Relative Structural Stability Research Articles

Structural evolution and bonding characteristics of neutral Cs2B n clusters

In this study, the unbiased crystal structure analysis by particle swarm optimisation (CALYPSO) combined with the density functional theory (DFT) method were used to perform a structure search for neutral Cs2B n (n = 1–12) clusters, as well as the corresponding global minimum of the potential energy surface were determined. The ground-state structures of the Cs2B n (n = 1–12) clusters have four types of geometries: planar, arch bridge, double pyramid, and shield shape. Subsequently, the relative stability of the ground-state structures was systematically analysed based on three effective rules, which indicates that the C7V Cs2B8 with a double pyramid structure has unusual stability. The results of the molecular orbitals (MOs) and density of states analysis (DOS) show that the B-2s and 2p atomic orbitals of Cs2B8 are the main components of MOs. In addition, from the results of adaptive natural density partitioning (AdNDP) and localised orbital locator (LOL), it can be seen that the excellent stability of Cs2B8 originates from the delocalised large π bonds with aromaticity and the s–p bonding of B–B. Our results reveal the structural growth mode of Cs2B n clusters and enrich the chemical bonding properties of boron-based clusters.

The Role of Structural Order in the Mechanism of Charge Transport across Tunnel Junctions with Various Iron‐Storing Proteins

In biomolecular electronics, the role of structural order in charge transport (CT) is poorly understood. It has been reported that the metal oxide cores of protein cages (e.g., iron oxide and ferrihydrite nanoparticles (NPs) present in ferritin and E2-LFtn, which is E2 protein engineered with an iron-binding sequence) play an important role in the mechanism of CT. At the same time, the NP core also plays a major role in the structural integrity of the proteins. This paper describes the role of structural order in CT across tunnel junctions by comparing three iron-storing proteins. They are (1) DNA binding protein from starved cells (Dps, diameter (∅) = 9 nm); (2) engineered archaeal ferritin (AfFtn-AA, ∅= 12 nm); and (3) engineered E2 of pyruvate dehydrogenase enzyme complex (E2-LFtn, ∅= 25 nm). Both holo-Dps and apo-Dps proteins undergo CT by coherent tunneling because their globular architecture and relative structural stability provide a coherent conduction pathway. In contrast, apo-AfFtn-AA forms a disordered structure across which charges have to tunnel incoherently, but holo-AfFtn-AA retains its globular structure and supports coherent tunneling. The large E2-LFtn always forms disordered structures across which charges incoherently tunnel regardless of the presence of the NP core. These findings highlight the importance of structural order in the mechanism of CT across biomolecular tunnel junctions.

Revisit the VEC criterion in high entropy alloys (HEAs) with high-throughput ab initio calculations: A case study with Al-Co-Cr-Fe-Ni system

Valence electron concentration (VEC) was treated as a useful parameter to predict the stability of solid solution phases. However, the available experimental data to support this criterion is far from enough. In the current study, the high-throughput ab initio modeling is applied to investigate the relative stability of FCC and BCC single crystals of the Al-Co-Cr-Fe-Ni high entropy alloys (HEAs) by using the special quasi-random structure (SQS) approach. The predictions start with pure elements of the Al-Co-Cr-Fe-Ni system and are continued with binaries, ternaries, and quaternary compositions, which come up with 180 compositions (360 structures). After that, the reliability of the VEC criterion is testified. The results show that the VEC criterion not only works for the stable structure but also works effectively for metastable structure when both FCC and BCC are not thermodynamic stable. However, it is found that the old VEC criterion proposed by Guo et al. fails to work effectively for compositions containing high concentrations of light-weight metals such as Al at VEC< 5. To solve this problem, the present work proposed a new VEC rule to define the stability of FCC and BCC structures at the ground state. With the implementation of the new VEC rule, the effectiveness of the VEC rule (EVEC) of both FCC and BCC structures is enhanced, especially for pure elements and binary compositions, indicating that this rule does not only work effectively for multicomponent systems but also works for low-order systems. • The Effectiveness of empirical VEC rule in the Al-Co-Cr-Fe-Ni system was systematically discussed. • The HT-ab initio calculations were performed to investigate the relative stability of FCC and BCC structure in the Al-Co-Cr-Fe-Ni system. • 180 compositions (360 structures) were investigated based on the Special Quasi-random Structures (SQS) method. • A new VEC criterion was proposed based on the results of the HT-calculations.

