Abstract: Metal-air batteries and fuel cells show a great deal of promise in advancing low-cost, high-energy-density charge storage solutions for sustainable energy applications. To improve the activities and stabilities of electrocatalysts for the critical oxygen reduction and evolution reactions (ORR and OER, respectively), a greater understanding is needed of the catalyst/carbon interactions and carbon stability. Herein, we report how LaNiO3 (LNO) supported on nitrogen-doped carbon nanotubes (N-CNT) made from a high-yield synthesis lowers the overpotential for both the OER and ORR markedly to enable a low bifunctional window of 0.81 V at only a 51 mu g cm(-2) mass loading. Furthermore, the addition of LNO to the N-CNTs improves the galvanostatic stability for the OER by almost 2 orders of magnitude. The nanoscale geometries of the perovskites and the CNTs enhance the number of metal-support and charge transfer interactions and thus the activity. We use rotating ring disk electrodes (RRDEs) combined with Tafel slope analysis and ICP-OES to quantitatively separate current contributions from the OER, carbon oxidation, and even anodic iron leaching from carbon nanotubes.

Abstract: The EPS Antwerp Young Minds (AYM) invited Prof. Nir Navon (Yale University) to hold a colloquium for the physics department. For an audience of students and researchers, Prof. Navon presented recent advances in ultracold quantum matter and research from his own lab. His experimental work paves the way to make toy models used by theorists a reality. We sat down afterwards to discuss ultracold physics, box traps and setting up a lab from scratch.

Abstract: The development of advanced methods for non-destructive selective imaging of painted works of art at the macroscopic level based on radiation in the X-ray and infrared range of the electromagnetic spectrum are concisely reviewed. Such methods allow to either record depth-selective, element-selective or species-selective images of entire paintings. Camera-based full field methods (that record the image data in parallel) can be discerned next to scanning methods (that build up distributions in a sequential manner by scanning a beam of radiation over the surface of an artefact). Six methods are discussed: on the one hand, macroscopic X-ray fluorescence and X-ray diffraction imaging and X-ray laminography and on the other hand macroscopic Mid and Near Infrared hyper- and full spectral imaging and Optical Coherence Tomography. These methods can be considered to be improved versions of the well-established imaging methods employed worldwide for examination of paintings, i.e., X-ray radiography and Infrared reflectography. Possibilities and limitations of these new imaging techniques are outlined.

Abstract: Combining partial nitrification, granular activated carbon (GAC) filtration, and distillation is a well-studied approach to convert urine into a fertilizer. To evaluate the environmental sustainability of a technology, the operational carbon footprint and therefore nitrous oxide (N2O) emissions should be known, but N2O emissions from urine nitrification have not been assessed yet. Therefore, N2O emissions of a decentralized urine nitrification reactor were monitored for 1 month. During nitrification, 0.4-1.2% of the total nitrogen load was emitted as N2O-N with an average N2O emission factor (EFN2O) of 0.7%. Additional N2O was produced during anoxic storage between nitrification and GAC filtration with an estimated EFN2O of 0.8%, resulting in an EFN2O of 1.5% for the treatment chain. N2O emissions during nitrification can be mitigated by 60% by avoiding low dissolved oxygen or anoxic conditions and nitrite concentrations above 5 mg-N L-1. Minimizing the hydraulic retention time between nitrification and GAC filtration can reduce N2O formation during intermediate storage by 100%. Overall, the N2O emissions accounted for 45% of the operational carbon footprint of 14 kg-CO2,equiv kg-N-1 for urine fertilizer production. Using electricity from renewable sources and applying the proposed N2O mitigation strategies could potentially lower the carbon footprint by 85%.

