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At least 19 records

Force field parameter estimation of functional perfluoropolyether lubricants

The head disk interface in a hard disk drive can be considered to be one of the hierarchical multiscale systems, which require the hybridization of multiscale modeling methods with coarse-graining procedure. However, the fundamental force field parameters are required to enable the coarse-graining procedure from atomistic/molecular scale to mesoscale models. In this paper, we investigate beyond molecular level and perform ab initio calculations to obtain the force field parameters. Intramolecular force field parameters for Zdol and Ztetraol were evaluated with truncated PFPE molecules to allow for feasible quantum calculations while still maintaining the characteristic chemical structure of the end groups. Using the harmonic approximation to the bond and angle potentials, the parameters were derived from the Hessian matrix, and the dihedral force constants are fit to the torsional energy profiles generated by a series of constrained molecular geometry optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture

Abstract Recently, machine learning (ML) has been used to address the computational cost that has been limiting ab initio molecular dynamics (AIMD). Here, we present GNNFF, a graph neural network framework to directly predict atomic forces from automatically extracted features of the local atomic environment that are translationally-invariant, but rotationally-covariant to the coordinate of the atoms. We demonstrate that GNNFF not only achieves high performance in terms of force prediction accuracy and computational speed on various materials systems, but also accurately predicts the forces of a large MD system after being trained on forces obtained from a smaller system. Finally, we use our framework to perform an MD simulation of Li 7 P 3 S 11 , a superionic conductor, and show that resulting Li diffusion coefficient is within 14% of that obtained directly from AIMD. The high performance exhibited by GNNFF can be easily generalized to study atomistic level dynamics of other material systems.

Chemistry↗

Long‐Term Large‐Scale Atmospheric Forcing Data From Three‐Dimensional Constrained Variational Analysis for the ARM SGP Site

Here, this study presents a long‐term three‐dimensional large‐scale forcing data set (VARANAL3D) derived from the three‐dimensional constrained variational analysis (3DCVA) method at the Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site from 2004 to 2018. Building on the same input data sets as the conventional continuous forcing data set (VARANAL), VARANAL3D maintains overall consistency in domain‐averaged fields while introducing spatial variability, offering critical insights into the influence of mesoscale synoptic systems on cloud‐related processes. Evaluations are conducted across four cloud and precipitation regimes: Clear‐sky, Shallow‐clouds, Afternoon‐precipitation, and Nocturnal‐precipitation, presenting high consistency of the domain‐mean forcing data sets while emphasizing the role of subdomain forcing variability particularly in precipitating regimes. Single column model (SCM) simulations demonstrate that subdomain VARANAL3D forcing improves cloud and precipitation representation, with the ensemble outperforming domain‐mean forcing in three cloudy and precipitating regimes. Overall, these results highlight VARANAL3D's value for investigating the impacts of spatial variability of large‐scale forcing on atmospheric processes. The VARANAL3D data set provides new opportunities for evaluating model physics, advancing the development of scale‐aware parameterizations and deepening our understanding of cloud and precipitation dynamics.

Environmental sciences↗

Hacking the thylakoid proton motive force for improved photosynthesis: modulating ion flux rates that control proton motive force partitioning into Δ ψ and ΔpH

There is considerable interest in improving plant productivity by altering the dynamic responses of photosynthesis in tune with natural conditions. This is exemplified by the 'energy-dependent' form of non-photochemical quenching (q E ), the formation and decay of which can be considerably slower than natural light fluctuations, limiting photochemical yield. In addition, we recently reported that rapidly fluctuating light can produce field recombination-induced photodamage (FRIP), where large spikes in electric field across the thylakoid membrane (Δψ) induce photosystem II recombination reactions that produce damaging singlet oxygen ( 1 O 2 ). Both q E and FRIP are directly linked to the thylakoid proton motive force (pmf), and in particular, the slow kinetics of partitioning pmf into its ΔpH and Δψ components. In this work, using a series of computational simulations, we explored the possibility of 'hacking' pmf partitioning as a target for improving photosynthesis. Under a range of illumination conditions, increasing the rate of counter-ion fluxes across the thylakoid membrane should lead to more rapid dissipation of Δψ and formation of ΔpH. This would result in increased rates for the formation and decay of qE while resulting in a more rapid decline in the amplitudes of Δψ-spikes and decreasing 1 O 2 production. These results suggest that ion fluxes may be a viable target for plant breeding or engineering. However, these changes also induce transient, but substantial mismatches in the ATP : NADPH output ratio as well as in the osmotic balance between the lumen and stroma, either of which may explain why evolution has not already accelerated thylakoid ion fluxes. Overall, though the model is simplified, it recapitulates many of the responses seen in vivo, while spotlighting critical aspects of the complex interactions between pmf components and photosynthetic processes. By making the programme available, we hope to enable the community of photosynthesis researchers to further explore and test specific hypotheses. This article is part of the themed issue 'Enhancing photosynthesis in crop plants: targets for improvement'.

