Refinement Of Parameters Research Articles

Force fields optimized against experimental data for large compound families using CombiFF: Validation considering non-target properties and polyfunctional compounds

The CombiFF scheme is a workflow for the automated calibration of force-field parameters against condensed-phase experimental data considering simultaneously entire classes of organic molecules. The main steps of this scheme are: (i) selection of a molecule family; (ii) enumeration of all isomers; (iii) query for experimental data; (iv) automatic construction of the molecular topologies; (v) iterative refinement of the force-field parameters considering the entire family. In two recent articles, CombiFF was applied to the design of GROMOS-compatible united-atom force fields for the saturated acyclic haloalkanes and for saturated acyclic compounds involving eight common chemical functional groups of oxygen and nitrogen. This calibration and the subsequent initial validation involved two limitations: (i) the experimental data considered was restricted to values for the pure-liquid density ρliq and the vaporization enthalpy ΔHvap of the compounds; (ii) beyond monofunctional compounds, the training set only involved homo-polyhaloalkanes (possibly mixing halogen types) in the first study, and homo-polyfunctional compounds of the considered oxygen or nitrogen functional groups (no mixing of different group types) in the second one. The goal of this article is to further test the accuracy of CombiFF-generated force fields by extending the validation to: (i) nine additional properties that were not used as optimization targets (pure-liquid thermodynamic, dielectric and transport properties, as well as solvation properties); (ii) hetero-polyfunctional molecules that were not included in the calibration and initial validation sets. The results for the nine additional properties show good agreement with experiment, except for the shear viscosity and the dielectric permittivity. There, larger discrepancies are observed, likely due to the united-atom representation adopted for the aliphatic groups and to the implicit treatment of electronic polarization effects. The results for the hetero-polyfunctional molecules also show reasonable agreement with experiment in terms of the monitored properties.

Detailed Microkinetics for the Oxidation of Exhaust Gas Emissions through Automated Mechanism Generation

Emissions from vehicles contain a variety of pollutants that must be either oxidized or reduced efficiently in the catalytic converter. Improvements to the catalyst require knowledge of the microkinetics, but the complexity of the exhaust gas mixture makes it challenging to identify the reaction network. This complexity was tackled by using the “Reaction Mechanism Generator” (RMG) to automatically generate microkinetic models for the oxidation of combustion byproducts from stoichiometric gasoline direct injection engines on Pt(111). The possibilities and the limitations encountered during the generation procedure are discussed in detail. A combination of first-principles-based mechanism construction and top-down parameter refinement allows a description of experimental results obtained by kinetic testing of a Pt/Al2O3 monolith under stoichiometric conditions. The study can serve as a blueprint for the usage of RMG for other challenging heterogeneously catalyzed reactions.

Parametric calibration study of fused filament fabrication printing with large nozzle diameter

The trend toward the scalability of fused filament fabrication requires strategies to reduce printing time. One way consists in using calibrated nozzles with larger diameters. However, the reduction in manufacturing time is accompanied by reduced printing resolution and changes in the control of the material’s viscous behavior. In this work, the parametric calibration was performed on a 1 mm diameter nozzle printing cubic models in polylactic acid. The procedure was divided into three steps: (i) identification of printing defects; (ii) systematic parametric study (based on Taguchi method); and (iii) interactive parametric refinement. The calibration of the 1 mm nozzle involved the analysis of six fused filament fabrication variables: layer thickness, extrusion temperature, extrusion multiplier, infill speed, perimeters speed, and first layer speed. Their effects were analyzed considering esthetic quality, dimensional and shape conformity, mass, and compression modulus variation of the parts. Despite the high degree of customization of fused filament fabrication printers, the results show that switching to a larger nozzle is not “plug-and-play”. The user needs to know the correlations between the printability of the material and the effects of the variables involved in slicing, especially extrusion multiplier and layer thickness. Both variables act directly on the main problem of printing with a 1 mm nozzle, controlling the extrusion volume with the best accommodation of the material between and within layers. The main contribution of the study highlights that large diameter nozzles can induce poorly distributed accumulations of excess material, which decreases the quality of surfaces, deforms parts, destabilizes dimensions, and disorganizes the mesostructure (reducing rigidity) of the models. Finally, the parameter refinement process defined a base configuration for future studies to improve 3D printing with 1 mm nozzles.