Dynamic stability of salt stable cowpea chlorotic mottle virus capsid protein dimers and pentamers of dimers

Intermediates of the self-assembly process of the salt stable cowpea chlorotic mottle virus (ss-CCMV) capsid can be modelled atomistically on realistic computational timescales either by studying oligomers in equilibrium or by focusing on their dissociation instead of their association. Our previous studies showed that among the three possible dimer interfaces in the icosahedral capsid, two are thermodynamically relevant for capsid formation. The aim of the current study is to evaluate the relative structural stabilities of the three different ss-CCMV dimers and to find and understand the conditions that lead to their dissociation. Long timescale molecular dynamics simulations at 300 K of the various dimers and of the pentamer of dimers underscore the importance of large contact surfaces on stabilizing the capsid subunits within an oligomer. Simulations in implicit solvent show that at higher temperature (350 K), the N-terminal tails of the protein units act as tethers, delaying dissociation for all but the most stable interface. The pentamer of dimers is also found to be stable on long timescales at 300 K, with an inherent flexibility of the outer protein chains.

Hyperspectral Monitoring of Powdery Mildew Disease Severity in Wheat Based on Machine Learning.

Powdery mildew has a negative impact on wheat growth and restricts yield formation. Therefore, accurate monitoring of the disease is of great significance for the prevention and control of powdery mildew to protect world food security. The canopy spectral reflectance was obtained using a ground feature hyperspectrometer during the flowering and filling periods of wheat, and then the Savitzky–Golay method was used to smooth the measured spectral data, and as original reflectivity (OR). Firstly, the OR was spectrally transformed using the mean centralization (MC), multivariate scattering correction (MSC), and standard normal variate transform (SNV) methods. Secondly, the feature bands of above four transformed spectral data were extracted through a combination of the Competitive Adaptive Reweighted Sampling (CARS) and Successive Projections Algorithm (SPA) algorithms. Finally, partial least square regression (PLSR), support vector regression (SVR), and random forest regression (RFR) were used to construct an optimal monitoring model for wheat powdery mildew disease index (mean disease index, mDI). The results showed that after Pearson correlation, two-band optimization combinations and machine learning method modeling comparisons, the comprehensive performance of the MC spectrum data was the best, and it was a better method for pretreating disease spectrum data. The transformed spectral data combined with the CARS–SPA algorithm was able to extract the characteristic bands more effectively. The number of bands screened was more than the number of bands extracted by the OR data, and the band positions were more evenly distributed. In comparison of different machine learning modeling methods, the RFR model performed the best (coefficient of determination, R2 = 0.741–0.852), while the SVR and PLSR models performed similarly (R2 = 0.733–0.836). Taken together, the estimation accuracy of spectral data transformation using the MC method combined with the RFR model (MC-RFR) was the highest, the model R2 was 0.849–0.852, and the root mean square error (RMSE) and the mean absolute error (MAE) ranged from 2.084 to 2.177 and 1.684 to 1.777, respectively. Compared with the OR combined with the RFR model (OR-RFR), the R2 increased by 14.39%, and the R2 of RMSE and MAE decreased by 23.9 and 27.87%. Also, the monitoring accuracy of flowering stage is better than that of grain filling stage, which is due to the relative stability of canopy structure in flowering stage. It can be seen that without changing the shape of the spectral curve, and that the use of MC to preprocess spectral data, the use of CARS and SPA algorithms to extract characteristic bands, and the use of RFR modeling methods to enhance the synergy between multiple variables, and the established model (MC-CARS-SPA-RFR) can better extract the covariant relationship between the canopy spectrum and the disease, thereby improving the monitoring accuracy of wheat powdery mildew. The research results of this study provide ideas and methods for realizing high-precision remote sensing monitoring of crop disease status.

