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Understanding materials' atomic structure with a high level of confidence and certainty is often regarded as a very arduous and sometimes impossible task, especially for newer, emerging technology materials exhibiting limited long-range order. Nevertheless, information about atomic structural properties is very valuable for materials science and synthesis. For non-crystalline amorphous and nanoscale materials, using conventional structural determination methods is impossible. Reverse Monte Carlo (RMC) modeling is commonly used to derive models of materials from experimental diffraction data. Here, the latest developments in the fullrmc software package are discussed. Despite its name, fullrmc provides a very flexible modeling framework for solving atomic structures with many methods beyond RMC. The stochastic nature of fullrmc allows it to explore all possible dimensions and degrees of freedom for atomic modeling and create statistical solutions to match measurements. Differing versions of fullrmc are provided as open source or for cloud computing access. The latter includes a modern web-based graphical user interface that incorporates advanced computing and structure-building modules and machine-learning-based components. The main features of fullrmc are presented, including constraint types, boundary conditions, density shape functions and the two running modes: stochastic using a Monte Carlo algorithm and optimization using a genetic algorithm. Capabilities include tools for statistical, mesoscopic and nanoscopic approaches, atomic or coarse-grained models, and smart artificial-intelligence-ready loss functions.

Atomic layer deposition (ALD) is a well-established technique for depositing nanoscale coatings with pristine control of film thickness and composition. The trimethylaluminum (TMA) and water (H2O) ALD chemistry is inarguably the most widely used and yet to date, we have little information about the atomic-scale structure of the amorphous aluminum oxide (AlOx) formed by this chemistry. This lack of understanding hinders our ability to establish process-structure-property relationships and ultimately limits technological advancements employing AlOx made via ALD. In this work, we employ synchrotron high-energy X-ray diffraction (HE-XRD) coupled with pair distribution function (PDF) analysis to characterize the atomic structure of amorphous AlOx ALD coatings. We combine ex situ and in operando HE-XRD measurements on ALD AlOx and fit these experimental data using stochastic structural modeling to reveal variations in the Al-O bond length, Al and O coordination environment, and extent of Al vacancies as a function of growth conditions. In particular, the local atomic structure of ALD AlOx is found to change with the substrate and number of ALD cycles. The observed trends are consistent with the formation of bulk Al2O3 surrounded by an O-rich surface layer. We deconvolute these data to reveal atomic-scale structural information for both the bulk and surface phases. Overall, this work demonstrates the usefulness of HE-XRD and PDF analysis in improving our understanding of the structure of amorphous ALD thin films and provides a pathway to evaluate how process changes impact the structure and properties of ALD films.

Summary Sodium-ion batteries are the primary candidate for a low-cost and resource-abundant alternative to lithium-ion batteries for large-scale electric storage applications. However, the development of sodium-ion batteries is hindered by the lack of suitable cathode materials that have sufficient specific energy density and cycle life. Here, we report layered NaVOPO 4 as a cathode material that exhibits high voltage (∼3.5 V versus Na/Na + ), high discharge capacity (144 mAh g −1 at 0.05 C), and remarkable cyclability with 67% capacity retention over 1,000 cycles. The excellent performances result from the high Na + ion diffusion rate in the two-dimensional path and the reversible transformation behavior of (de)sodiation. Particularly, this layered structure and its synthetic procedure can be extended to other alkali-metal intercalation materials, leading to other metal-ion battery systems, which opens a new avenue for large-scale energy storage systems with the development of high-energy-density and long-life cathodes for electric storage applications.

We investigate the effect of several coatings applied in biomedical applications to iron oxide nanoparticles on the size, structure and composition of the particles. The four structural techniques employed - TEM, DLS, VSM, SAXS and EXAFS - show no significant effects of the coatings on the spherical shape of the bare nanoparticles, the average sizes or the local order around the Fe atoms. The NPs coated with hydroxylmethylene bisphosphonate or catechol have a lower proportion of magnetite than the bare and citrated ones, raising the question whether the former are responsible for increasing the valence state of the oxide on the NP surfaces and lowering the overall proportion of magnetite in the particles. VSM measurements show that these two coatings lead to a slightly higher saturation magnetization than the citrate. This article is part of a Special Issue entitled "Science for Life" Guest Editor: Dr. Austen Angell, Dr. Salvatore Magazu and Dr. Federica Migliardo. (C) 2016 Elsevier B.V. All rights reserved.

In this work, we explore the pore structure of overcoated materials by in situ synchrotron small-angle (SAXS) and wide-angle X-ray scattering (WAXS). Thin films of aluminum oxide (Al2O3) and titanium dioxide (TiO2) with thicknesses of 4.9 and 2.5 nm, respectively, are prepared by atomic layer deposition (ALD) on nonporous nanoparticles. In situ X-ray measurements reveal that porosity is induced in the ALD films by annealing the samples at high temperatures. Moreover, this pore formation can be attributed to densification resulting from an amorphous to crystalline phase transition of the ALD films as confirmed by high-resolution X-ray diffraction and the pair distribution function. Simultaneous SAXS and WAXS results show not only that the porosity is formed by the phase transition but also that the pore size increases with temperature.

