Ab initio calculations have been employed to elucidate the habit and surface reactivity of iron carbonate crystals, which are a major component of corrosion scales formed in sweet solutions. The habit is environment dependent, varying from rhombohedral to micro-facetted cylinders with trigonal pyramidal caps as a function of iron activity. Consistent with modelling, the cap facets are shown to be (104) surfaces through a combination of EBSD and confocal microscopy. Furthermore, it is concluded that reactivity is facet dependent, with the (104) surface being relatively inert. These observations have the potential to initiate new approaches to corrosion control and prediction.

Surface adsorption is one of the fundamental processes in numerous fields, including catalysis, the environment, energy and medicine. The development of an adsorption model which provides an effective prediction of binding energy in minutes has been a long term goal in surface and interface science. The solution has been elusive as identifying the intrinsic determinants of the adsorption energy for various compositions, structures and environments is non-trivial. We introduce a new and flexible model for predicting adsorption energies to metal substrates. The model is based on easily computed, intrinsic properties of the substrate and adsorbate, which are the same for all the considered systems. It is parameterised using machine learning based on first-principles calculations of probe molecules (e.g., H2O, CO2, O2, N2) adsorbed to a range of pure metal substrates. The model predicts the computed dissociative adsorption energy to metal surfaces with a correlation coefficient of 0.93 and a mean absolute error of 0.77 eV for the large database of molecular adsorption energies provided by Catalysis-Hub.org which have a range of 15 eV. As the model is based on pre-computed quantities it provides near-instantaneous estimates of adsorption energies and it is sufficiently accurate to eliminate around 90% of candidates in screening study of new adsorbates. The model, therefore, significantly enhances current efforts to identify new molecular coatings in many applied research fields.

The description of adsorption to surfaces and interfaces is essential in many technological fields, such as catalysis, corrosion and friction. For example, an accurate prediction of the structure and properties of molecules on substrates is essential to both the design and optimisation of coatings used to protect and enhance the properties of metals. We introduce a new model for the prediction of adsorption energies of molecules to metal substrates. The model is based on easily computed, intrinsic properties of the substrate and molecules (e.g., bulk cohesive energy, work function, molecule-cluster binding and the molecular orbital energy gap). It is parameterised by combining ab initio calculations with machine learning algorithms. The model is trained using a small set of probe molecules (e.g., H$_2$O, CO$_2$, O$_2$, N$_2$) adsorbed to a range of pure metal substrates. The model predicts the computed dissociative adsorption energy to metal surfaces with a correlation coefficient of 0.93 and a mean absolute error of 0.77 eV for the large database of molecular adsorptions stored in the this http URL database. The model therefore significantly enhances current efforts to identify new molecular coatings in many research fields and thus facilitates the discovery of new environmentally friendly and inexpensive materials with specific adhesion characteristics.

Robust fitting of core level photoemission spectra is often central to reliable interpretation of X‐ray photoelectron spectroscopy (XPS) data. One key element is employment of the correct line shape function for each spectral component. In this study, we consider this topic, focusing on XPS data from atomic adsorbates, namely, O and S, on Fe(110). The potential of employing density functional theory (DFT) for generating adsorbate projected electronic density of states (PDOS) to support line shape selection is explored. O 1s core level XPS spectra, acquired from various ordered overlayers of chemisorbed O, all display an equivalent asymmetric line shape. Previous work suggests that this asymmetry is a result of finite O PDOS in the vicinity of the Fermi level, allowing O 1s photoexcitation to induce a weighted continuum of final states through electron‐hole pair excitation. This origin is corroborated by O DFT‐PDOS generated for an optimised five‐layer Fe(110)(2 × 2)‐O slab. Adsorbate DFT‐PDOS were also computed for Fe(110) ‐S. As, similar to adsorbed O, there is a significant continuous distribution of states about the Fermi level, it is proposed that the S 2p XPS core levels should also have asymmetric profiles. S 2p XPS data acquired from Fe(110) ‐S, and their subsequent fitting, verify this prediction, suggesting that DFT‐PDOS could aid line shape selection.

A new approach for the study of photocatalytic heterojunctions based on a layer-by-layer PDOS has been developed. Our combination of experimental and theoretical calculations reveals the importance of interfacial effects when a heterojunction is formed that can dictate the performance of a heterojunction.

Perovskites have been widely studied for electrocatalysis due to the exceptional activity they exhibit for surface-mediated redox reactions. To date, descriptors based on density functional theory calculations or experimental measurements have assumed a bulk-like configuration for the surfaces of these oxides. Herein, we probed an initial exposed surface and the screened subsurface of LaMnO3 particles, demonstrating that their augmented activity toward the oxygen reduction reaction (ORR) can be related to a spontaneous surface reconstruction. Our approach involves high energy resolution electron energy loss spectroscopy for the fine structure probing of oxygen and manganese ionization edges under electron beam conditions that leave the structure unaffected. Atomic multiplet and density functional theory calculations were used to compute the theoretical energy loss spectra for comparison to the experimental data, allowing to quantitatively demonstrate that the particle surface layers are La-deficient. This deficiency is linked to equivalent tetrahedral Mn2+ sites at the reconstructed surface, leading to the coexistence of +3 and +2 oxidation states of Mn at the surface layers. This electronic and structural configuration of the as-synthesized particles is indirectly linked to strong adsorption pathways that promote the ORR on LaMnO3, and thus, it could prove to be a valuable design feature in the engineering of catalytic surfaces.