Abstract: Using first-principles calculations, we demonstrated that high lithium storage capacity and fast kinetics are achieved for Ti3C2O2 by preintercalating organic molecules. As a proof-of-concept, two different quinone molecules, namely 1,4-benzoquinone (C6H4O2) and tetrafluoro-1,4-benzoquinone (C6F4O2) were selected as the molecular linkers to demonstrate the feasibility of this interlayer engineering strategy for energy storage. As compared to Ti3C2O2 bilayer without linker molecules, our pillared structures facilitate a much faster ion transport, promising a higher charge/discharge rate for Li. For example, while the diffusion barrier of a single Li ion within pristine Ti3C2O2 bilayer is at least 1.0 eV, it becomes 0.3 eV in pillared structures, which is comparable and even lower than that of commercial materials. At high Li concentrations, the calculated diffusion barriers are as low as 0.4 eV. Out-of-plane migration of Li ions is hindered due to large barrier energy with a value of around 1-1.35 eV. Concerning storage capacity, we can only intercalate one monolayer of Li within pristine Ti3C2O2 bilayer. In contrast, pillared structures offer significantly higher storage capacity. Our calculations showed that at least two layers of Li can be intercalated between Ti3C2O2 layers without forming bulk Li and losing the pillared structure upon Li loading/unloading. A small change in the in-plane lattice parameters (<0.5%) and volume (<1.0%) and ab initio molecular dynamics simulations prove the stability of the pillared structures against Li intercalation and thermal effects. Intercalated molecules avoid the large contraction/expansion of the whole structure, which is one of the key problems in electrochemical energy storage. Pillared structures allow us to realize electrodes with high capacity and fast kinetics. Our results open new research paths for improving the performance of not only MXenes but also other layered materials for supercapacitor and battery applications.

Abstract: The Darhib mine is one of the several talc deposits in the Hamata area of southeastern Egypt. Several specimens of minerals coming from this mine were subjected to complementary investigation by micro-Raman spectrometry and scanning electron microscopy. The difficulty in their identification is the appearance of most of them: they are all very small and only visible under the mineral binocular microscope(×10 – ×40). They appear as small crystals in fissures and holes and a visual determination on colour and crystal gives only a guess of what kind of mineral it could be. Therefore, only after analyzing them by micro-Raman and scanning electron microscopy it was possible to identify their structure and they can be divided in three main groups: one is quite generic and several minerals of different species were identified, such as quartz, talc, mottramite and chrysocolla, very common in the talc mine (these ones are Si-based minerals); the other one is constituted by four samples which are Zn and/or Cu rich, which means minerals of the rosasite or aurichalcite groups; the last group is constituted by two samples containing mainly Pb..

Abstract: We generalize the Gielis Superformula by extending the R. Chacon approach, but avoiding the use of Jacobi elliptic functions. The obtained results are extended to the three-dimensional case. Several new shapes are derived by using the computer algebra system Mathematica(C).

Abstract: The definition of Gielis curves allows for the representation of self intersecting curves. The analysis and the understanding of these representations is of major interest for the analytical representation of sectors bounded by multiple subsets of curves (or surfaces), as this occurs for instance in many natural objects. We present a construction scheme based on R-functions to build signed potential fields with guaranteed differential properties, such that their zero-set corresponds to the outer, the inner envelop, or combined subparts of the curve. Our framework is designed to allow for the definition of composed domains built upon Boolean operations between several distinct objects or some subpart of self-intersecting curves, but also provides a representation for soft blending techniques in which the traditional Boolean union and intersection become special cases of linear combinations between the objects' potential fields. Finally, by establishing a connection between R-functions and Lame curves, we can extend the domain of the p parameter within the R-p-function from the set of the even positive numbers to the real numbers strictly greater than 1, i.e. p is an element of]1, +infinity[.

Abstract: Single-shot structured light profilometry (SLP) aims at reconstructing the 3D height map of an object from a single deformed fringe pattern and has long been the ultimate goal in fringe projection profilometry. Recently, deep learning was introduced into SLP setups to replace the task-specific algorithm of fringe demodulation with a dedicated neural network. Research on deep learning-based profilometry has made considerable progress in a short amount of time due to the rapid development of general neural network strategies and to the transferrable nature of deep learning techniques to a wide array of application fields. The selection of the employed loss function has received very little to no attention in the recently reported deep learning-based SLP setups. In this paper, we demonstrate the significant impact of loss function selection on height map prediction accuracy, we evaluate the performance of a range of commonly used loss functions and we propose a new mixed gradient loss function that yields a higher 3D surface reconstruction accuracy than any previously used loss functions.