. Policymakers, practitioners, and researchers can benefit from the valuable perspectives the findings offer. The study contributes to understanding the relationship between policy discourses and extension practices, and its implications can inform policy design and implementation in similar contexts. A qualitative research approach was deployed to analyze policy discourse and practice. Data were collected in Fogera, a district in Northwest Ethiopia, between August 2018 and February 2019. The data for the paper were obtained from 23 Focus Group Discussions conducted with men and women. 13 Informant Interviews (KIIs) were also carried out with personnel at different levels of government agricultural services and departments. Transcripts of recordings of the Focus Group Discussions (FGDs) and Key Informant Interviews (KIIs) were analyzed using a deductive approach. The study focuses on rice crops in the Fogera district, which are crucial for food security and reducing poverty. Although the geographic area is limited, the results can be used to improve the extension system in other areas facing similar challenges. Specifically, the study suggests switching from the traditional transfer of technology approach to the agricultural innovation system approach. Furthermore, the study's techniques, such as qualitative interviews, may have limitations and not fully capture the intricacies of policy and extension practices. The findings demonstrate that, although the policy documents strongly adhere to agricultural innovation system principles, top-down transfer of technology approaches continues to dominate in practice. Moreover, we have found potential discrepancies between the training content delivered and the specific needs of smallholder farmers. Practically, prescriptive systems are still used because agricultural innovation system approaches are not well understood by the Extension Agents. To realize a genuine agricultural innovation system, Ethiopia's extension apparatus should move forward with building committed and robust relationships between farmers, extension agents, researchers, private sectors, and non-governmental organizations. To this end, more research, enhanced training, and improved institutions are needed on what genuine agricultural innovation system could look like at the grass-roots level. This also includes understanding the roles that different actors within Ethiopia's development army should assume how a multi-actor policy dialogue can be organized.

Abstract: Previous reports on Poisson-Nernst-Planck (PNP) simulations of solid-state nanopores have focused on steady state behaviour under simplified boundary conditions. These are Neumann boundary conditions for the voltage at the pore walls, and in some cases also Donnan equilibrium boundary conditions for concentrations and voltages at both entrances of the nanopore. In this paper, we report time-dependent and steady state PNP simulations under less restrictive boundary conditions, including Neumann boundary conditions applied throughout the membrane relatively far away from the nanopore. We simulated ion currents through cylindrical and conical nanopores with several surface charge configurations, studying the spatial and temporal dependence of the currents contributed by each ion species. This revealed that, due to slow co-diffusion of oppositely charged ions, steady state is generally not reached in simulations or in practice. Furthermore, it is shown that ion concentration polarization is responsible for the observed limiting conductances and ion current rectification in nanopores with asymmetric surface charges or shapes. Hence, after more than a decade of collective research attempting to understand the nature of ion current rectification in solid-state nanopores, a relatively intuitive model is retrieved. Moreover, we measured and simulated current-voltage characteristics of rectifying silicon nitride nanopores presenting overlimiting conductances. The similarity between measurement and simulation shows that overlimiting conductances can result from the increased conductance of the electric double-layer at the membrane surface at the depletion side due to voltage-induced polarization charges.