Bayesian data integration framework for the development of component-level fragilities derived from multiple post-disaster datasets

Widespread, disaster-related damage to buildings often results in severe economic, environmental, and societal impacts for the affected regions. The design of targeted mitigation strategies and policies to reduce disaster-related losses at community scale would benefit from building-specific, component-level loss estimations across regional building inventories under realistic hazard scenarios. However, such highly granular loss estimations face a unique challenge in sourcing reliable fragilities to project likely damage to specific buildings in a given inventory, especially for the case of wind-vulnerable structures. Notably, increased accessibility to post-disaster datasets, particularly those that standardize damage quantifications at the component-level, are quickly advancing the utility of this data for the development of observation-informed fragilities. In response, this paper offers a Bayesian data integration framework to guide the development of component-level fragilities derived from the fusion of multiple post-disaster datasets. This framework advances the utility of Bayesian approaches to fragility model updating for applications to high-granularity regional loss estimation by contributing subroutines that (1) generalize the process of sample building selection and (2) formalize the query and integration of heterogeneous open disaster data. These contributions then enable automated model updating of component-level fragilities, taking advantage of an object-oriented data model to facilitate efficient building data management across the framework’s subroutines. Such a Bayesian approach to fragility development not only allows for continuous refinement of model parameters as post-disaster data becomes available, but also creates opportunities for the framework to support fragility descriptions for classes of buildings that comprise smaller proportions of the building inventory, and are thus unlikely to have large sample sizes. The framework is applied to two case studies in the state of Florida, utilizing datasets produced after Hurricanes Michael and Irma to update fragility models for roof cover components in residential and institutional buildings. The case studies not only demonstrate the proposed framework’s rational approach to generating observation-informed fragilities in support of regional damage assessments, but also how this data-driven Bayesian approach can in turn inform hazard intensities and building classes to be targeted in data collection after future hurricanes to further refine the fragilities for use cases/damage measures/wind speeds that have limited observations.

Parametrics XRD Rietveld refinements of mechanically activated solid-state reactions in iron-brass alloy

The process of diffusion at the atomic level plays an important role in the formation of new phases. Iron-based Fe9Cu2Zn alloy was investigated by high-energy ball milling of elemental α-Fe powders and Cu7Zn2 brass alloy. The evolutions of structural, microstructural and mechanical properties of the obtained powders were studied by means of X-ray diffraction analysis using the parametric Rietveld refinement method which leads to higher precision of refined parameters. The solid state reaction pathways, occurring after 1 h of milling of (70 wt% α-Fe + 30 wt% Cu7Zn2) powder mixture, take place via demixing of metastable cubic complex γ-Cu5Zn8 in addition to cfc α-Cu7Zn2 and α-Cu25Zn8 phases and subsequently leading to the formation of new stable nanometric phases, namely cubic complex Γ-Fe4Zn9 and trigonal α-Cu3Zn with a stable grain size and good mechanical properties.

44 Boo – A unified integrated light curve analysis

Radial velocity (RV) data from Lu et al. (2001) were combined with light curve (LC) data from the Transiting Exoplanet Survey Satellite (TESS) in an integrated Wilson-Devinney analysis to yield fundamental parameters. Obtained were masses M 1 = 0.526 (5), M ʘ, and M 2 = 1.063 (7) M ʘ, stellar radii R1 = 0.65 (2) Rʘ, and R2 = 0.90 (1) Rʘ, and luminosities L1 = 0.40 (4) Lʘ and L2 = 0.62 (5) Lʘ. These are in reasonable agreement with the values from Hill et al. (1989). Additional analyses were carried out also using the same RV data but substituting, in turn, the LC datasets of Binnendijk (1955), Duerbeck (1978), Robb and Milone (1982) and Genet et al. (1982). While the four Earthbound LC datasets were of much lower precision than the satellite data, they still yielded reasonable agreement in the final parameters. Additionally, they yielded some insight as to the behaviour of the dark spot (on star 1) over some 75 years. The B and V light curve data of Duerbeck (1978) suggested that the unresolved companion is hot. An updated period study originally presented in Nelson et al. (2014) but now with a Light Time Effect (LiTE) fit is presented. Fifteen new times of minimum from the TESS data were added, requiring only a modest refinement of the LiTE parameters. The intrinsic rate of period change (that is, with the LiTE component removed) is dP/dt = 1.80 (20) x 10−7 seconds/year. If dP/dt can be attributed to conservative mass exchange, the rate would be dM1/dt = -2.33 (26) x 10−7 Mʘ/year. When the fundamental parameters for each star were added to the Log L vs Log T plot for EW-type binaries from Yakut and Eggleton (2005), the results suggested that star 1 of the W-type binary is under-luminous, while the cooler but larger secondary is somewhat evolved. Both are in a marginal contact, typical of W-type eclipsing binaries.

