Comparative analysis of surface phase diagrams in aqueous environment: Implicit vs explicit solvation models.

Identifying the stable surface phases under a given electrochemical conditions serves as the basis for studying the atomistic mechanism of reactions at solid/water interfaces. In this work, we systematically compare the performance of the two main approaches that are used to capture the impact of an aqueous environment, implicit and explicit solvent, on surface energies and phase diagrams. As a model system, we consider the magnesium/water interface with (i) Ca substitution and (ii) proton and hydroxyl adsorption. We show that while the implicit solvent model is computationally very efficient, it suffers from two shortcomings. First, the choice of the implicit solvent parameters significantly influences the energy landscape in the vicinity of the surface. The default parameters benchmarked on solvation in water underestimate the energy of the dissolved Mg ion and lead to spontaneous dissolution of the surface atom, resulting in large differences in the surface energetics. Second, in systems containing a charged surface and a solvated ion, the implicit solvent model may not converge to the energetically stable ionic charge state but remain in a high-energy metastable configuration, representing the neutral charge state of the ion. When these two issues are addressed, surface phase diagrams that closely match the explicit water results can be obtained. This makes the implicit solvent model highly attractive as a computationally-efficient surrogate model to compute surface energies and phase diagrams.

A Machine Learning Framework for Quantifying Chemical Segregation and Microstructural Features in Atom Probe Tomography Data.

Atom probe tomography (APT) is ideally suited to characterize and understand the interplay of segregation and microstructure in modern multi-component materials. Yet, the quantitative analysis typically relies on human expertise to define regions of interest. We introduce a computationally efficient, multi-stage machine learning strategy to identify compositionally distinct domains in a semi-automated way, and subsequently quantify their geometric and compositional characteristics. In our algorithmic pipeline, we first coarse-grain the APT data into voxels, collect the composition statistics, and decompose it via clustering in composition space. The composition classification then enables the real-space segmentation via a density-based clustering algorithm, thus revealing the microstructure at voxel resolution. Our approach is demonstrated for a Sm-(Co,Fe)-Zr-Cu alloy. The alloy exhibits two precipitate phases with a plate-like, but intertwined morphology. The primary segmentation is further refined to disentangle these geometrically complex precipitates into individual plate-like parts by an unsupervised approach based on principle component analysis, or a U-Net-based semantic segmentation trained on the former. Following the composition and geometric analysis, detailed composition distribution and segregation effects relative to the predominant plate-like geometry can be readily mapped from the point cloud, without resorting to the voxel compositions.

Morphological Studies to Identify the Nasopalatine and Inferior Alveolar Nerve Using a Special Head and Neck MRI Coil.

OBJECTIVES: Procedures in oral and maxillofacial surgery bear a high risk of nerve damage. Three-dimensional imaging techniques can optimize surgical planning and help to spare nerves. The aim of this study was to investigate the diagnostic value of a 1.5 T magnetic resonance imaging (MRI) scanner with a dedicated dental signal amplification coil for the assessment of nerves in the oral cavity as compared with cone beam computed tomography (CBCT). METHODS: Based on 6 predefined criteria, the assessability of the inferior alveolar and nasopalatine nerves in CBCT and MRI with a dedicated 4-channel dental coil were compared in 24 patients. RESULTS: Compared with CBCT, MRI with the dental coil showed significantly better evaluability of the inferior alveolar nerve in the sagittal and axial plane and the nasopalatine nerve in the axial plane. In the sagittal plane; however, the assessability of the nasopalatine nerve was significantly better in CBCT as compared with MRI. Yet, pertaining to overall assessability, no significant differences between modalities were found. CONCLUSIONS: In this pilot study, it can be reported that 1.5- T MRI with a dedicated dental coil is at least equivalent, if not superior, to CBCT in imaging nerve structures of the stomatognathic system. CLINICAL RELEVANCE: Preoperative, 3-dimensional images are known to simplify and refine the planning and execution of operations in maxillofacial surgery. In contrast to computed tomography and CBCT, MRI does not cause radiation exposure while enabling visualization of all relevant hard and soft tissues and, therefore, holds an advantage over well-established techniques.

Understanding Alkali Contamination in Colloidal Nanomaterials to Unlock Grain Boundary Impurity Engineering.

Metal nanogels combine a large surface area, a high structural stability, and a high catalytic activity toward a variety of chemical reactions. Their performance is underpinned by the atomic-level distribution of their constituents, yet analyzing their subnanoscale structure and composition to guide property optimization remains extremely challenging. Here, we synthesized Pd nanogels using a conventional wet chemistry route, and a near-atomic-scale analysis reveals that impurities from the reactants (Na and K) are integrated into the grain boundaries of the poly crystalline gel, typically loci of high catalytic activity. We demonstrate that the level of impurities is controlled by the reaction condition. Based on ab initio calculations, we provide a detailed mechanism to explain how surface-bound impurities become trapped at grain boundaries that form as the particles coalesce during synthesis, possibly facilitating their decohesion. If controlled, impurity integration into grain boundaries may offer opportunities for designing new nanogels.