Effect of magnetism on the atomic structure and properties of [formula omitted]5 grain boundaries in fcc Fe and fcc Ni

Grain boundaries (GB) play a major role in the mechanical properties of steel. We model here the most common Σ5 (210) and (310) [001] tilt boundaries in fcc Ni and fcc Fe which are main components of steel, paying particular attention to the effect of magnetism on the relative stabilities of the competing GB structures and on their main characteristics (excess volume, microstructure, stress profile, ...). To this aim we develop a new interatomic potential in the second moment approximation of the Tight-Binding scheme which accounts for magnetism in an effective manner in order to relax the structures at T=0K within quenched molecular dynamics simulations. Similar results are obtained for Fe and Ni, even though magnetic effects are found much more important in the former case. More precisely, magnetism significantly lowers the excess GB energy and volume, strongly reduces the stress in the GB region, and can even modify the microstructure in some cases. Finally a local analysis is proposed which allows to classify the relative stabilities of the different structures in terms of only a few given atomic sites.

First-Principles Modeling of Protein/Surface Interactions. Polyglycine Secondary Structure Adsorption on the TiO2 (101) Anatase Surface Adopting a Full Periodic Approach.

Computational modeling of protein/surface systems is challenging since the conformational variations of the protein and its interactions with the surface need to be considered at once. Adoption of first-principles methods to this purpose is overwhelming and computationally extremely expensive so that, in many cases, dramatically simplified systems (e.g., small peptides or amino acids) are used at the expenses of modeling nonrealistic systems. In this work, we propose a cost-effective strategy for the modeling of peptide/surface interactions at a full quantum mechanical level, taking the adsorption of polyglycine on the TiO2 (101) anatase surface as a test case. Our approach is based on applying the periodic boundary conditions for both the surface model and the polyglycine peptide, giving rise to full periodic polyglycine/TiO2 surface systems. By proceeding this way, the considered complexes are modeled with a drastically reduced number of atoms compared with the finite-analogous systems, modeling the polypeptide structures at the same time in a realistic way. Within our modeling approach, full periodic density functional theory calculations (including implicit solvation effects) and ab initio molecular dynamics (AIMD) simulations at the PBE-D2* theory level have been carried out to investigate the adsorption and relative stability of the different polyglycine structures (i.e., extended primary, β-sheet, and α-helix) on the TiO2 surface. It has been found that, upon adsorption, secondary structures become partially denatured because the peptide C═O groups form Ti-O═C dative bonds. AIMD simulations have been fundamental to identify these phenomena because thermal and entropic effects are of paramount importance. Irrespective of the simulated environments (gas phase and implicit solvent), adsorption of the α-helix is more favorable than that of the β-sheet because in the former, more Ti-O═C bonds are formed and the adsorbed secondary structure results less distorted with respect to the isolated state. Under the implicit water solvent, additionally, adsorbed β-sheet structures weaken with respect to their isolated states as the H-bonds between the strands are longer due to solvation effects. Accordingly, the results indicate that the preferred conformation upon adsorption is the α-helix over the β-sheet.

Theoretical study of cellulose II nanocrystals with different exposed facets

Derived from the most abundant natural polymer, cellulose nanocrystal materials have attracted attention in recent decades due to their chemical and mechanical properties. However, still unclear is the influence of different exposed facets of the cellulose nanocrystals on the physicochemical properties. Herein, we first designed cellulose II nanocrystals with different exposed facets, the hydroxymethyl conformations distribution, hydrogen bond (HB) analysis, as well as the relative structural stability of these models (including crystal facets {A, B, O} and Type-A models vary in size) are theoretically investigated. The results reveal that the HB network of terminal anhydroglucose depends on the adjacent chain’s contact sites in nanocrystals exposed with different facets. Compared to nanocrystals exposed with inclined facet, these exposed with flat facet tend to be the most stable. Therefore, the strategy of tuning exposed crystal facets will guide the design of novel cellulose nanocrystals with various physicochemical properties.

