Abstract: (Sun)Light is an abundantly available sustainable source of energy that has been used in catalyzing chemical reactions for several decades now. In particular, studies related to the interaction of light with plasmonic nanostructures have been receiving increased attention. These structures display the unique property of localized surface plasmon resonance, which converts light of a specific wavelength range into hot charge carriers, along with strong local electromagnetic fields, and/or heat, which may all enhance the reaction efficiency in their own way. These unique properties of plasmonic nanoparticles can be conveniently tuned by varying the metal type, size, shape, and dielectric environment, thus prompting a research focus on rationally designed plasmonic hybrid nanostructures. In this review, the term “hybrid” implies nanomaterials that consist of multiple plasmonic or non-plasmonic materials, forming complex configurations in the geometry and/or at the atomic level. We discuss the synthetic techniques and evolution of such hybrid plasmonic nanostructures giving rise to a wide variety of material and geometric configurations. Bimetallic alloys, which result in a new set of opto-physical parameters, are compared with core–shell configurations. For the latter, the use of metal, semiconductor, and polymer shells is reviewed. Also, more complex structures such as Janus and antenna reactor composites are discussed. This review further summarizes the studies exploiting plasmonic hybrids to elucidate the plasmonic-photocatalytic mechanism. Finally, we review the implementation of these plasmonic hybrids in different photocatalytic application domains such as H2 generation, CO2 reduction, water purification, air purification, and disinfection.

Abstract: Many geometries of plant organs can be described by the Gielis equation, a polar coordinate equation extended from the superellipse equation, . Here, r is the polar radius corresponding to the polar angle φ; m is a positive integer that determines the number of angles of the Gielis curve when φ ∈ [0 to 2π); and the rest of the symbols are parameters to be estimated. The pentagonal radial symmetry of calyxes and corolla tubes in top view is a common feature in the flowers of many eudicots. However, prior studies have not tested whether the Gielis equation can depict the shapes of corolla tubes. We sampled randomly 366 flowers of Vinca major L., among which 360 had five petals and pentagonal corolla tubes, and six had four petals and quadrangular corolla tubes. We extracted the planar coordinates of the outer rims of corolla tubes (in top view) (ORCTs), and then fitted the data with two simplified versions of the Gielis equation with k = 1 and m = 5: (Model 1), and (Model 2). The adjusted root mean square error (RMSEadj) was used to evaluate the goodness of fit of each model. In addition, to test whether ORCTs are radially symmetrical, we correlated the estimates of n2 and n3 in Model 1 on a log-log scale. The results validated the two simplified Gielis equations. The RMSEadj values for all corolla tubes were smaller than 0.05 for both models. The numerical values of n2 and n3 were demonstrated to be statistically equal based on the regression analysis, which suggested that the ORCTs of V. major are radially symmetrical. It suggests that Model 1 can be replaced by the simpler Model 2 for fitting the ORCT in this species. This work indicates that the pentagonal or quadrangular corolla tubes (in top view) can both be modeled by the Gielis equation and demonstrates that the pentagonal or quadrangular corolla tubes of plants tend to form radial symmetrical geometries during their development and growth.

Abstract: Phenols are considered as toxic pollutants and their discharge into the environment by industries is regulated by a concentration limit. As these limits are in the low mg L−1 to µg L−1-range, sensitive methods are necessary to detect these phenols. Here, aqueous industrial phenolic samples throughout a cleaning process were analyzed by two novel electrochemical sensors. Both the photoelectrochemical (PEC) sensor and the square wave voltammetric (SWV) sensor could successfully follow the decrease of the concentration of phenols along the industrial cleaning process. The discharge sample (μg L−1) could only be analyzed by the PEC sensor and not by the SWV sensor, as the phenolic concentration was close to the LOD of the latter. With HPLC-diode array detector (DAD) measurements, classical phenols such as phenol (PHOH), hydroquinone, resorcinol and o-cresol could be identified in the industrial samples, and their presence could be linked to the electrochemical responses. At last, the performance of the PEC and SWV sensors were compared with commercial colorimetric and chemical oxygen demand (COD) test kits. This comparison demonstrated the high sensitivity of the PEC sensor in the μg L−1 concentrated phenolic samples. Together with the identification of the redox peaks through HPLC-DAD analysis, the SWV sensor can be a powerful tool in the qualitative analysis of mg L−1 concentrated phenolic samples due to its speed, simplicity and absence of laborious sample pre-treatment steps.