59 BASIC BIOLOGICAL SCIENCES↗

An automated analysis workflow for optimization of force-field parameters using neutron scattering data

Graphical abstract: - Highlights: • An automated workflow to optimize force-field parameters. • Used the workflow to optimize force-field parameter for a system containing nanodiamond and tRNA. • The mechanism relies on molecular dynamics simulation and neutron scattering experimental data. • The workflow can be generalized to any other experimental and simulation techniques. - Abstract: Large-scale simulations and data analysis are often required to explain neutron scattering experiments to establish a connection between the fundamental physics at the nanoscale and data probed by neutrons. However, to perform simulations at experimental conditions it is critical to use correct force-field (FF) parameters which are unfortunately not available for most complex experimental systems. In this work, we have developed a workflow optimization technique to provide optimized FF parameters by comparing molecular dynamics (MD) to neutron scattering data. We describe the workflow in detail by using an example system consisting of tRNA and hydrophilic nanodiamonds in a deuterated water (D{sub 2}O) environment. Quasi-elastic neutron scattering (QENS) data show a faster motion of the tRNA in the presence of nanodiamond than without the ND. To compare the QENS and MD results quantitatively, a proper choice of FF parameters is necessary. We use an efficient workflow to optimize the FF parameters between the hydrophilic nanodiamond and water by comparing to the QENS data. Our results show that we can obtain accurate FF parameters by using this technique. The workflow can be generalized to other types of neutron data for FF optimization, such as vibrational spectroscopy and spin echo.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Rigorous force field optimization principles based on statistical distance minimization

We use the concept of statistical distance to define a measure of distinguishability between a pair of statistical mechanical systems, i.e., a model and its target, and show that its minimization leads to general convergence of the model’s static measurable properties to those of the target. We exploit this feature to define a rigorous basis for the development of accurate and robust effective molecular force fields that are inherently compatible with coarse-grained experimental data. The new model optimization principles and their efficient implementation are illustrated through selected examples, whose outcome demonstrates the higher robustness and predictive accuracy of the approach compared to other currently used methods, such as force matching and relative entropy minimization. We also discuss relations between the newly developed principles and established thermodynamic concepts, which include the Gibbs-Bogoliubov inequality and the thermodynamic length.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design of a self-aligned, wide temperature range (300 mK-300 K) atomic force microscope/magnetic force microscope with 10 nm magnetic force microscope resolution

We describe the design of a wide temperature range (300 mK-300 K) atomic force microscope/magnetic force microscope with a self-aligned fibre-cantilever mechanism. An alignment chip with alignment groves and a special mechanical design are used to eliminate tedious and time consuming fibre-cantilever alignment procedure for the entire temperature range. A low noise, Michelson fibre interferometer was integrated into the system for measuring deflection of the cantilever. The spectral noise density of the system was measured to be ~12 fm/√Hz at 4.2 K at 3 mW incident optical power. Abrikosov vortices in BSCCO(2212) single crystal sample and a high density hard disk sample were imaged at 10 nm resolution to demonstrate the performance of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Atomic force microscopy based nanoindentation study of onion abaxial epidermis walls in aqueous environment

An atomic force microscopy based nanoindentation method was employed to study how the structure of cellulose microfibril packing and matrix polymers affect elastic modulus of fully hydrated primary plant cell walls. The isolated, single-layered abaxial epidermis cell wall of an onion bulb was used as a test system since the cellulose microfibril packing in this cell wall is known to vary systematically from inside to outside scales and the most abundant matrix polymer, pectin, can easily be altered through simple chemical treatments such as ethylenediaminetetraacetic acid and calcium ions. Experimental results showed that the pectin network variation has significant impacts on the cell wall modulus, and not the cellulose microfibril packing.