Atomic Structures of Single-Layer Nanoislands of Ni, Cu, Rh, Pd, Ag, Ir, Pt, Au Supported on Au(111) from Density Functional Theory Calculations

We have used density functional theory calculations to study the atomic structure of single-layer nanoislands of metal M (M=Ni, Cu, Rh, Pd, Ag, Ir, Pt, Au) supported on M(111) and Au(111) surfaces. Nanoislands of Cu, Pd, Ag, Pt, and Au have planar structures on Au(111), while nanoislands of Ni, Rh, and Ir are nonplanar. The calculations also show that nanoislands of Cu, Pd, Pt, and Au on Au(111) with a diameter below 3 nm can have one of several atomic structures. Two of these structures have atoms at the edges of the nanoislands located near bridge sites on Au(111), and the other structures have atoms at the edges and center of the nanoislands located near bridge sites. The relative stability of these atomic structures depends on the size and nature of the Au-supported nanoparticles. Our findings provided computational support for the work of Liao and Ya [J. Phys. Chem. C. 121 (2017) 19218–19225] reporting the formation of two phases of Pt nanoislands on Au(111). These findings also reveal the rich and complex atomic structures of small single-layer metal nanoislands supported on metal surfaces.

Structural stability and thermodynamic properties of (Y2O3)n (n = 1–15) clusters based on density functional theory

AbstractThe initial configuration of Yttrium oxide clusters (Y2O3)n (n = 1–15) was creatively constructed by combining artificial bee colony algorithm with density functional theory. The structures of large and medium‐sized yttrium oxide clusters with molecular number greater than 10 were established for the first time, and many new structures that are different from existing research have been obtained. Studies have shown that for small‐sized clusters, the atomic stacking structure is cage‐like, while for medium‐sized and large‐sized clusters, the composite trapezoidal structure and ellipsoid‐like structure are more stable. The nanoclusters tend to be stable as a whole, and the relative stability of the cluster structure is higher when n = 2, 4, 7, 9. The heat capacity (Cp), enthalpy change (H) and entropy (S) of (Y2O3)n (n = 1–15) clusters increase with the increase of temperature (T), and the vibration free energy (Gv) decreases with the increase of T.

Machine Learning-Based Screening of Highly Stable and Active Ternary Pt Alloys for Oxygen Reduction Reaction

Alloying Pt with other chemical elements is a promising method for achieving higher catalytic activity for oxygen reduction reaction in proton-exchange membrane fuel cells. However, dissolution of secondary elements in acidic solutions is one of the major reasons for the poor durability of such alloy catalysts. Therefore, it is desirable to identify adequate compositions that can stabilize Pt alloys while maintaining high activity. First-principles calculations are a useful tool to search for an adequate alloy composition because it can predict the stability and catalytic activity based on kinetic models with reasonable accuracy; however, a high computational cost is unavoidable because an enormous number of atomic configurations need to be considered to compare the relative stabilities of the surface structures. In this study, we propose a rational and efficient screening strategy to find active and stable ternary Pt alloys from 4140 Pt15MmNn (m + n = 5) compositions with over two million surface structures. To realize efficient and accurate predictions of stability and activity, a new screening scheme combining crystal graph convolutional neural network-based machine learning (ML) method and the first-principles calculations is proposed. The ML model allows us to reduce candidate structures efficiently from two million to thousands. The first-principles screening of the suggested structures provides 29 ternary Pt alloys that have stable and active Pt-skin surfaces. The proposed method can be used to efficiently explore various catalytic materials that require millions of expensive first-principles calculations.

Detection and Stabilization of a Previously Unknown Two-Dimensional (Pseudo)polymorph using Lateral Nanoconfinement.