Abstract: Atomic layer deposition (ALD) typically employs metal precursors and co-reactant pulses to deposit thin films in a layer-by-layer fashion. While conventional ABAB-type ALD sequences implement only two functionalities, namely, a metal source and ligand exchange agent, additional functionalities have emerged, including etching and reduction agents. Herein, we construct gas-phase sequences-coined as ALD+-with complex-ities reaching beyond the classic ABAB-type ALD by freely combining multiple functionalities within irregular pulse schemes, e.g., ABCADC. The possibilities of such combinations are explored as a smart strategy to tailor bimetallic thin films and nanoparticle (NP) properties. By doing so, we demonstrate that bimetallic thin films can be tailored with target thickness and through the full compositional range, while the morphology can be flexibly modulated from thin films to NPs by shuI 1ing the pulse sequence. These complex pulse schemes are expected to be broadly applicable but are here explored for Pd-Ru bimetallic thin films and NPs.

Abstract: According to the World Health Organization, about 422 million people worldwide have diabetes, with 1.5 million deaths directly attributed each year. Therefore, there is still a need to effectively monitor glucose in diabetic patients for proper management. Recently, wearable patches based on microneedle (MN) sensors provide minimally invasive analysis of glucose through the interstitial fluid (ISF) while exhibiting excellent correlation with blood glucose. Despite many advances in wearable electrochemical sensors, long-term stability and continuous monitoring remain unsolved challenges. Herein, we present a highly stable electrochemical biosensor based on a redox mediator bilayer consisting of Prussian blue and iron-nickel hexacyanoferrate to increase the long-term stability of the readout coupled with a hollow MN array as a sampling unit for ISF uptake. First, the enzymatic biosensor is developed by using affordable screen-printed electrodes (SPE) and optimized for long-term stability fitting the physiological range of glucose in ISF (i.e., 2.5–22.5 mM). In parallel, the MN array is assessed for minimally invasive piercing of the skin. Subsequently, the biosensor is integrated with the MN array leaving a microfluidic spacer that works as the electrochemical cell. Interestingly, a microfluidic channel connects the cell with an external syringe to actively and rapidly withdraw ISF toward the cell. Finally, the robust MN sensing patch is characterized during in vitro and ex vivo tests. Overall, affordable wearable MN-based patches for the continuous monitoring of glucose in ISF are providing an advent in wearable devices for rapid and life-threatening decision-making processes.

Abstract: Two electrochemical methodologies, i.e. flowchart and dual-sensor, were developed to aid law enforcement present at festivals to obtain a rapid indication of the presence of four illicit drugs in suspicious samples encountered.

Abstract: Artificial photosynthesis of H2O2, an environmentally friendly oxidant and a clean fuel, holds great promise. However, improving its efficiency and stability for industrial implementation remains highly challenging. Here, we report the visible-light H2O2 artificial photosynthesis by digging pro-superoxide radical carbon vacancies in three-dimensional hierarchical porous g-C3N4 through a simple hydrolysis-freeze-drying-thermal treatment. A significant electronic structure change is revealed upon the implantation of carbon vacancies, broadening visible-light absorption and facilitating the photogenerated charge separation. The strong electron affinity of the carbon vacancies promotes superoxide radical (O-center dot(2)-) formation, significantly boosting the H2O2 photocatalytic production. The developed photocatalyst shows an H2O2 evolution rate of 6287.5 mM g(-1) h(-1) under visible-light irradiation with a long cycling stability being the best-performing photocatalyst among all reported g-C3N4-based systems. Our work provides fundamental insight into highly active and stable photocatalysts with great potential for safe industrial H2O2 production.