Despite intensive study over many years, the chemistry and physics of the atomic level mechanisms that govern corrosion are not fully understood. In particular, the occurrence and severity of highly localized metal degradation cannot currently be predicted and often cannot be rationalized in failure analysis. We report a first-principles model of the nature of protective iron carbonate films coupled with a detailed chemical and physical characterization of such a film in a carefully controlled environment. The fundamental building blocks of the protective film, siderite (FeCO3) crystallites, are found to be very sensitive to the growth environment. In iron-rich conditions, cylindrical crystallites form that are highly likely to be more susceptible to chemical attack and dissolution than the rhombohedral crystallites formed in iron-poor conditions. This suggests that local degradation of metal surfaces is influenced by structures that form during early growth and provides new avenues for the prevention, detection, and mitigation of carbon steel corrosion.

Electrochemical measurements and substrate analysis have been employed to study the corrosion of iron in sweet solution (pH = 6.8, T = 80 degrees C) over a period of 288 h. Correlated with decreasing corrosion rate, diffraction, microscopy, and spectroscopy data reveal the evolution of adhered sweet corrosion scale. Initially, it is comprised of two phases, siderite and chukanovite, with the latter affording little substrate protection. Subsequently, as the scale becomes highly protective, siderite is the sole component. Notably, siderite crystals are concluded to display a somewhat unexpected habit, which may be a trigger for local breakdown of protective sweet scales.

We show that chemical fixation enables top-down micro-machining of large periodic 3D arrays of protein-encapsulated magnetic nanoparticles (NPs) without loss of order. We machined 3D micro-cubes containing a superlattice of NPs by means of focused ion beam etching, integrated an individual micro-cube to a thin-film coplanar waveguide and measured the resonant microwave response. Our work represents a major step towards well-defined magnonic metamaterials created from the self-assembly of magnetic nanoparticles.

A real time magnetovision camera with a refresh rate of 600 frames per second (fps) was developed based on small size, high sensitivity Quantum Well Hall Effect (QWHE) sensors. This handheld system consists of a 16 x 16 QWHE sensor array covering an 80 mm x 80 mm area. This system has a spatial resolution of 5.08 pixels per inch (ppi). By using a superheterodyne technique to reduce the impact of (1/f) noise, magnetic fields down to 2 mu T can be detected for both direct and alternating magnetic field operations. Experimental results of five case studies demonstrate that magnetic flux leakage (MFL) and magnetovision imaging in DC and AC magnetic field resulting from defects and shape, can be successfully measured. The major applications of this new system are: (1) in MFL testing equipment with permanent magnets or electromagnets, (2) to obtain 2D graphical imaging similar to magnetic particle inspection (MPI) without its inherent drawbacks, (3) for examination of non-ferromagnetic materials such as aluminium, copper, and stainless steels for deep defects below the surface using low frequency alternating magnetic fields, and (4) for material identification, which has a considerable potential in several applications such as in security, product protection, bio-imaging, and medical. (C) 2017 Elsevier B.V. All rights reserved.

A linear galvanic isolator was developed, using a compact and high sensitivity Quantum Well Hall Effect (QWHE) sensor. This sensor is based on a GaAs-InGaAs-AlGaAs heterostructure, with a maximum capacitance of 5.5 pF and a 3 dB bandwidth of 40.2 MHz. As part of this work, a printed transmitter coil was also designed as part of this QWHE galvanic isolator. A linear relationship between input current and output voltage, at each frequency of the isolation device, were observed (R-2 approximate to 1.0). The relative errors of frequency response between 0 and 100 kHz were <= 5.4%. Two gain temperature coefficients were also obtained at low and high temperatures, alpha(1) and alpha(2), with a temperature of 280 K being the boundary between the two regions. The mean values of alpha(1) and alpha 2 were (7.09 +/- 0.27) x 10(-4) K-1 and (3.22 +/- 0.17) x 10(-4) K-1 respectively. The controlling mechanisms for the amplitudes of alpha(1) and alpha(2) are suggested to be due to the temperature variation of the two-dimensional electron gas (2DEG) electron mobility, arising from the heterostructure nature of the QWHE sensor used. The QWHE isolator has high accuracy, large bandwidth, high frequency-gain linearity and thermal stability. Compared with commercial optical isolators, Silicon Hall sensor-based isolators and coil isolators, this QWHE isolator does not require any external light sensor transistor or ferrite toroid to enhance its sensitivity. As such, it is not affected by any nonlinear transistor behaviour, B-H curve or magnetic retention. The results indicate that this high sensitivity, highly linear QWHE isolator is suitable for use as a low cost, high efficiency, linear galvanic isolation device. (C) 2017 The Authors. Published by Elsevier B.V.