We report on the detection and stabilization of a previously unknown two-dimensional (2D) pseudopolymorph of an alkoxy isophthalic acid using lateral nanoconfinement. The self-assembled molecular networks formed by the isophthalic acid derivative were studied at the interface between covalently modified graphite and an organic solvent. When self-assembled on graphite with moderate surface coverage of covalently bound aryl groups, a previously unknown metastable pseudopolymorph was detected. This pseudopolymorph, which was presumably "trapped" in between the surface bound aryl groups, underwent a time-dependent phase transition to the stable polymorph typically observed on pristine graphite. The stabilization of the pseudopolymorph was then achieved by using an alternative nanoconfinement strategy, where the domains of the pseudopolymorph could be formed and stabilized by restricting the self-assembly in nanometer-sized shallow compartments produced by STM-based nanolithography carried out on a graphite surface with a high density of covalently bound aryl groups. These experimental results are supported by molecular mechanics and molecular dynamics simulations, which not only provide important insight into the relative stabilities of the different structures, but also shed light onto the mechanism of the formation and stabilization of the pseudopolymorph under nanoscopic lateral confinement.

MOF‐Nanocomposite Mixed‐Matrix Membrane for Dual‐Luminescence Ratiometric Temperature Sensing

AbstractAccurate measurement of temperature is crucial in many branches of medicine, science, and engineering, and often requires temperature sensors that are noninvasive, of high accuracy, and can spatially resolve thermal fluctuations at the nanoscale. Here a new type of flexible and tailorable mixed‐matrix membranes (MMMs) is introduced, which feature dual‐emitting metal–organic framework (MOF)‐based nanocomposites embedded in polymer matrix, and its potential use in luminescence temperature sensing is evaluated. The as‐prepared “Cdots&amp;RB@ZIF‐82‐MMM” inherits the luminescence properties of the incorporated Cdots&amp;RB@zeolitic‐imidazolate‐framework (ZIF)‐82 nanocomposite and possesses the luminescence of both the blue‐emitting carbon dots (Cdots) and the green‐emitting rhodamine B (RB). Since the fluorescence resonance energy transfer between the two guest emitters is thermally correlated, the thermometric parameter (IC/IRB) of the Cdots&amp;RB@ZIF‐82‐MMM has excellent linear response in the physiological temperature range, with favorable relative sensitivity, spectral repeatability, and structural stability. The new ratiometric membranous thermometers proposed here should initiate further interest in luminescent MOF/polymer hybrids and their diverse sensing applications.

Mn- or Cu- substituted LaFeO[formula omitted]-based three-way catalysts: Highlighting different catalytically operating modes of La[formula omitted]Fe[formula omitted]M[formula omitted]O[formula omitted] (M=Cu, Mn)

The present work aims at presenting our investigations on the redox behaviour of Cu- or Mn-doped LaFeO3-based perovskite powders under three-way catalysis (TWC) relevant conditions. Two distinct La-deficient catalysts of generic formula La0.67Fe0.8Mn0.2O3 and La0.67Fe0.8Cu0.2O3 denoted as Mn-dLFO and Cu-dLFO, respectively, were prepared based on the conventional citrate complexation route and systematically investigated using complementary characterisation techniques. This study has made it possible to highlight fundamentally different structures. In Cu-dLFO, most Cu2+ cations are expelled from the LaFeO3 perovskite lattice in the form of a segregated CuO phase. On the other hand, in the case of Mn-dLFO, majority of Mn3+ cations are stabilised within the perovskite solid solution, while substantial iron exsolution in the form of an additional α-Fe2O3 phase was evidenced. The evolution of both catalysts during CO-TPR using operando Raman revealed the formation of polycyclic aromatic hydrocarbons (PAHs) besides the relative structural stability of the LaFeO3 lattice. The reduction of Mn3+ to Mn2+, indirectly suggested by Raman analysis, is further supported by a quasi-in situ XPS study. The latter also evidenced the reduction of CuO to metal copper to a large extent in Cu-dLFO. In addition, a share of the α-Fe2O3 phase present in Mn-dLFO is reduced to metal Fe0 during CO oxidation, and is fully re-oxidised upon NO reduction. Our investigation thus evidences that both copper and manganese sites in Cu-dLFO and Mn-dLFO, respectively, are redox-active centres upon CO oxidation/NO reduction with, however, varying operating modes underpinned by their fundamentally different structures.

