Abstract: Oxygen loss is a serious problem of lithium-rich layered oxide (LLO) cathodes, as the high capacity of LLO relies on reversible oxygen redox. Oxygen release can occur at the surface leading to the formation of spinel or rock salt structures. Also, the lattice oxygen will usually become unstable after long cycling, which remains a major roadblock in the application of LLO. Here, it is shown that Zr doping is an effective strategy to retain lattice oxygen in LLO due to the high affinity between Zr and O. A simple sol-gel method is used to dope Zr4+ into the LLOs to adjust the local electronic structure and inhibit the diffusion of oxygen anions to the surface during cycling. Compared with untreated LLOs, LLO-Zr cathodes exhibit a higher cycling stability, with 94% capacity retention after 100 cycles at 0.4 C, up to 223 mAh g-1 at 1 C, and 88% capacity retention after 300 cycles. Theoretical calculations show that due to the strong Zr-O covalent bonding, the formation energy of oxygen vacancies has effectively increased and the loss of lattice oxygen under high voltage can be suppressed. This study provides a simple method for developing high-capacity and cyclability Li-rich cathode materials for lithium-ion batteries. Oxygen release can occur at the cathode surface leading to the formation of spinel or rock salt structures. Here, it is shown that Zr doping is an effective strategy to retain lattice oxygen in lithium-rich layered oxides (LLO) due to the high affinity between Zr and O. LLO-Zr exhibit higher cycling stability, with 88% capacity retention after 300 cycles at 1 C. 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: The increasing availability of real-time in situ measurements and remote sensing observations have the potential to contribute to the optimization of water resources management. Global challenges such as climate change, intensive agriculture and urbanization put a high pressure on our water resources. Due to recent innovations in measuring both water quantity and quality, river systems can now be monitored in real time at an unprecedented spatial and temporal scale. To interpret the sensor measurements and remote sensing observations additional data for example on: the location of the measurement, upstream and downstream catchment characteristics, horizontal ellipsis are required. In this paper, we present a data management system to support flow-path related functionality for decision making and prediction modelling. Adding meta data sets and facilitating (near) real-time processing of sensor data questions are key concepts for the systems. The potential of the database framework for hydrological applications is demonstrated using different applications for the river system of Flanders. In one, the database framework is used to simulate the daily discharge for each segment within a catchment using a simple data-driven approach. The presented system is useful for numerous applications including pollution tracking, alerting and inter-sensor validation in river systems, or related networks.

Abstract: This work reports the use of modified screen-printed carbon electrodes (SPCEs) for the identification of three drugs of abuse and two habitual cutting agents, caffeine and paracetamol, combining voltammetric sensing and chemometrics. In order to achieve this goal, codeine, heroin and morphine were subjected to Square Wave Voltammetry (SWV) at pH 7, in order to elucidate their electrochemical fingerprints. The optimized SPCEs electrode array, which have a differentiated response for the three oxidizable compounds, was derived from Carbon, Prussian blue, Cobalt (II) phthalocyanine, Copper (II) oxide, Polypyrrole and Palladium nanoparticles ink-modified carbon electrodes. Finally, Principal Component Analysis (PCA) coupled with Silhouette parameter assessment was used to select the most suitable combination of sensors for identification of drugs of abuse in presence of cutting agents.

Abstract: The use of inks containing organic solvents by the offset printing process implies in the release of volatile organic compounds to the work environment. Many of these compounds such as benzene, toluene, ethylbenzene, and the xylene isomers (well known by the acronym BTEX) are extremely toxic. In this study, the BTEX concentrations were determined in two different printing plants that use distinct types of inks: the conventional and the so-called ecological, which is manufactured based on vegetal oil. Concentration ranges were 4384, 153,480, 2133, 5459, and 2236 μg m−3 for benzene, toluene, ethylbenzene, m + p-xylene, and o-xylene, respectively, for the conventional printing plant. At the ecological printing plant, concentration ranges were below limit of detection (<LD)-31, <LD-618, <LD-1,690, <LD-10,500, <LD-3,360 μg m−3 for benzene, toluene, ethylbenzene, m + p-xylene, and o-xylene, respectively. BTEX concentrations are lower at the ecological printing environment than in the conventional, where mineral oil-based inks are used. However, the worker who cleans the printing matrices is exposed to high concentrations of ethylbenzene and xylenes, due probably to the cleaning products composition (containing high amounts of BTEX). Although the BTEX concentrations found in both printing work environments were below the limits considered by the Brazilian Law for Activities and Unhealthy Operations (NR-15), the exposure to such vapors characterizes risk to the workers health for some of the evaluated samples, mainly the personal ones.