Nanoscale physical parameters of source rocks identified by atomic force microscopy: A review

The refinement of nanoscale physical parameters of source rocks has benefitted from continuous innovations in technology and methods. Traditional methods for detecting reservoir physical properties are limited by the properties of the instruments. Atomic force microscopy (AFM) provides new methods and approaches for furthering our understanding and exploring the nanoscale world. Its wide range of applications and gradually developed multiscenario application modes make it an ideal tool for the characterization of nanoscale physical properties of source rocks (coal, shale, mudstone, sandstone, etc.). We highlight the advantages of AFM in regard to performing nondestructive 3D imaging and mechanical property measurements with nanoscale resolution in any desired environment (air, vacuum, liquid). The limitations of AFM applied to source rocks are also summarized. The process has great potential in micro/nanopore characterization, surface morphology characterization, in situ micromechanical property acquisition, wettability research, and so on. The gradual development and improvement of this new model will expand new methods, bring enlightenment to basic research on unconventional oil and gas resources, and provide a scientific basis for the exploration and development of unconventional oil and gas resources.

Compliance of Fasteners in Metal-Composite Joints

The greatest difficulties in creating a new structure or upgrading an old one are associated with designing joints and connecting parts of the structure, especially composite and metal ones. Nowadays, the problem of designing and improving such joints is timely and is being actively studied so that the best solutions are found. The article presents the research carried out to determine the main parameters of elements of mechanical joints made of polymer composite materials, as factors affecting the requirements for precision of connection compliance estimation. There has been found the influence of the number of fastener rows on estimating the maximum forces which act in the joint, as well as the influence of the ratio of the connection compliance to the compliance of the part. A field of possible states of the joint has been built. Within the field, the following areas have been identified: the area of high sensitivity to precision of estimating the parameters of the joint elements, requiring experimental confirmation and more accurate models; the area of average sensitivity of the joint to precision of estimating the parameters of its elements, permitting the use of known dependences; and the area of low sensitivity, where simplified models can be used. In the course of the developed model testing, joint samples were tested to evaluate the force connection compliance, and a reference variant was calculated using the Douglas formula. The reference variant of the joint sample was chosen based on the principle of equal compliances of the parts to be joined, presented by a series of samples assembled from a composite package of 80 layers and two surface layers made of 3.98 mm-thick steel. The parts were connected with steel bolts with a diameter of 6 and 8 mm. Numerically, the ratio of the connection compliance to the part compliance is 85...96 for the experimental data, and 9...10 for the calculated data. This indicated that the joint was in the transition area between high and medium sensitivity of the joint to the accuracy of compliance estimation, which requires continuous refinement of the connection parameters.

Automation of AMOEBA polarizable force field for small molecules: Poltype 2.