Analysis of the relative stability of lithium halide crystal structures: Density functional theory and classical models.

All lithium halides exist in the rock salt crystal structure under ambient conditions. In contrast, common lithium halide classical force fields more often predict wurtzite as the stable structure. This failure of classical models severely limits their range of application in molecular simulations of crystal nucleation and growth. Employing high accuracy density functional theory (DFT) together with classical models, we examine the relative stability of seven candidate crystal structures for lithium halides. We give a detailed examination of the influence of DFT inputs, including the exchange-correlation functional, basis set, and dispersion correction. We show that a high-accuracy basis set, along with an accurate description of dispersion, is necessary to ensure prediction of the correct rock salt structure, with lattice energies in good agreement with the experiment. We also find excellent agreement between the DFT-calculated rock salt lattice parameters and experiment when using the TMTPSS-rVV10 exchange-correlation functional and a large basis set. Detailed analysis shows that dispersion interactions play a key role in the stability of rock salt over closely competing structures. Hartree-Fock calculations, where dispersion interactions are absent, predict the rock salt structure only for LiF, while LiCl, LiBr, and LiI are more stable as wurtzite crystals, consistent with radius ratio rules. Anion-anion second shell dispersion interactions overcome the radius ratio rules to tip the structural balance to rock salt. We show that classical models can be made qualitatively correct in their structural predictions by simply scaling up the pairwise additive dispersion terms, indicating a pathway toward better lithium halide force fields.

Application of Nanotechnology in Immunity against Infection

The immune system has a physiological defense function, protecting the body from infectious diseases. Antibiotics have long been one of the most important means to treat infectious diseases, but in recent years, with the emergence of more and more multidrug-resistant (MDR) bacteria, it has become urgent to find new ways or drugs to treat infectious diseases. Nanoparticles (NPs) have attracted extensive attention owing to the special properties within the particle size range of 1–100 nanometers. In addition, NPs also have special shape symmetry and relative structural stability. The emergence of nanotechnology has brought new light to the widespread existence of MDR by its different antibacterial mechanisms. In addition to antibiotic nanocarriers being able to improve the antibacterial effect of antibiotics, some NPs also have certain antibacterial effect. What is more interesting is that linking functional groups on the surface of NPS as coatings can improve the stability of the whole system and improve the biocompatibility. The present review overviews the development of antimicrobial agents, so as to better understand the causes and mechanisms of antibiotic resistance in most microbial species, and to better think and explore new strategies to solve the problem. At the same time, this review introduces how nanotechnology can be applied to anti-infection immunity and its practical application and advantages in the treatment of infection.

SxIP binding disrupts the constitutive homodimer interface of EB1 and stabilizes EB1 monomer

SxIP is a microtubule tip localizing signal found in many +TIP proteins that bind to the hydrophobic cavity of the C-terminal domain of end binding protein 1 (EB1) and then positively regulate the microtubule plus-end tracking of EBs. However, the exact mechanism of microtubule activation of EBs in the presence of SxIP signaling motif is not known. Here, we studied the effect of SxIP peptide on the native conformation of EB1 in solution. Using various NMR experiments, we found that SxIP peptide promoted the dissociation of natively formed EB1 dimer. We also discovered that I224A mutation of EB1 resulted in an unfolded C-terminal domain, which upon binding with the SxIP motif folded to its native structure. Molecular dynamics simulations also confirmed the relative structural stability of EB1 monomer in the SxIP bound state. Residual dipolar couplings and heteronuclear NOE analysis suggested that the binding of SxIP peptide at the C-terminal domain of EB1 decreased the dynamics and conformational flexibility of the N-terminal domain involved in EB1-microtubule interaction. The SxIP-induced disruption of the dimeric interactions in EB1, coupled with the reduction in conformational flexibility of the N-terminal domain of EB1, might facilitate the microtubule association of EB1.