Microstructure evolution of a cold-drawn NiTi shape memory alloy wire was investigated by means of in-situ synchrotron high-energy X-ray diffraction during continuous heating. The cold-drawn wire contained amorphous regions and nano-crystalline domains in its microstructure. Pair distribution function analysis revealed that the amorphous regions underwent structural relaxation via atomic rearrangement when heated above 100 °C. The nano-crystalline domains were found to exhibit a strong cold work induced lattice strain anisotropy along 〈111〉, which coincides with the crystallographic fiber orientation of the domains along the wire axial direction. The lattice strain anisotropy systematically decreased upon heating above 200 °C, implying a structural recovery. Crystallization of the amorphous phase led to a broadening of the angular distribution of 〈111〉 preferential orientations of grains along the axial direction as relative to the original 〈111〉 axial fiber texture of the nanocrystalline domains produced by the severe cold wire drawing deformation.

A new Reverse Monte Carlo (RMC) package "fullrmc" for atomic or rigid body and molecular, amorphous, or crystalline materials is presented. fullrmc main purpose is to provide a fully modular, fast and flexible software, thoroughly documented, complex molecules enabled, written in a modern programming language (python, cython, C and C++ when performance is needed) and complying to modern programming practices. fullrmc approach in solving an atomic or molecular structure is different from existing RMC algorithms and software. In a nutshell, traditional RMC methods and software randomly adjust atom positions until the whole system has the greatest consistency with a set of experimental data. In contrast, fullrmc applies smart moves endorsed with reinforcement machine learning to groups of atoms. While fullrmc allows running traditional RMC modeling, the uniqueness of this approach resides in its ability to customize grouping atoms in any convenient way with no additional programming efforts and to apply smart and more physically meaningful moves to the defined groups of atoms. In addition, fullrmc provides a unique way with almost no additional computational cost to recur a group's selection, allowing the system to go out of local minimas by refining a group's position or exploring through and beyond not allowed positions and energy barriers the unrestricted three dimensional space around a group.

We have reanalyzed quasielastic neutron scattering data measured for three prototypical ionic liquids characterized by increasingly longer alkyl chains using two standard models of different complexity. The first one contains only two main components representing a long-range translational diffusion process plus a faster localized-like motion. The second model includes an additional component in order to account for the possibility of having more than one type of localized motion with different characteristic time scales. Our results show the complexity of the relaxation landscape of ionic liquids, indicating that even the more complex model provides only a qualitative average picture of such complex dynamics. The comparison of both models allows to asses also the robustness of the parameters obtained from the fits. Finally the results for the three different ionic liquids are compared in order to determine the effect of the length of the alkyl chain in the translational dynamics of ionic liquids, showing a clear decrease in diffusivity when passing from the ethyl (n=2) to the butyl (n=4) alkyl chain, but a much smaller effect when adding two extra C atoms to the chain.We have reanalyzed quasielastic neutron scattering data measured for three prototypical ionic liquids characterized by increasingly longer alkyl chains using two standard models of different complexity. The first one contains only two main components representing a long-range translational diffusion process plus a faster localized-like motion. The second model includes an additional component in order to account for the possibility of having more than one type of localized motion with different characteristic time scales. Our results show the complexity of the relaxation landscape of ionic liquids, indicating that even the more complex model provides only a qualitative average picture of such complex dynamics. The comparison of both models allows to asses also the robustness of the parameters obtained from the fits. Finally the results for the three different ionic liquids are compared in order to determine the effect of the length of the alkyl chain in the translational dynamics of ionic liquids, showing...

A generalized method is introduced to extract critical information from series of ranked correlated data. The method is generally applicable to all types of spectra evolving as a function of any arbitrary parameter. This approach is based on correlation functions and statistical scedasticity formalism. Numerous challenges in analyzing high throughput experimental data can be tackled using the herein proposed method. We applied this method to understand the reactivity pathway and formation mechanism of a Li-ion battery cathode material during high temperature synthesis using in-situ high-energy X-ray diffraction. We demonstrate that Pearson's correlation function can easily unravel all major phase transition and, more importantly, the minor structural changes which cannot be revealed by conventionally inspecting the series of diffraction patterns. Furthermore, a two-dimensional (2D) reactivity pattern calculated as the scedasticity along all measured reciprocal space of all successive diffraction pattern pairs unveils clearly the structural evolution path and the active areas of interest during the synthesis. The methods described here can be readily used for on-the-fly data analysis during various in-situ operando experiments in order to quickly evaluate and optimize experimental conditions, as well as for post data analysis and large data mining where considerable amount of data hinders the feasibility of the investigation through point-by-point inspection.