A next-generation protocol (Poltype 2) has been developed which automatically generates AMOEBA polarizable force field parameters for small molecules. Both features and computational efficiency have been drastically improved. Notable advances include improved database transferability using SMILES, robust torsion fitting, non-aromatic ring torsion parameterization, coupled torsion-torsion parameterization, Van der Waals parameter refinement using ab initio dimer data and an intelligent fragmentation scheme that produces parameters with dramatically reduced ab initio computational cost. Additional improvements include better local frame assignment for atomic multipoles, automated formal charge assignment, Zwitterion detection, smart memory resource defaults, parallelized fragment job submission, incorporation of Psi4 quantum package, ab initio error handling, ionization state enumeration, hydration free energy prediction and binding free energy prediction. For validation, we have applied Poltype 2 to ~1000 FDA approved drug molecules from DrugBank. The ab initio molecular dipole moments and electrostatic potential values were compared with Poltype 2 derived AMOEBA counterparts. Parameters were further substantiated by calculating hydration free energy (HFE) on 40 small organic molecules and were compared with experimental data, resulting in an RMSE error of 0.59 kcal/mol. The torsion database has expanded to include 3543 fragments derived from FDA approved drugs. Poltype 2 provides a convenient utility for applications including binding free energy prediction for computational drug discovery. Further improvement will focus on automated parameter refinement by experimental liquid properties, expansion of the Van der Waals parameter database and automated parametrization of modified bio-fragments such as amino and nucleic acids.

Biomass-derived carbon doping to enhance the current carrying capacity and flux pinning of an isotopic Mg11B2 superconductor

Low activation isotopic boron (11B) based magnesium diboride (Mg11B2) superconductors doped with biomass-derived activated carbon were synthesized using 11B and magnesium powder via solid-state reaction. The effect of carbon doping on the lattice structure and superconducting properties of Mg11B2 bulks were evaluated using X-ray powder diffraction, high resolution transmission electron microscopy, scanning electron microscopy and magnetization measurements. Precise refinement of structural parameters indicates successful substitution of carbon in Mg11B2 bulks. The critical current density (Jc) of carbon doped Mg11B2 synthesized at 650 °C was enhanced more than two times compared with the pure Mg11B2 bulk. Similar improvement was observed for the Mg11B2 bulks heat-treated at 800 °C. This enhancement is due to successful substitution of biomass-derived carbon with high surface area into Mg11B2 lattice. The flux pinning mechanism of pure and doped Mg11B2 bulks were investigated using the Dew-Hughes model. This study provides information regarding enhancement of the Jc of low activation Mg11B2 superconductors suitable for next-generation fusion magnets.

WAYS TO EFFECTIVELY ADDRESS PROBLEMS EXISTING IN THE URBAN PASSENGER TRANSPORT SYSTEM

At present, public transport needs to be managed using the different models, which will take into account health problems, passenger transport problems, refinement of technical parameters of buses and their adaptation to urban operating conditions, which would be one of the preventive measures in the context of combating the coronavirus pandemic. The article discusses the issues of optimizing the routeing scheme of buses and minibuses in the conditions of a three-level transport network in large cities. Measures for the performance of the city bus routes have been developed. It has been established that the qualification of a driver and the selection of urban passenger vehicles are central issues in terms of fuel efficiency and reducing the number of harmful substances in exhaust gases.

Accurately Quantifying Stress during Metal Halide Perovskite Thin Film Formation.

The role of strain in metal halide perovskite (MHP) solar cells is still under investigation, showing both beneficial and detrimental effects on the device performance and stability. One crucial component to elucidating the impact of strain in the MHP absorber is a robust method of quantifying the amount of strain in the material. Here, we present a parametric refinement approach based on grazing incidence wide-angle X-ray scattering and demonstrate its use on quantifying strain during thermal annealing and subsequent cooling as a function of substrate and processing route. We use the analysis to reveal the impact of the cubic-to-tetragonal phase transition during cooling on the material's strain and discuss texture formation as a potential strain-relief mechanism. Thereby we present both a robust approach to quantify strain in MHPs and potential mechanisms to control strain in the film, opening the path for further investigations of strain in MHPs.

Identification of parameters of structure of soil curvilinear massifs by numerical methods of complex analysis