Peri-implant soft-tissue esthetic outcome after immediate implant placement in conjunction with xenogeneic acellular dermal matrix or connective tissue graft: A randomized controlled clinical study.

OBJECTIVES: This randomized comparative study evaluated the clinical esthetic outcome of the peri-implant mucosa following extraction and immediate implant placement in conjunction with anorganic bovine bone mineral (ABBM) and the use of a porcine acellular dermal matrix (pADM) versus an autogenous connective tissue graft (CTG) in the anterior maxilla. MATERIALS AND METHODS: Twenty patients (11 men, 9 women) with a mean age of 48,9 years (range 21-72) were included in the study and randomly assigned to either the test (pADM) or control group (CTG). They underwent extraction and immediate implant placement together with ABBM for socket grafting and either pADM or CTG for soft tissue augmentation. Twelve months after implant placement color measurements of the peri-implant mucosa and a reference tooth were performed using a spectophotometer and the color difference (ΔE) was calculated. The overall esthetic appearance of the peri-implant soft tissue was evaluated using the Pink Esthetic Score (PES). Statistical analysis was performed using Student's T-Test, the alpha was set to 0.05. RESULTS: All implants received osseointegration and were restored. The mean color difference of the peri-implant mucosa 1 year after surgery amounted ΔE 4.06 ± 1.6 for the test group (pADM) and ΔE 3.58 ± 1.36 mm for the control group (CTG), showing no statistically significant difference (p = 0.47). The mean PES of the pADM group was 11.4 ± 1.4 and for the CTG group 10.7 ± 1.5, showing no statistically significant difference (p = 0.29). CONCLUSION: Twelve months after surgery, a porcine acellular dermal matrix for soft tissue augmentation in conjunction with immediate implant placement showed no difference in the overall esthetic appearance regarding color match and Pink Esthetic Score in comparison to autogenous soft tissue graft. CLINICAL SIGNIFICANCE: Connective tissue grafts have become a standard in order to enhance the soft tissue quality and esthetic appearance in immediate implant placement. The use of new biomaterials like porcine acellular dermal matrices may avoid the need to harvest autogenous grafts resulting in simplified treatment and less postoperative morbidity.

Clinical performance of zirconia implant abutments luted to a titanium base - a retrospective cross-sectional study.

AIM: To evaluate the survival of implant-retained restorations fabricated on CAD/CAM-derived zirconia abutments luted to a titanium base. MATERIALS AND METHODS: 153 patients who received a total of 310 dental implants (Camlog Promote plus or Xive S) and all-ceramic restorations on yttria-stabilized tetragonal zirconia polycrystal (3Y-TZP) abutments luted to a titanium base during the last 10 years were included. Patients were examined for technical complications during routine visits. Crestal bone level changes were randomly analyzed based on periapical radiographs of 75 implants. RESULTS: Among the included 153 patients, 17 ceramic chippings (5.5%), 6 abutment loosenings (1.9%), and 2 abutment fractures (0.6%) were identified. The mean follow-up time was 4.7 years (standard deviation [SD]: 1.94), with a follow-up period of up to 10 years (maximum). Kaplan-Meier estimation resulted in a survival rate without complications of 91.6% for the restoration and 97.4% for the abutment. There was no statistically significant difference between the two implant systems, either between implant location or regarding the complication rate of the type of restoration. For the 75 implants included in the radiographic analysis, the mean bone level change was 0.384 mm (SD: 0.242, 95% CI: 0.315 to 0.452) for the Camlog implant system and 0.585 mm (SD: 0.366, 95% CI: 0.434 to 0.736) for the Xive system (P = 0.007). CONCLUSION: The results of the present retrospective study demonstrate acceptable clinical outcomes for zirconia abutments luted to a titanium base in combination with all-ceramic restorations. The assessed abutment design does not appear to have a negative impact on peri-implant hard tissue.

Mechanism of collective interstitial ordering in Fe-C alloys.

Collective interstitial ordering is at the core of martensite formation in Fe-C-based alloys, laying the foundation for high-strength steels. Even though this ordering has been studied extensively for more than a century, some fundamental mechanisms remain elusive. Here, we show the unexpected effects of two correlated phenomena on the ordering mechanism: anharmonicity and segregation. The local anharmonicity in the strain fields induced by interstitials substantially reduces the critical concentration for interstitial ordering, up to a factor of three. Further, the competition between interstitial ordering and segregation results in an effective decrease of interstitial segregation into extended defects for high interstitial concentrations. The mechanism and corresponding impact on interstitial ordering identified here enrich the theory of phase transitions in materials and constitute a crucial step in the design of ultra-high-performance alloys.