A novel magnetovision system was developed based on miniature, highly sensitive Quantum Well Hall Effect (QWHE) Sensors. This system consists of a handheld, portable 1616 QWHE sensors array, and an adjustable electromagnet, which can generate both DC and AC magnetic fields. The system has high spatial resolution due to the use of the small size sensors (QWHE) compared to conventional coils. By using a superheterodyne technique, magnetic fields in the range of nano to micro Tesla can be detected both for DC and AC operations, respectively. In DC measurements, this system can also be used as a MFL testing equipment, which can provide 2 dimensional graphical images results similar to MPI but without its inherent drawbacks. By using low frequency magnetic fields, non-magnetic materials such as aluminum, copper and stainless steels can also be examined allowing for deeper defects below the surface to be detected. By varying the frequency of the excitation magnetic field, different skin depth can be accessed and therefore the full thickness of the materials can be tested leading to 3 dimensional visualization of the positions and sizes of the defects. Finally, the system can be used in multiple sampling measurements to give better signal to noise ratios and in real time measurements for fast scan speed requirements.

Catalytic activity of perovskites for oxygen reduction (ORR) was recently correlated with bulk d-electron occupancy of the transition metal. We expand on the resultant model, which successfully reproduces the high activity of LaMnO3 relative. to other perovskites, by addressing catalyst surface Morphology as an important aspect of the optimal OAR. catalyst The nature of reaction sites on low index surfaces of orthorhombic (Pnma) LaMnO3 is established from First Principles. The adsorption of O-2 is Markedly influenced by local geometry and strong electron correlation. Only one of the six reactions sites that result from experimentally confirmed symmetry-breaking Jahn-Teller distortions is found to bind O-2 with an intermediate binding-energy while facilitating the formation of superoxide; an important ORR intermediate in alkaline media. As demonstrated here for LaMnO3, rational design of the catalyst morphology to promote specific active sites is a highly effective Optimization strategy for advanced functional ORR catalysts.

We report a combined experimental and theoretical study of the quasistatic hysteresis and dynamic excitations in large-area arrays of NiFe nanodisks forming a hexagonal lattice with the lattice constant of 390 nm. Arrays were fabricated by patterning a 20-nm-thick NiFe film using the etched nanosphere lithography. We have studied a close-packed (edge-to-edge separation between disks d(cp) = 65 nm) and an ultraclosed packed (d(ucp) = 20 nm) array. Hysteresis loops for both arrays were qualitatively similar and nearly isotropic, i.e., independent on the in-plane external field orientation. The shape of these loops revealed that magnetization reversal is governed by the formation and expulsion of vortices inside the nanodisks. When we assumed that the nanodisks' magnetization significantly decreases near their edges, micromagnetic simulations with material parameters deter-mined independently from continuous film measu-rements could satisfactorily reproduce the hysteresis. Despite the isotropic hysteresis, significant in-plane anisotropy of the dynamic response of the ultraclose-packed array was found experimentally by the all-electrical spin-wave spectroscopy and Brillouin light scattering. Dynamical simulations could successfully reproduce the difference between excitation spectra for fields directed along the two main symmetry axes of the hexagonal lattice. Simulations revealed that this difference is caused by the magnetodipolar interaction between nanodisks, which leads to a strong variation of the spatial distribution of the oscillation power both for bulk and edge modes as a function of the bias field orientation. Comparison of simulated and measured frequencies enabled the unambiguous identification of experimentally observed modes. Results of this systematic research are relevant both for fundamental studies of spin-wave modes in patterned magnetic structures and for the design of magnonic crystals for potential applications as, e. g., spin-wave guides and filters.

An all-optical experiment long utilized to image phonons excited by ultrashort optical pulses has been applied to a magnetic sample. In addition to circular ripples due to surface acoustic waves, we observe an X-shaped pattern formed by propagating spin waves. The emission of spin waves from the optical pulse epicenter in the form of collimated beams is qualitatively reproduced by micromagnetic simulations. We explain the observed pattern in terms of the group velocity distribution of Damon-Eshbach magnetostatic spin waves in the reciprocal space and the wave vector spectrum of the focused ultrafast laser pulse.

We report a study of the dispersion of spin waves in a hexagonal array of interacting ferromagnetic nanodisks for two orthogonal orientations of the in-plane applied magnetic field, i.e., either parallel or perpendicular to the direction of first neighbour disks. The experimental data were modelled using the dynamical matrix method, and the results were interpreted in terms of the effective wave vector model. We have found that spin waves propagating in the two orthogonal directions exhibit marked asymmetry concerning the existence of maxima/minima in their dispersion curves and the sign of their group velocities.