The works by specialists in electrical tomography usually model soil masses as a two-dimensional single-connected domain, the boundary of which consists of a horizon line and some «deep» line with a constant potential value on it. At the same time, the latter is set very approximately because of the «absence» of charges in remote (deep) areas. To avoid such simplification, the author proposes to solve the corresponding model problem in a relatively simple domain through its subsequent conformal mapping onto studied physical environment with a complex structure. The latter is carried out using some fractional-rational function. Whereas to simulate the movement of charges, numerical complex analysis methods are generally used. In this case, common simplification regarding the «point-like» nature of the applied quasipotential sections is rejected, and the distribution of current density on the last is taken into account. The studied medium, for example, is assumed to be given in the form of a function of local bursts of homogeneities. Image reconstruction is conducted during alternate iterative solving of problems on the construction of a range of fields of current densities and refinement of parameters of conductivity coefficient. The latter is implemented out under the minimization of the functional of residuals between discrete (known) measurements of potential and stream functions on the surface of the soil mass and the corresponding calculated ones, using the ideas of regularization. Non-use of information (due to the high complexity of obtaining it) about the distribution of voltage and current in deep areas generates a certain mathematical uncertainty. However, its influence on the results of image reconstruction in the near-surface areas is insignificant. Numerical experiments were performed and analyzed. For the given examples, the conductivity coefficient on the «lion’s share» of the medium was found with a small residual. Whereas the coordinates of the identified bursts, in comparison with a priori known ones, shifted towards the surface of soil mass. This is explained both by the peculiarities of the construction of the subproblem of identification of the conductivity coefficient in the absence of boundary conditions at deep sections and the existing significant quasiconformity residuals. In the future, these shortcomings can be «eliminated» by implementing an additional intermediate conformal mapping onto a circle and applying «fictitious orthogonalization» in the vicinity of the «junction» points of boundary streamlines and equipotential lines.

A Test and Refinement of Folding Free Energy Nearest Neighbor Parameters for RNA Including N6-Methyladenosine

RNA folding free energy change parameters are widely used to predict RNA secondary structure and to design RNA sequences. These parameters include terms for the folding free energies of helices and loops. Although the full set of parameters has only been traditionally available for the four common bases and backbone, it is well known that covalent modifications of nucleotides are widespread in natural RNAs. Covalent modifications are also widely used in engineered sequences. We recently derived a full set of nearest neighbor terms for RNA that includes N6-methyladenosine (m6A). In this work, we test the model using 98 optical melting experiments, matching duplexes with or without N6-methylation of A. Most experiments place RRACH, the consensus site of N6-methylation, in a variety of contexts, including helices, bulge loops, internal loops, dangling ends, and terminal mismatches. For matched sets of experiments that include either A or m6A in the same context, we find that the parameters for m6A are as accurate as those for A. Across all experiments, the root mean squared deviation between estimated and experimental free energy changes is 0.67 kcal/mol. We used the new experimental data to refine the set of nearest neighbor parameter terms for m6A. These parameters enable prediction of RNA secondary structures including m6A, which can be used to model how N6-methylation of A affects RNA structure.

Ambiguous structure determination from powder data: four different structural models of 4,11-di-fluoro-quinacridone with similar X-ray powder patterns, fit to the PDF, SSNMR and DFT-D.

Four different structural models, which all fit the same X-ray powder pattern, were obtained in the structure determination of 4,11-di-fluoro-quinacridone (C20H10N2O2F2) from unindexed X-ray powder data by a global fit. The models differ in their lattice parameters, space groups, Z, Z', molecular packing and hydrogen bond patterns. The molecules form a criss-cross pattern in models A and B, a layer structure built from chains in model C and a criss-cross arrangement of dimers in model D. Nevertheless, all models give a good Rietveld fit to the experimental powder pattern with acceptable R-values. All molecular geometries are reliable, except for model D, which is slightly distorted. All structures are crystallochemically plausible, concerning density, hydrogen bonds, intermolecular distances etc. All models passed the checkCIF test without major problems; only in model A a missed symmetry was detected. All structures could have probably been published, although 3 of the 4 structures were wrong. The investigation, which of the four structures is actually the correct one, was challenging. Six methods were used: (1) Rietveld refinements, (2) fit of the crystal structures to the pair distribution function (PDF) including the refinement of lattice parameters and atomic coordinates, (3) evaluation of the colour, (4) lattice-energy minimizations with force fields, (5) lattice-energy minimizations by two dispersion-corrected density functional theory methods, and (6) multinuclear CPMAS solid-state NMR spectroscopy (1H, 13C, 19F) including the comparison of calculated and experimental chemical shifts. All in all, model B (perhaps with some disorder) can probably be considered to be the correct one. This work shows that a structure determination from limited-quality powder data may result in totally different structural models, which all may be correct or wrong, even if they are chemically sensible and give a good Rietveld refinement. Additionally, the work is an excellent example that the refinement of an organic crystal structure can be successfully performed by a fit to the PDF, and the combination of computed and experimental solid-state NMR chemical shifts can provide further information for the selection of the most reliable structure among several possibilities.