Abstract: In this work, the absorption–desorption performance of CO2 in six new solvent blends of amine (diisopropylamine (DPA), 2-amino-2-methyl-1-propanol (AMP), methyldiethanolamine (MDEA), diethanolamine (DEA), diisopropanolamine (DIPA), and ethanolamine (MEA)), sulfolane, and methanol has been monitored using ATR-FTIR spectroscopy. Additionally, NMR-based species confirmation and solvent viscosity analysis were done for DPA solvent samples. The identified CO2 capture products are monomethyl carbonate (MMC), carbamate, carbonate, and bicarbonate anions in different ratios. The DPA solvent formed MMC entirely with 0.88 molCO2/molamine capture capacity, 0.48 molCO2/molamine cyclic capacity, and 3.28 mPa·s CO2-loaded solvent viscosity. MEA, DEA, DIPA, and MDEA were shown to produce a low or a negligible amount of MMC while AMP occupied an intermediate position.

Abstract: Supershapes are used in Parametric Design to model, literally, thou-sands of natural and man-made shapes with a single 6 parameter formula. However, users are left to probe such a rich yet dense collection of supershapes using a set of independent 1-D sliders. Some of the formula’s parameters are non-linear in nature, making them particularly difficult to grasp with conventional 1-D sliders alone. VR appears as a promising setting for Parametric Design with supershapes since it empowers users with more natural visual inspection and shape browsing techniques, with multiple solutions being displayed at once and the possibility to design more interesting forms of slider interaction. In this work, we propose VR shape widgets that allow users to probe and select supershapes from a multitude of solutions. Our designs take leverage on thumbnails, mini-maps, haptic feedback and spatial interaction, while supporting 1-D, 2-D and 3-D supershape parameter spaces. We conducted a user study (N = 18) and found that VR shape widgets are effective, more efficient, and natural than conventional VR 1-D sliders while also usable for users without prior knowledge on supershapes. We also found that the proposed VR widgets provide a quick overview of the main supershapes, and users can easily reach the desired solution without having to perform fine-grain handle manipulations.

Abstract: There is an urgent need for sensing strategies to screen perfluoroalkyl substances (PFAS) in aqueous matrices. These strategies must be applicable in large-scale monitoring plans to face the ubiquitous use of PFAS, their wide global spread, and their fast evolution towards short-chain, branched molecules. To this aim, the changes in fluorinated self-assembled monolayers (SAM) with different architectures (pinholes/defects-free and with randomized pinholes/defects) were studied upon exposure to both long and short-chain PFAS. The applicability of fluorinated SAM in PFAS sensing was evaluated. Changes in the SAM structures were characterised combining electrochemical impedance spectroscopy and voltam-metric techniques. The experimental data interpretation was supported by molecular dynamics simu-lations to gain a more in-depth understanding of the interaction mechanisms involved. Pinhole/defect-free fluorinated SAM were found to be applicable to long-chain PFAS screening within switch-on sensing strategy, while a switch-off sensing strategy was reported for screening of both short/long-chain PFAS. These strategies confirmed the possibility to play on fluorophilic interactions when designing PFAS screening methods.(c) 2022 Elsevier B.V. All rights reserved.

Abstract: Enhancing aluminium interaction with graphene-based materials is of crucial importance for the development of Al-storage materials and novel functional materials via atomically precise doping. Here, DFT calculations are employed to investigate Al interactions with non-doped and N-doped graphene nanoribbons (GNRs) and address the impact of the edge sites and N-containing defects on the material's reactivity towards Al. The presence of edges does not influence the energetics of Al adsorption significantly (compared to pristine graphene sheet). On the other hand, N-doping of graphene nanoribbons is found to affect the adsorption energy of Al to an extent that strongly depends on the type of N-containing defect. The introduction of edge-NO group and doping with in -plane pyridinic N result in Al adsorption nearly twice as strong as on pristine graphene. Moreover, double n-type doping via N and Al significantly alters the electronic structure of Al,N-containing GNRs. Our results suggest that selectively doped GNRs with pyridinic N can have enhanced Al-storage capacity and could be potentially used for selective Al electrosorption and removal. On the other hand, Al,N-containing GNRs with pyridinic N could also be used in resistive sensors for mechanical deformation. Namely, strain along the longitudinal axis of these dual doped GNRs does not affect the binding of Al but tunes the bandgap and causes more than 700-fold change in the conductivity. Thus, careful defect engineering and selective doping of GNRs with N (and Al) could lead to novel multifunctional materials with exceptional properties. [GRAPHICS]