Relative stability of Cu, Ag, and Pt at high pressures and temperatures from ab initio calculations

The paper presents ab initio studies into the relative stability of the crystalline structures of copper, silver, and platinum up to high pressures at $T\ensuremath{\ge}0$ K. Our calculations in quasiharmonic approximation suggest that not the fcc structure of Cu and Ag, but the body-centered cubic one, is thermodynamically most favorable at $P\ensuremath{\gtrsim}100$ GPa and $T&gt;3$ kK. The shock Hugoniot of Cu and Ag crosses the fcc-bcc phase boundary and the calculated transition pressures agree well with the result of recent laser shock experiments by Sharma et al. The advantage of the bcc structure comes from its softer low-frequency phonon modes and the smaller contribution of lattice vibrations to free energy at high temperatures, as compared to close-packed structures. The compression of platinum crystal also causes the $\mathrm{fcc}\ensuremath{\rightarrow}\mathrm{bcc}$ transition but at much higher pressures, $P&gt;1.4$ TPa.

Leber Congenital Amaurosis Due to GUCY2D Mutations: Longitudinal Analysis of Retinal Structure and Visual Function.

Gene augmentation therapy is being planned for GUCY2D-associated Leber congenital amaurosis (LCA). To increase our understanding of the natural history of GUCY2D-LCA, patients were evaluated twice with an interval of 4 to 7 years between visits using safety and efficacy outcome measures previously determined to be useful for monitoring this disorder. In this group of molecularly-identified LCA patients (n = 10; ages 7–37 years at first visit), optical coherence tomography (OCT) was used to measure foveal cone outer nuclear layer (ONL) thickness and rod ONL at a superior retinal locus. Full-field stimulus testing (FST) with chromatic stimuli in dark- and light-adapted states was used to assay rod and cone vision. Changes in OCT and FST over the interval were mostly attributable to inter-visit variability. There were no major negative changes in structure or function across the cohort and over the intervals studied. Variation in severity of disease expression between patients occurs; however, despite difficulties in quantifying structure and function in such seriously visually impaired individuals with nystagmus, the present work supports the use of OCT as a safety outcome and FST as an efficacy outcome in a clinical trial of GUCY2D-LCA. A wide age spectrum for therapy was confirmed, and there was relative stability of structure and function during a typical time interval for clinical trials.

Structural phase transitions of LaScO3 from first principles

We report a density functional theory study of LaScO3 perovskite using the SCAN meta-GGA potential. LaScO3 is of interest for applications such as hydrogen gas sensors, protonic ceramic fuel cells, and inorganic phosphors because of the useful electrical and optical properties it displays when doped, but little is known about its structural phase stability or phase transition behavior. We thus examine the relative stabilities of various candidate structures of LaScO3 and identify the likely transition sequence as a function of temperature. The low-temperature phase is confirmed to have an orthorhombic crystal structure with Pnma symmetry, with cooperative tilting of ScO6 octahedra about three pseudo-cubic axes, corresponding to Glazer tilt system a−b+a−. With increasing temperature, LaScO3 is predicted to undergo a second-order transition to a pseudo-tetragonal Imma structure (a−b0a−), followed by a first-order transition to a tetragonal I4/mcm structure (a0a0c−), and finally another second-order transition to the aristotype (cubic Pm3¯m; a0a0a0) structure below the melting point. The large difference in lattice enthalpy between the orthorhombic and cubic structures is consistent with the experimental difficulty in stabilizing the cubic structure at room temperature, although the results suggest other polymorphs may be accessible through synthesis at non-standard pressures or application of strain.