Abstract: The immobilization of biomolecules at screen printed electrodes for biosensing applications is still an open challenge. To enrich the toolbox of bioelectrochemists, graphite screen printed electrodes (G-SPE) were modified with an electropolymerized film of pyrrole-2-carboxilic acid (Py-2-COOH), a pyrrole derivative rich in carboxylic acid functional groups. These functionalities are suitable for the covalent immobilization of biomolecular recognition layers. The electropolymerization was first optimized to obtain stable and conductive polymeric films, comparing two different electrolytes: sodium dodecyl sulphate (SDS) and sodium perchlorate. The G-SPE modified with Py-2-COOH in 0.1 M SDS solution showed the required properties and were further tested. A proof-of-concept study for the development of an impedimetric sensor for perfluorooctanoic acid (PFOA) was carried out using the delipidated human serum albumin (hSA) as bioreceptor. The data interpretation was supported by size exclusion chromatography and small-angle X-ray scattering (SEC-SAXS) analysis of the bioreceptor-target complex and the preliminary results suggest the possibility to further develop this biosensing strategy for toxicological and analytical studies.

Abstract: The haem group is a promising redox probe for the design of albumin-based voltammetric sensors. Among the endogenous ligands carried by human serum albumin (hSA), haem is characterised by a reversible redox behaviour and its binding kinetics strongly depend on hSA’s conformation, which, in turn, depends on the presence of other ligands. In this work, the potential applicability of haem, especially hemin, as a redox probe was first tested in a proof-of-concept study using perfluorooctanoic acid (PFOA) as model analyte. PFOA is known to bind hSA by occupying Sudlow’s I site (FA7) which is spatially related to the haem-binding site (FA1). The latter undergoes a conformational change, which is expected to affect hemin’s binding kinetics. To verify this hypothesis, hemin:albumin complexes in the presence/absence of PFOA were first screened by UV–Vis spectroscopy. Once the complex formation was verified, haem was further characterised via electrochemical methods to estimate its electron transfer kinetics. The hemin:albumin:PFOA system was studied in solution, with the aim of describing the multiple equilibria at stake and designing an electrochemical assay for PFOA monitoring. This latter could be integrated with protein-based bioremediation approaches for the treatment of per- and polyfluoroalkyl substances polluted waters. Overall, our preliminary results show how hemin can be applied as a redox probe in albumin-based voltammetric sensing strategies.

Abstract: Dysregulation of miRNA expression occurs in many cancers, making miRNAs useful in cancer diagnosis and therapeutic guidance. In a clinical context using methods such as polymerase chain reaction (PCR), the limited amount of miRNAs in circulation often limits their quantification. Here, we present a PCR-free and sensitive singlet oxygen (1O2)-based strategy for the detection and quantification of miRNAs in untreated human plasma from patients diagnosed with prostate cancer. A target miRNA is specifically captured by functionalised magnetic beads and a detection oligonucleotide probe in a sandwich-like format. The formed complex is concentrated at the sensor surface via magnetic beads, providing an interface for the photoinduced redox signal amplification. The detection oligonucleotide probe bears a molecular photosensitiser, which produces 1O2 upon illumination, oxidising a redox reporter and creating a redox cycling loop, allowing quantification of pM level miRNA in diluted human plasma within minutes after hybridisation and without target amplification.