Abstract: Most farm adaptations are reactive actions that run the risk of locking farm systems into suboptimal long-term trajectories. This is especially the case with regard to water management as water scarcity will be aggravated by climate change. This paper looks into farm irrigation choices in combination with crop choices because a proper crop choice has the potential to reduce water requirements. It proposes an extended Ricardian model to capture multiple adaptation decisions explicitly. The new simultaneous irrigation-crop farm decision model uses spatially detailed farm-level data of over 18,000 European farms on irrigation and seven different crop choices. The analysis shows that larger farmers and farmers in less water-scarce regions that use irrigation are more sensitive to temperature increases than rain-fed agriculture. This might be explained by the fact that these farmers do not experience the real cost of water scarcity because of which they take less efficient decisions.

Abstract: Formation and aggregation of metal carboxylates (metal soaps) can degrade the appearance and integrity of oil paints, challenging efforts to conserve painted works of art. Endeavors to understand the root cause of metal soap formation have been hampered by the limited spatial resolution of Fourier transform infrared microscopy (mu-FTIR). We overcome this limitation using optical photothermal infrared spectroscopy (O-PTIR) and photothermal-induced resonance (PTIR), two novel methods that provide IR spectra with approximate to 500 and approximate to 10 nm spatial resolutions, respectively. The distribution of chemical phases in thin sections from the top layer of a 19th-century painting is investigated at multiple scales (mu-FTIR approximate to 10(2) mu m(3), O-PTIR approximate to 10(-1) mu m(3), PTIR approximate to 10(-5) mu m(3)). The paint samples analyzed here are found to be mixtures of pigments (cobalt green, lead white), cured oil, and a rich array of intermixed, small (often << 0.1 mu m(3)) zinc soap domains. We identify Zn stearate and Zn oleate crystalline soaps with characteristic narrow IR peaks (approximate to 1530-1558 cm(-1)) and a heterogeneous, disordered, water-permeable, tetrahedral zinc soap phase, with a characteristic broad peak centered at approximate to 1596 cm(-1). We show that the high signal-to-noise ratio and spatial resolution afforded by O-PTIR are ideal for identifying phase-separated (or locally concentrated) species with low average concentration, while PTIR provides an unprecedented nanoscale view of distributions and associations of species in paint. This newly accessible nanocompositional information will advance our knowledge of chemical processes in oil paint and will stimulate new art conservation practices.

Abstract: In the present work, the resolution and quantification of mixtures of different opiate compounds in the presence of common cutting agents using an electronic tongue (ET) is evaluated. More specifically, ternary mixtures of heroin, morphine and codeine were resolved in the presence of caffeine and paracetamol. To this aim, an array of three carbon screen-printed electrodes were modified with different ink-like solutions of graphite, cobalt (II) phthalocyanine and palladium, and their responses towards the different drugs were characterized by means of square wave voltammetry (SWV). Developed sensors showed a good performance with good linearity at the mu M level, LODs between 1.8 and 5.3 mu M for the 3 actual drugs, and relative standard deviation (RSD) ca. 2% for over 50 consecutive measurements. Next, a quantitative model that allowed the identification and quantification of the individual substances from the overlapped voltammograms was built using partial least squares regression (PLS) as the modeling tool. With this approach, quantification of the different drugs was achieved at the mu M level, with a total normalized root mean square error (NRMSE) of 0.084 for the test subset.