Atlas-ISTN: Joint segmentation, registration and atlas construction with image-and-spatial transformer networks.

Deep learning models for semantic segmentation are able to learn powerful representations for pixel-wise predictions, but are sensitive to noise at test time and may lead to implausible topologies. Image registration models on the other hand are able to warp known topologies to target images as a means of segmentation, but typically require large amounts of training data, and have not widely been benchmarked against pixel-wise segmentation models. We propose the Atlas Image-and-Spatial Transformer Network (Atlas-ISTN), a framework that jointly learns segmentation and registration on 2D and 3D image data, and constructs a population-derived atlas in the process. Atlas-ISTN learns to segment multiple structures of interest and to register the constructed atlas labelmap to an intermediate pixel-wise segmentation. Additionally, Atlas-ISTN allows for test time refinement of the model's parameters to optimize the alignment of the atlas labelmap to an intermediate pixel-wise segmentation. This process both mitigates for noise in the target image that can result in spurious pixel-wise predictions, as well as improves upon the one-pass prediction of the model. Benefits of the Atlas-ISTN framework are demonstrated qualitatively and quantitatively on 2D synthetic data and 3D cardiac computed tomography and brain magnetic resonance image data, out-performing both segmentation and registration baseline models. Atlas-ISTN also provides inter-subject correspondence of the structures of interest.

Order-Disorder in the Structures of Lithium Aluminosilicate Minerals by XRD and Multinuclear NMR

The crystal structures of the lithium aluminosilicate minerals of the Li2O–Al2O3–SiO2 (LAS) system (Li1−xAl1−xSi1+xO4 system for 0.0 ≤ x ≤ 1.0), and bikitaite were determined by X-ray diffraction (XRD) in literature, suggesting several possible lattice models for each of the crystallized phases, because of the intrinsic experimental difficulties of this technique. Here, we correlate powder XRD patterns with Rietveld refinement of cell parameters and magic angle sample spinning multinuclear magnetic resonance (NMR) spectra, including 29Si, 27Al, 7Li, and 6Li spectroscopy at 7.05 T, 9.4 T, and 20 T. The aim is to select appropriate lattice models from short-range order schemes in the lithium aluminosilicate phases, from natural minerals and synthetic crystals from the crystallization of amorphous gel precursors by a ceramic route and also by hydrothermal high-pressure experiments. Solid solutions were found in α-quartz and α-cristobalite up to x ≥ 0.75, and in β-eucryptite and β-spodumene for 0.0 ≤ x ≤ 1.0, when the ceramic synthesis is at work. The local structures of these intermediate members of the β-eucryptite and β-spodumene solid-solution series have 29Si NMR spectra consistent with the Loewenstein’s rule, i.e., they have short-range order but are strictly non-periodic structures. However, β-eucryptite LiAlSiO4 end-member has a short-range structure compatible with the long-range order of the P6422 symmetry, when the crystallization is produced at hydrothermal conditions. The local structure of α-spodumene LiAlSi2O6 is consistent with the C2/c model. α-eucryptite LiAlSiO4 shows a short-range structure as that suggested by the R-3 lattice model. Petalite LiAlSi4O10 has a local structure compatible with the P2/a space group. Finally, the 29Si NMR spectra of bikitaite LiAlSi2O6·H2O indicate a short-range structure well-suited with the P1 symmetry. These results are consistent with the Ostwald‘s rule of stages, forming a order-disorder sequence of increasing long-range order from the starting fully disordered solid gels, through crystalline pseudoperiodic structures in non-stoichiometric solid solution crystals that respect the Lowenstein’s rule, up to fully ordered crystals with short-range structures from NMR close to the long-range structures by XRD, as in the stoichiometric compounds found in some natural minerals.

Increasing application of pediatric physiologically based pharmacokinetic models across academic and industry organizations.