Abstract: To sustain human deep space exploration or extra-terrestrial settlements where no resupply from the Earth or other planets is possible, technologies for in situ food production, water, air, and waste recovery need to be developed. The Micro-Ecological Life Support System Alternative (MELiSSA) is such a Regenerative Life Support System (RLSS) and it builds on several bacterial bioprocesses. However, alterations in gravity, temperature, and radiation associated with the space environment can affect survival and functionality of the microorganisms. In this study, representative strains of different carbon and nitrogen metabolisms with application in the MELiSSA were selected for launch and Low Earth Orbit (LEO) exposure. An edible photoautotrophic strain (Arthrospira sp. PCC 8005), a photoheterotrophic strain (Rhodospirillum rubrum S1H), a ureolytic heterotrophic strain (Cupriavidus pinatubonensis 1245), and combinations of C. pinatubonensis 1245 and autotrophic ammonia and nitrite oxidizing strains (Nitrosomonas europaea ATCC19718, Nitrosomonas ureae Nm10, and Nitrobacter winogradskyi Nb255) were sent to the International Space Station (ISS) for 7 days. There, the samples were exposed to 2.8 mGy, a dose 140 times higher than on the Earth, and a temperature of 22 degrees C +/- 1 degrees C. On return to the Earth, the cultures were reactivated and their growth and activity were compared with terrestrial controls stored under refrigerated (5 degrees C +/- 2 degrees C) or room temperature (22 degrees C +/- 1 degrees C and 21 degrees C +/- 0 degrees C) conditions. Overall, no difference was observed between terrestrial and ISS samples. Most cultures presented lower cell viability after the test, regardless of the type of exposure, indicating a harsher effect of the storage and sample preparation than the spaceflight itself. Postmission analysis revealed the successful survival and proliferation of all cultures except for Arthrospira, which suffered from the premission depressurization test. These observations validate the possibility of launching, storing, and reactivating bacteria with essential functionalities for microbial bioprocesses in RLSS.

Abstract: Accurate barriers for rate controlling elementary reactions on metal surfaces are key to understanding, controlling, and predicting the rate of heterogeneously catalyzed processes. While barrier heights for gas phase reactions have been extensively benchmarked, dissociative chemisorption barriers for the reactions of molecules on metal surfaces have received much less attention. The first database called SBH10 and containing 10 entries was recently constructed based on the specific reaction parameter approach to density functional theory (SRP-DFT) and experimental results. We have now constructed a new and improved database (SBH17) containing 17 entries based on SRP-DFT and experiments. For this new SBH17 benchmark study, we have tested three algorithms (high, medium, and light) for calculating barrier heights for dissociative chemisorption on metals, which we have named for the amount of computational effort involved in their use. We test the performance of 14 density functionals at the GGA, GGA+vdW-DF, and meta-GGA rungs. Our results show that, in contrast with the previous SBH10 study where the BEEF-vdW-DF2 functional seemed to be most accurate, the workhorse functional PBE and the MS2 density functional are the most accurate of the GGA and meta-GGA functionals tested. Of the GGA+vdW functionals tested, the SRP32-vdW-DF1 functional is the most accurate. Additionally, we found that the medium algorithm is accurate enough for assessing the performance of the density functionals tested, while it avoids geometry optimizations of minimum barrier geometries for each density functional tested. The medium algorithm does require metal lattice constants and interlayer distances that are optimized separately for each functional. While these are avoided in the light algorithm, this algorithm is found not to give a reliable description of functional performance. The combination of relative ease of use and demonstrated reliability of the medium algorithm will likely pave the way for incorporation of the SBH17 database in larger databases used for testing new density functionals and electronic structure methods.

Abstract: The installation of urban green infrastructure, particularly green walls, has proven to be an effective strategy for the mitigation of particulate matter (PM) pollution and the urban heat island effect. For the interaction between vegetation, PM and the local microclimate, wind flow is the main driving force. In order to investigate these interactions in detail, it is important to know how air flows through vegetation. This study proposes a method based on the DarcyForchheimer equation, where vegetation is considered as a porous medium and several plant species and the effects of plant morphological characteristics are examined both experimentally and using computer simulations. Results showed that the DarcyForchheimer model is a simple and robust way to describe air flow through vegetation regardless of its morphology. This research provides a new vision on studying aerodynamic properties of vegetation in relation to their morphology and provides opportunities for model the interaction between vegetation and its environment.