36 MATERIALS SCIENCE↗

Comparison of Cellulose Ib Simulations with Three Carbohydrate Force Fields

Molecular dynamics simulations of cellulose have recently become more prevalent due to increased interest in renewable energy applications, and many atomistic and coarse-grained force fields exist that can be applied to cellulose. However, to date no systematic comparison between carbohydrate force fields has been conducted for this important system. To that end, we present a molecular dynamics simulation study of hydrated, 36-chain cellulose I{beta} microfibrils at room temperature with three carbohydrate force fields (CHARMM35, GLYCAM06, and Gromos 45a4) up to the near-microsecond time scale. Our results indicate that each of these simulated microfibrils diverge from the cellulose I{beta} crystal structure to varying degrees under the conditions tested. The CHARMM35 and GLYCAM06 force fields eventually result in structures similar to those observed at 500 K with the same force fields, which are consistent with the experimentally observed high-temperature behavior of cellulose I. The third force field, Gromos 45a4, produces behavior significantly different from experiment, from the other two force fields, and from previously reported simulations with this force field using shorter simulation times and constrained periodic boundary conditions. For the GLYCAM06 force field, initial hydrogen-bond conformations and choice of electrostatic scaling factors significantly affect the rate of structural divergence. Our results suggest dramatically different time scales for convergence of properties of interest, which is important in the design of computational studies and comparisons to experimental data. This study highlights that further experimental and theoretical work is required to understand the structure of small diameter cellulose microfibrils typical of plant cellulose.

09 BIOMASS FUELS↗

Adaptive local basis set for Kohn–Sham density functional theory in a discontinuous Galerkin framework II: Force, vibration, and molecular dynamics calculations

Recently, we have proposed the adaptive local basis set for electronic structure calculations based on Kohn–Sham density functional theory in a pseudopotential framework. The adaptive local basis set is efficient and systematically improvable for total energy calculations. In this paper, we present the calculation of atomic forces, which can be used for a range of applications such as geometry optimization and molecular dynamics simulation. We demonstrate that, under mild assumptions, the computation of atomic forces can scale nearly linearly with the number of atoms in the system using the adaptive local basis set. We quantify the accuracy of the Hellmann–Feynman forces for a range of physical systems, benchmarked against converged planewave calculations, and find that the adaptive local basis set is efficient for both force and energy calculations, requiring at most a few tens of basis functions per atom to attain accuracies required in practice. Since the adaptive local basis set has implicit dependence on atomic positions, Pulay forces are in general nonzero. However, we find that the Pulay force is numerically small and systematically decreasing with increasing basis completeness, so that the Hellmann–Feynman force is sufficient for basis sizes of a few tens of basis functions per atom. We verify the accuracy of the computed forces in static calculations of quasi-1D and 3D disordered Si systems, vibration calculation of a quasi-1D Si system, and molecular dynamics calculations of H{sub 2} and liquid Al–Si alloy systems, where we show systematic convergence to benchmark planewave results and results from the literature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Novel 3D Force Sensors for a Cost-Effective 3D Force Plate for Biomechanical Analysis

Three-dimensional force plates are important tools for biomechanics discovery and sports performance practice. However, currently, available 3D force plates lack portability and are often cost-prohibitive. To address this, a recently discovered 3D force sensor technology was used in the fabrication of a prototype force plate. Thirteen participants performed bodyweight and weighted lunges and squats on the prototype force plate and a standard 3D force plate positioned in series to compare forces measured by both force plates and validate the technology. For the lunges, there was excellent agreement between the experimental force plate and the standard force plate in the X-, Y-, and Z-axes (r = 0.950–0.999, p < 0.001). For the squats, there was excellent agreement between the force plates in the Z-axis (r = 0.996, p < 0.001). Across axes and movements, root mean square error (RMSE) ranged from 1.17% to 5.36% between force plates. Although the current prototype force plate is limited in sampling rate, the low RMSEs and extremely high agreement in peak forces provide confidence the novel force sensors have utility in constructing cost-effective and versatile use-case 3D force plates.

42 ENGINEERING↗