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1. Thermodynamic Properties as a Function of Temperature of AlMoNbV, NbTaTiV, NbTaTiZr, AlNbTaTiV, HfNbTaTiZr, and MoNbTaVW Refractory High-Entropy Alloys from First-Principles Calculations

   https://doi.org/10.3390/solids4040021  

   Moreno, Danielsen E; Hargather, Chelsey Z (December 2023, Solids)

   Refractory high-entropy alloys (RHEAs) are strong candidates for use in high-temperature engineering applications. As such, the thermodynamic properties as a function of temperature for a variety of RHEA systems need to be studied. In the present work, thermodynamic quantities such as entropy, enthalpy, heat capacity at constant volume, and linear thermal expansion are calculated for three quaternary and three quinary single-phase, BCC RHEAs: AlMoNbV, NbTaTiV, NbTaTiZr, AlNbTaTiV, HfNbTaTiZr, and MoNbTaVW. First-principle calculations based on density functional theory are used for the calculations, and special quasirandom structures (SQSs) are used to represent the random solid solution nature of the RHEAs. A code for the finite temperature thermodynamic properties using the Debye-Grüneisen model is written and employed. For the first time, the finite temperature thermodynamic properties of all 24 atomic configuration permutations of a quaternary RHEA are calculated. At most, 1.7% difference is found between the resulting properties as a function of atomic configuration, indicating that the atomic configuration of the SQS has little effect on the calculated thermodynamic properties. The behavior of thermodynamic properties among the RHEAs studied is discussed based on valence electron concentration and atomic size. Among the quaternary RHEAs studied, namely AlMoNbV, NbTaTiZr, and NbTaTiV, it is found that the presence of Zr contributes to higher entropy. Additionally, at lower temperatures, Zr contributes to higher heat capacity and thermal expansion compared to the alloys without Zr, possibly due to its valence electron concentration. At higher temperatures, Al contributes to higher heat capacity and thermal expansion, possibly due its ductility. Among the quinary systems, the presence of Mo, W, and/or V causes the RHEA to have a lower thermal expansion than the other systems studied. Finally, when comparing the systems with the NbTaTi core, the addition of Al increases thermal expansion, while the removal of Zr lowers the thermal expansion. 

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2. Machine learned coarse-grained protein force-fields: Are we there yet?

   https://doi.org/10.1016/j.sbi.2023.102533  

   Durumeric, Aleksander EP; Charron, Nicholas E; Templeton, Clark; Musil, Félix; Bonneau, Klara; Pasos-Trejo, Aldo S; Chen, Yaoyi; Kelkar, Atharva; Noé, Frank; Clementi, Cecilia (April 2023, Current Opinion in Structural Biology)

   The successful recent application of machine learning methods to scientific problems includes the learning of flexible and accurate atomic-level force-fields for materials and biomolecules from quantum chemical data. In parallel, the machine learning of force-fields at coarser resolutions is rapidly gaining relevance as an efficient way to represent the higherbody interactions needed in coarse-grained force-fields to compensate for the omitted degrees of freedom. Coarsegrained models are important for the study of systems at time and length scales exceeding those of atomistic simulations. However, the development of transferable coarse-grained models via machine learning still presents significant challenges. Here, we discuss recent developments in this field and current efforts to address the remaining challenges. 

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3. Modified Polynomial Chaos Expansion for Efficient Uncertainty Quantification in Biological Systems

   https://doi.org/10.3390/applmech1030011  

   Son, Jeongeun; Du, Dongping; Du, Yuncheng (September 2020, Applied Mechanics)

   null (Ed.)

   Uncertainty quantification (UQ) is an important part of mathematical modeling and simulations, which quantifies the impact of parametric uncertainty on model predictions. This paper presents an efficient approach for polynomial chaos expansion (PCE) based UQ method in biological systems. For PCE, the key step is the stochastic Galerkin (SG) projection, which yields a family of deterministic models of PCE coefficients to describe the original stochastic system. When dealing with systems that involve nonpolynomial terms and many uncertainties, the SG-based PCE is computationally prohibitive because it often involves high-dimensional integrals. To address this, a generalized dimension reduction method (gDRM) is coupled with quadrature rules to convert a high-dimensional integral in the SG into a few lower dimensional ones that can be rapidly solved. The performance of the algorithm is validated with two examples describing the dynamic behavior of cells. Compared to other UQ techniques (e.g., nonintrusive PCE), the results show the potential of the algorithm to tackle UQ in more complicated biological systems. 

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4. Progress on Meson-Baryon Scattering

   https://doi.org/10.22323/1.396.0170  

   C. Morningstar; J. Bulava; A. Hanlon; B. Hörz; D. Mohler; A. Nicholson; S. Skinner; A. Walker-Loud (January 2021, 38th International Symposium on Lattice Field Theory, LATTICE2021 26th-30th July, 2021)

   Progress in computing various meson-baryon scattering amplitudes is presented on a single en- semble from the Coordinated Lattice Simulations (CLS) consortium with m π = 200 MeV and Nf = 2 + 1 dynamical fermions. The finite-volume Lüscher approach is employed to determine the lowest few partial waves from ground- and excited-state energies computed from correla- tion matrices rotated in a single pivot using a generalized eigenvector solution. This analysis requires evaluating matrices of correlation functions between single- and two-hadron interpolat- ing operators which are projected onto definite spatial momenta and finite-volume irreducible representations. The stochastic LapH method is used to estimate all needed quark propagators. Preliminary results are presented for I = 1/2, 3/2 N π amplitudes including the ∆(1232) resonance and the I = 0 S-wave amplitude with unit strangeness relevant for the Λ(1405). 

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5. Reduced Order Models for the Quasi-Geostrophic Equations: A Brief Survey

   https://doi.org/10.3390/fluids6010016  

   Mou, Changhong; Wang, Zhu; Wells, David R.; Xie, Xuping; Iliescu, Traian (January 2021, Fluids)

   null (Ed.)

   Reduced order models (ROMs) are computational models whose dimension is significantly lower than those obtained through classical numerical discretizations (e.g., finite element, finite difference, finite volume, or spectral methods). Thus, ROMs have been used to accelerate numerical simulations of many query problems, e.g., uncertainty quantification, control, and shape optimization. Projection-based ROMs have been particularly successful in the numerical simulation of fluid flows. In this brief survey, we summarize some recent ROM developments for the quasi-geostrophic equations (QGE) (also known as the barotropic vorticity equations), which are a simplified model for geophysical flows in which rotation plays a central role, such as wind-driven ocean circulation in mid-latitude ocean basins. Since the QGE represent a practical compromise between efficient numerical simulations of ocean flows and accurate representations of large scale ocean dynamics, these equations have often been used in the testing of new numerical methods for ocean flows. ROMs have also been tested on the QGE for various settings in order to understand their potential in efficient numerical simulations of ocean flows. In this paper, we survey the ROMs developed for the QGE in order to understand their potential in efficient numerical simulations of more complex ocean flows: We explain how classical numerical methods for the QGE are used to generate the ROM basis functions, we outline the main steps in the construction of projection-based ROMs (with a particular focus on the under-resolved regime, when the closure problem needs to be addressed), we illustrate the ROMs in the numerical simulation of the QGE for various settings, and we present several potential future research avenues in the ROM exploration of the QGE and more complex models of geophysical flows. 

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