Abstract: Hierarchicalassembly of arc-like fractal nanostructures not onlyhas its unique self-similarity feature for stability enhancement butalso possesses the structural advantages of highly exposed surface-activesites for activity enhancement, remaining a great challenge for high-performancemetallic nanocatalyst design. Herein, we report a facile strategyto synthesize a novel arc-like hierarchical fractal structure of PtPdbimetallic nanoparticles (h-PtPd) by using pyridinium-type ionic liquidsas the structure-directing agent. Growth mechanisms of the arc-likenanostructured PtPd nanoparticles have been fully studied, and precisecontrol of the particle sizes and pore sizes has been achieved. Dueto the structural features, such as size control by self-similaritygrowth of subunits, structural stability by nanofusion of subunits,and increased numbers of exposed active atoms by the curved homoepitaxialgrowth, h-PtPd displays outstanding electrocatalytic activity towardoxygen reduction reaction and excellent stability during hydrothermaltreatment and catalytic process.

Abstract: We have developed an innovative methodology to overcome the lack of techniques for real-time assessment of degradable biomedical polymers at physiological conditions. The methodology was established by combining polymer characterization techniques with electrochemical sensors. The in vitro hydrolytic degradation of a series of aliphatic polyesters was evaluated by following the molar mass decrease and the mass loss at different incubation times while tracing pH and l-lactate released into the incubation media with customized miniaturized electrochemical sensors. The combination of different analytical approaches provided new insights into the mechanistic and kinetics aspects of the degradation of these biomedical materials. Although molar mass had to reach threshold values for soluble oligomers to be formed and specimens’ resorption to occur, the pH variation and l-lactate concentration were direct evidence of the resorption of the polymers and indicative of the extent of chain scission. Linear models were found for pH and released l-lactate as a function of mass loss for the l-lactide-based copolymers. The methodology should enable the sequential screening of degradable polymers at physiological conditions and has potential to be used for preclinical material’s evaluation aiming at reducing animal tests.

Abstract: The morphology and spatial distribution of alpha (α) precipitates have been mapped as a function of Mo content in Ti-Mo binary alloys employing a combinatorial approach. Heat-treatments were carried out on compositionally graded Ti-xMo samples processed using a rapid throughput laser engineered net shape (LENS) process. The composition space spans 1.5 at% to 6 at% Mo with ageing at 750°C, 650°C and 600°C following a β solution treatment. Three distinct regimes of α morphology and distribution were observed. These are colony-dominated microstructures originating from grain boundary α allotriomorphs, bundles of intragranular α laths, and homogeneously distributed individual fine-scale α laths. Branching of the α precipitates was observed in all these domains in a manner reminiscent of solid-state dendritic growth. The phenomenon is particularly apparent at low volume fractions of α. Similar features are present in a wide variety of alloy compositions. 3-dimensional features of such branched structures have been analysed. Simulation of the branching process by phase field methods incorporating anisotropy in the α/β interface energy and elasticity suggests that it can be initiated at growth ledges present at broad faces of the α laths, driven by the enhancement of the diffusion flux at these steps. The dependence of branching on various parameters such as supersaturation and diffusivity, and microstructural features like ledge height and distribution and the presence of adjacent α variants has been evaluated.

Abstract: Galvanised iron is popular in many applications, particular as a roofing material. However, just like other materials, especially metallic ones, it is prone to degradation by corrosion. In this particular study, the degradation of galvanised roof sheets was investigated at a coastal, urban and rural site in Tanzania, Africa. Samples were exposed to various outdoor environments over a period of 3 years. In addition, some accelerated laboratory investigations were conducted in different simulated air pollution environments in an artificial corrosion chamber constructed for this purpose to supplement the outdoor exposure tests. It was found that the combination of the tropical climate and increasing air pollution due to industrial development in the capital Dar-es-Salaam resulted in substantial atmospheric corrosion of the roof sheets, which eventually leads to failure and the necessity for replacement. The rural site had the lowest degree of atmospheric corrosion as expected. A combination of different corrosion products was identified as a result of the atmospheric corrosion by Raman and EDX analyses. The information gained from this investigation could be utilised to construct more durable structures requiring less frequent replacement and maintenance in future.