There has been a significant increase in the use of physiologically based pharmacokinetic (PBPK) models during the past 20 years, especially for pediatrics. The aim of this study was to give a detailed overview of the growth and areas of application of pediatric PBPK (P‐PBPK) models. A total of 181 publications and publicly available regulatory reviews were identified and categorized according to year, author affiliation, platform, and primary application of the P‐PBPK model (in clinical settings, drug development or to advance pediatric model development in general). Secondary application areas, including dose selection, biologics, and drug interactions, were also assessed. The growth rate for P‐PBPK modeling increased 33‐fold between 2005 and 2020; this was mainly attributed to growth in clinical and drug development applications. For primary applications, 50% of articles were classified under clinical, 18% under drug development, and 33% under model development. The most common secondary applications were dose selection (75% drug development), pharmacokinetic prediction and covariate identification (47% clinical), and model parameter identification (68% model development), respectively. Although population PK modeling remains the mainstay of approaches supporting pediatric drug development, the data presented here demonstrate the widespread application of P‐PBPK models in both drug development and clinical settings. Although applications for pharmacokinetic and drug–drug interaction predictions in pediatrics is advocated, this approach remains underused in areas such as assessment of pediatric formulations, toxicology, and trial design. The increasing number of publications supporting the development and refinement of the pediatric model parameters can only serve to enhance optimal use of P‐PBPK models.

Structure and magnetic properties of RE4Ni2Mg3 with RE=Y, Tb−Tm and Lu – New representatives of the Ru4B2Al3 type

AbstractThe intermetallic compounds RE4Ni2Mg3 with RE=Y, Tb−Tm and Lu were synthesized from the elements in sealed tantalum ampules in a high‐frequency furnace and characterized by powder X‐ray diffraction. The RE4Ni2Mg3 phases crystallize with a site occupancy variant of the tetragonal Ru4B2Al3 type structure, space group P4/mmm. The structures of Tm4.21(1)Ni2Mg2.79(1), Lu4.28(1)Ni2Mg2.72(1) and Lu4.41(1)Ni2Mg2.59(1) were refined from single crystal X‐ray diffractometer data. Refinements of the occupancy parameters indicated different degrees of RE/Mg mixing on several Wyckoff positions. The RE4Ni2Mg3 structures are simple intergrowth variants of CsCl and AlB2 related slabs with distorted Ni@RE6 trigonal prisms and Mg@RE8 distorted cubes. Temperature dependent magnetic susceptibility studies reveal Pauli paramagnetism for Y4Ni2Mg3 and Lu4Ni2Mg3. The compounds with RE=Dy, Ho, Er and Tm are Curie‐Weiss paramagnets that order antiferromagnetically between 17.1(1) (RE=Dy) and 6.0(1) K (RE=Tm). The antiferromagnetic ground states are substantiated by metamagnetic transitions.

On the parameter refinement of inflated exoplanets with large radius uncertainty based on TESS observations

We revisited ten known exoplanetary systems using publicly available data provided by the Transiting Exoplanet Survey Satellite (TESS). The sample presented in this work consists of short period transiting exoplanets, with inflated radii and large reported uncertainty on their planetary radii. The precise determination of these values is crucial in order to develop accurate evolutionary models and understand the inflation mechanisms of these systems. Aiming to evaluate the planetary radius measurement, we made use of the planet-to-star radii ratio, a quantity that can be measured during a transit event. We fit the obtained transit light curves of each target with a detrending model and a transit model. Furthermore, we used emcee, which is based on a Markov chain Monte Carlo approach, to assess the best fit posterior distributions of each system parameter of interest. We refined the planetary radius of WASP-140 b by approximately 12%, and we derived a better precision on its reported asymmetric radius uncertainty by approximately 86% and 67%. We also refined the orbital parameters of WASP-120 b by 2$\sigma$. Moreover, using the high-cadence TESS datasets, we were able to solve a discrepancy in the literature, regarding the planetary radius of the exoplanet WASP-93 b. For all the other exoplanets in our sample, even though there is a tentative trend that planetary radii of (near-) grazing systems have been slightly overestimated in the literature, the planetary radius estimation and the orbital parameters were confirmed with independent observations from space, showing that TESS and ground-based observations are overall in good agreement.