Impact of Water Coadsorption on the Electrode Potential of H-Pt(1 1 1)-Liquid Water Interfaces.

Density functional theory molecular dynamics simulations of H-covered Pt(111)-H_{2}O interfaces reveal that, in contrast to common understanding, H_{2}O coadsorption has a significant impact on the electrode potential of and plays a major role in determining the stability of H adsorbates under electrochemical conditions. Based on these insights, we explain the origin behind the experimentally observed upper limit of H coverage well below one monolayer and derive a chemically intuitive model for metal-water bonding that explains an unexpectedly large interaction between coadsorbed water and adsorbates.

Segmentation of Static and Dynamic Atomic-Resolution Microscopy Data Sets with Unsupervised Machine Learning Using Local Symmetry Descriptors.

We present an unsupervised machine learning approach for segmentation of static and dynamic atomic-resolution microscopy data sets in the form of images and video sequences. In our approach, we first extract local features via symmetry operations. Subsequent dimension reduction and clustering analysis are performed in feature space to assign pattern labels to each pixel. Furthermore, we propose the stride and upsampling scheme as well as separability analysis to speed up the segmentation process of image sequences. We apply our approach to static atomic-resolution scanning transmission electron microscopy images and video sequences. Our code is released as a python module that can be used as a standalone program or as a plugin to other microscopy packages.

Ab initio Description of Bond Breaking in Large Electric Fields.

Strong (10^{10} V/m) electric fields capable of inducing atomic bond breaking represent a powerful tool for surface chemistry. However, their exact effects are difficult to predict due to a lack of suitable tools to probe their associated atomic-scale mechanisms. Here we introduce a generalized dipole correction for charged repeated-slab models that controls the electric field on both sides of the slab, thereby enabling direct theoretical treatment of field-induced bond-breaking events. As a prototype application, we consider field evaporation from a kinked W surface. We reveal two qualitatively different desorption mechanisms that can be selected by the magnitude of the applied field.

Interplay of Chemistry and Faceting at Grain Boundaries in a Model Al Alloy.

The boundary between two crystal grains can decompose into arrays of facets with distinct crystallographic character. Faceting occurs to minimize the system's free energy, i.e., when the total interfacial energy of all facets is below that of the topologically shortest interface plane. In a model Al-Zn-Mg-Cu alloy, we show that faceting occurs at investigated grain boundaries and that the local chemistry is strongly correlated with the facet character. The self-consistent coevolution of facet structure and chemistry leads to the formation of periodic segregation patterns of 5-10 nm, or to preferential precipitation. This study shows that segregation-faceting interplay is not limited to bicrystals but exists in bulk engineering Al alloys and hence affects their performance.

Phonon Lifetimes throughout the Brillouin Zone at Elevated Temperatures from Experiment and Ab Initio.

We obtain phonon lifetimes in aluminium by inelastic neutron scattering experiments, by ab initio molecular dynamics, and by perturbation theory. At elevated temperatures significant discrepancies are found between experiment and perturbation theory, which disappear when using molecular dynamics due to the inclusion of full anharmonicity and the correct treatment of the multiphonon background. We show that multiple-site interactions are small and that local pairwise anharmonicity dominates phonon-phonon interactions, which permits an efficient computation of phonon lifetimes.

Discovery of Elusive K4 O6 , a Compound Stabilized by Configurational Entropy of Polarons.

Synthesis of elusive K4 O6 has disclosed implications of crucial relevance for new solid materials discovery. K4 O6 forms in equilibrium from K2 O2 and KO2 , in an all-solid state, endothermic reaction at elevated temperature, undergoing back reaction upon cooling to ambient conditions. This tells that the compound is stabilized by entropy alone. Analyzing possible entropic contributions reveals that the configurational entropy of "localized" electrons, i.e., of polaronic quasi-particles, provides the essential contribution to the stabilization. We corroborate this assumption by measuring the relevant heats of transformation and tracking the origin of entropy of formation computationally. These findings challenge current experimental and computational approaches towards exploring chemical systems for new materials by searching the potential energy landscape: one would fail in detecting candidates that are crucially stabilized by the configurational entropy of localized polarons.

Selective Solvent-Induced Stabilization of Polar Oxide Surfaces in an Electrochemical Environment.

The impact of an electrochemical environment on the thermodynamic stability of polar oxide surfaces is investigated for the example of ZnO(0001) surfaces immersed in water using density functional theory calculations. We show that solvation effects are highly selective: They have little effect on surfaces showing a metallic character, but largely stabilize semiconducting structures, particularly those that have a high electrostatic penalty in vacuum. The high selectivity is shown to have direct consequences for the surface phase diagram and explains, e.g., why certain surface structures could be observed only in an electrochemical environment.