The influence of water on the structure of a prototype ionic liquid (IL) 1-octyl-3-methylimidazolium tetrafluoroborate (C8mimBF4) is examined in the IL-rich regime using high-energy X-ray diffraction (HEXRD) and molecular dynamics (MD) simulations. A many-body polarizable force field APPLE&P was developed for C8mimBF4-water mixture. It predicts structure factors of pure IL and IL-water mixture in excellent agreement with the HEXRD experiments. The MD results provide detailed insights into the structural changes from the partial structure factors, 2-D projections of the simulation box and 3-D distribution functions. Water partitioning with IL and its competition with BF4(-) for complexing the imidazolium rings was examined. The added water molecules occupy a diffuse coordination shell around the imidazolium ring but are not present around the alkyl tail. The strong coordination of the fluorine atoms of the BF4(-) anions to the imidazolium ring is not significantly changed by the addition of water. A complementary packing of water and imidazolium around BF4(-) was found. These results are consistent with the very small differences in the average structure between the pure IL and the mixture.

Neutron scattering techniques have been employed to investigate 1,2-dimyristoyl-sn -glycero-3-phosphocholine (DMPC) membranes in the form of multilamellar vesicles (MLVs) and deposited, stacked multilamellar-bilayers (MLBs), covering transitions from the gel to the liquid phase. Neutron diffraction was used to characterise the samples in terms of transition temperatures, whereas elastic incoherent neutron scattering (EINS) demonstrates that the dynamics on the sub-macromolecular length-scale and pico- to nano-second time-scale are correlated with the structural transitions through a discontinuity in the observed elastic intensities and the derived mean square displacements. Molecular dynamics simulations have been performed in parallel focussing on the length-, time- and temperature-scales of the neutron experiments. They correctly reproduce the structural features of the main gel-liquid phase transition. Particular emphasis is placed on the dynamical amplitudes derived from experiment and simulations. Two methods are used to analyse the experimental data and mean square displacements. They agree within a factor of 2 irrespective of the probed time-scale, i.e. the instrument utilized. Mean square displacements computed from simulations show a comparable level of agreement with the experimental values, albeit, the best match with the two methods varies for the two instruments. Consequently, experiments and simulations together give a consistent picture of the structural and dynamical aspects of the main lipid transition and provide a basis for future, theoretical modelling of dynamics and phase behaviour in membranes. The need for more detailed analytical models is pointed out by the remaining variation of the dynamical amplitudes derived in two different ways from experiments on the one hand and simulations on the other.

We present experimental (X-ray diffraction) data on the structure of liquid dibutyl sulfoxide at 320 K and rationalise the data by means of molecular dynamics simulations. Not unexpectedly, DBSO bearing a strong dipolar moiety and two medium length, apolar butyl chains, this compound was characterised by a distinct degree of polar vs. apolar structural differentiation at the nm spatial scale, which was fingerprinted by a low Q peak in its X-ray diffraction pattern. Similar to, but to a larger extent than its shorter chain family members (such as DMSO), DBSO was also characterised by an enhanced dipole-dipole correlation, which was responsible for a moderate Kirkwood correlation factor as well as for the self-association detected in this compound. We show, however, that the supposedly relevant hydrogen bonding correlations between oxygen and the butyl chain hydrogens are of a limited extent only, and only in the case of α-hydrogens is an appreciable indication of the existence of such an interaction found, albeit this turned out to be a mere consequence of the strong dipole-dipole correlation.

Molecular dynamics simulations have been used to investigate the confinement packing characteristics of small hydrophilic (N-acetyl-glycine-methylamide, Nagma) and hydrophobic (N-acetyl-leucine-methylamide, Nalma) biomolecules in large diameter single-wall carbon nanotubes (SWCNTs). We find that hydrophilic biomolecules easily fill the nanotube and self organize into a geometrical configuration which reminds the water structural organization under SWCNT confinement. The packing of hydrophilic biomolecules inside the cylinder confines all water molecules in its core, which enhances their mobility. Conversely, hydrophobic biomolecules accommodate into the nanotubes with a trend for homogeneous filling, which generate unstable small pockets of water and drive toward a state of dehydration. These results shed light on key parameters important for the encapsulation of biomolecules with direct relevance for long-term storage and prevention of degradation.

Here we report the first structural and dynamic investigation on ethylammonium nitrate, a representative protic Ionic liquid, and dimethylsulfoxide. By using joined x/ray and neutron diffraction, we exploit the EPSR approach to extract structural information at atomistic level. EAN/DMSO turns out to be homogeneous at microscopic scales and indications for the existence of a structural leit motiv with stoichiometric composition 2DMSO:1EAN are found. Dielectric spectroscopy is used to access the relaxation map of the DMSO:EAN = 60:40 mixture. No crystallisation is detected and three relaxation processes could be characterised. Overall this study provides new indications of strict analogies between water and ethylammonium nitrate.