First-Principles Approach to Model Electrochemical Reactions: Understanding the Fundamental Mechanisms behind Mg Corrosion.

Combining concepts of semiconductor physics and corrosion science, we develop a novel approach that allows us to perform ab initio calculations under controlled potentiostat conditions for electrochemical systems. The proposed approach can be straightforwardly applied in standard density functional theory codes. To demonstrate the performance and the opportunities opened by this approach, we study the chemical reactions that take place during initial corrosion at the water-Mg interface under anodic polarization. Based on this insight, we derive an atomistic model that explains the origin of the anodic hydrogen evolution.

Anomalous Phonon Lifetime Shortening in Paramagnetic CrN Caused by Spin-Lattice Coupling: A Combined Spin and Ab Initio Molecular Dynamics Study.

We study the mutual coupling of spin fluctuations and lattice vibrations in paramagnetic CrN by combining atomistic spin dynamics and ab initio molecular dynamics. The two degrees of freedom are dynamically coupled, leading to nonadiabatic effects. Those effects suppress the phonon lifetimes at low temperature compared to an adiabatic approach. The dynamic coupling identified here provides an explanation for the experimentally observed unexpected temperature dependence of the thermal conductivity of magnetic semiconductors above the magnetic ordering temperature.

Strain-Induced Asymmetric Line Segregation at Faceted Si Grain Boundaries.

The unique combination of atomic-scale composition measurements, employing atom probe tomography, atomic structure determination with picometer resolution by aberration-corrected scanning transmission electron microscopy, and atomistic simulations reveals site-specific linear segregation features at grain boundary facet junctions. More specific, an asymmetric line segregation along one particular type of facet junction core, instead of a homogeneous decoration of the facet planes, is observed. Molecular-statics calculations show that this segregation pattern is a consequence of the interplay between the asymmetric core structure and its corresponding local strain state. Our results contrast with the classical view of a homogeneous decoration of the facet planes and evidence a complex segregation patterning.

Impact of Chemical Fluctuations on Stacking Fault Energies of CrCoNi and CrMnFeCoNi High Entropy Alloys from First Principles.

Medium and high entropy alloys (MEAs and HEAs) based on 3d transition metals, such as face-centered cubic (fcc) CrCoNi and CrMnFeCoNi alloys, reveal remarkable mechanical properties. The stacking fault energy (SFE) is one of the key ingredients that controls the underlying deformation mechanism and hence the mechanical performance of materials. Previous experiments and simulations have therefore been devoted to determining the SFEs of various MEAs and HEAs. The impact of local chemical environment in the vicinity of the stacking faults is, however, still not fully understood. In this work, we investigate the impact of the compositional fluctuations in the vicinity of stacking faults for two prototype fcc MEAs and HEAs, namely CrCoNi and CrMnFeCoNi by employing first-principles calculations. Depending on the chemical composition close to the stacking fault, the intrinsic SFEs vary in the range of more than 150 mJ/m 2 for both the alloys, which indicates the presence of a strong driving force to promote particular types of chemical segregations towards the intrinsic stacking faults in MEAs and HEAs. Furthermore, the dependence of the intrinsic SFEs on local chemical fluctuations reveals a highly non-linear behavior, resulting in a non-trivial interplay of local chemical fluctuations and SFEs. This sheds new light on the importance of controlling chemical fluctuations via tuning, e.g., the annealing condition to obtain the desired mechanical properties for MEAs and HEAs.

Operando Phonon Studies of the Protonation Mechanism in Highly Active Hydrogen Evolution Reaction Pentlandite Catalysts.

Synthetic pentlandite (Fe4.5Ni4.5S8) is a promising electrocatalyst for hydrogen evolution, demonstrating high current densities, low overpotential, and remarkable stability in bulk form. The depletion of sulfur from the surface of this catalyst during the electrochemical reaction has been proposed to be beneficial for its catalytic performance, but the role of sulfur vacancies and the mechanism determining the reaction kinetics are still unknown. We have performed electrochemical operando studies of the vibrational dynamics of pentlandite under hydrogen evolution reaction conditions using 57Fe nuclear resonant inelastic X-ray scattering. Comparing the measured Fe partial vibrational density of states with density functional theory calculations, we have demonstrated that hydrogen atoms preferentially occupy substitutional positions replacing pre-existing sulfur vacancies. Once all vacancies are filled, the protonation proceeds interstitially, which slows down the reaction. Our results highlight the beneficial role of sulfur vacancies in the electrocatalytic performance of pentlandite and give insights into the hydrogen adsorption mechanism during the reaction.