Systematic Molecular Dynamics Simulations Research Articles

A correct, reversible Trotter splitting for the evolution operator in molecular dynamics simulations of molecular systems with constraints

ABSTRACT For generating an isobaric–isothermal ensemble in molecular dynamics simulations of atomic systems a correct ensemble distribution can be obtained by the approach of Martyna, Tobias and Klein [J. Chem. Phys. 101, 4177–4189 (1994)]. The constituting equations of the latter approach have been also generalised to molecular systems [M. E. Tuckerman, Statistical Mechanics: Theory and Molecular Simulation, Oxford Graduate Texts (2010)] using the molecular virial instead of the atomic one. An isothermal–isobaric method for systems with holonomic molecular constraints has been also introduced in the past [G. Kalibaeva, M. Ferrario and G. Ciccotti, Mol. Phys. 101 765–778 (2003)] but the factorisation was not worked out completely, resulting in a non-reversible first-order algorithm. Here, we propose the correct factorisation and implement a reversible integrator based on Martyna, Tobias and Klein equations for a system of molecules subjected to holonomic constraints. We add to the algorithm the Suzuki–Yoshida treatment that improves the energy conservation or permits to go to larger time steps. Finally, we test our algorithm by applying it to the dynamics of a Ortotherphenyl model.

Atomistic description of the OCTN1 recognition mechanism via in silico methods.

The Organic Cation Transporter Novel 1 (OCTN1), also known as SLC22A4, is widely expressed in various human tissues, and involved in numerous physiological and pathological processes remains. It facilitates the transport of organic cations, zwitterions, with selectivity for positively charged solutes. Ergothioneine, an antioxidant compound, and acetylcholine (Ach) are among its substrates. Given the lack of experimentally solved structures of this protein, this study aimed at generating a reliable 3D model of OCTN1 to shed light on its substrate-binding preferences and the role of sodium in substrate recognition and transport. A chimeric model was built by grafting the large extracellular loop 1 (EL1) from an AlphaFold-generated model onto a homology model. Molecular dynamics simulations revealed domain-specific mobility, with EL1 exhibiting the highest impact on overall stability. Molecular docking simulations identified cytarabine and verapamil as highest affinity ligands, consistent with their known inhibitory effects on OCTN1. Furthermore, MM/GBSA analysis allowed the categorization of substrates into weak, good, and strong binders, with molecular weight strongly correlating with binding affinity to the recognition site. Key recognition residues, including Tyr211, Glu381, and Arg469, were identified through interaction analysis. Ach demonstrated a low interaction energy, supporting the hypothesis of its one-directional transport towards to outside of the membrane. Regarding the role of sodium, our model suggested the involvement of Glu381 in sodium binding. Molecular dynamics simulations of systems at increasing levels of Na+ concentrations revealed increased sodium occupancy around Glu381, supporting experimental data associating Na+ concentration to molecule transport. In conclusion, this study provides valuable insights into the 3D structure of OCTN1, its substrate-binding preferences, and the role of sodium in the recognition. These findings contribute to the understanding of OCTN1 involvement in various physiological and pathological processes and may have implications for drug development and disease management.

Molecular dynamics simulations of interaction of cascade damage with self-interstitial atom-loaded grain boundaries in tungsten

In this study, we conducted systematic molecular dynamics simulations to investigate the radiation resistance of grain boundaries (GBs) in tungsten with/without self-interstitial atoms (SIAs) loaded on them. The simulation results show that the presence of SIAs can extend the width of the Σ3<110>{112} twin GB compared to the SIA-free GB. When cascade damage occurs near Σ3, the presence of SIAs at Σ3 enhances radiation resistance. Specifically, it inhibits producing residual defects, particularly vacancies and prevents their aggregating into clusters. The radiation-resistant performance is most excellent when the SIA concentration at Σ3 is approximately 5 %. The influence of temperature and primary knock-on atom energy on radiation damage is also discussed. However, SIA-loaded high angle GBs and low angle GBs do not significantly enhance their radiation-resistant performance compared to their SIA-free counterparts. This study provides valuable insights into the radiation damage behaviors near GBs and contributes to understanding their radiation-resistant mechanisms.

CO Intermediate-Assisted Dynamic Cu Sintering During Electrocatalytic CO2 Reduction on Cu-N-C Catalysts.

The electrochemical CO2 reduction reaction (eCO2RR) to multicarbon products has been widely recognized for Cu-based catalysts. However, the structural changes in Cu-based catalysts during the eCO2RR pose challenges to achieving an in-depth understanding of the structure-activity relationship, thereby limiting catalyst development. Herein, we employ constant-potential density functional theory calculations to investigate the sintering process of Cu single atoms of Cu-N-C single-atom catalysts into clusters under eCO2RR conditions. Systematic constant-potential ab initio molecular dynamics simulations revealed that the leaching of Cu-(CO)x moieties and subsequent agglomeration into clusters can be facilitated by synergistic adsorption of H and eCO2RR intermediates (e.g., CO). Increasing the Cu2+ concentration or the applied potential can efficiently suppress Cu sintering. Both microkinetic simulations and experimental results further confirm that sintered Cu clusters play a crucial role in generating C2 products. These findings provide significant insights into the dynamic evolution of Cu-based catalysts and the origin of their activity toward C2 products during the eCO2RR.

A machine learning interatomic potential for high entropy alloys

High entropy alloys (HEAs) possess a vast compositional space, providing exciting prospects for tailoring material properties yet also presenting challenges in their rational design. Efficiently achieving a well-designed HEA often necessitates the aid of atomistic simulations, which rely on the availability of high-quality interatomic potentials. However, such potentials for most HEA systems are missing due to the complex interatomic interaction. To fundamentally resolve the challenge of the rational design of HEAs, we propose a strategy to build a machine learning (ML) interatomic potential for HEAs and demonstrate this strategy using CrFeCoNiPd as a model material. The fully trained ML model can achieve remarkable prediction precision (>0.92 R2) for atomic forces, comparable to the ab initio molecular dynamics (AIMD) simulations. To further validate the accuracy of the ML model, we implement the ML potential for CrFeCoNiPd in parallel molecular dynamics (MD) code. The MD simulations can predict the lattice constant (1 % error) and stacking fault energy (10 % error) of CrFeCoNiPd HEAs with high accuracy compared to experimental results. Through systematic MD simulations, for the first time, we reveal the atomic-scale deformation mechanisms associated with the stacking fault formation and dislocation cross-slips in CrFeCoNiPd HEAs under uniaxial compression, which are consistent with experimental observations. This study can help elucidate the underlying deformation mechanisms that govern the exceptional performance of CrFeCoNiPd HEAs. The strategy to establish ML interatomic potentials could accelerate the rational design of new HEAs with desirable properties.

Systematic Coarse Graining of Environments for the Nonperturbative Simulation of Open Quantum Systems.

Conducting precise electronic-vibrational dynamics simulations of molecular systems poses significant challenges when dealing with realistic environments composed of numerous vibrational modes. Here, we introduce a technique for the construction of effective phonon spectral densities that capture accurately open-system dynamics over a finite time interval of interest. When combined with existing nonperturbative simulation tools, our approach can reduce significantly the computational costs associated with many-body open-system dynamics.

Wettability-modulated behavior of polymers under varying degrees of nano-confinement

Extreme confinement in nanochannels results in unconventional equilibrium and flow behavior of polymers. The underlying flow physics dictating such paradigms remains far from being understood and more so if the confining substrate is composed of two-dimensional materials, such as graphene. In this study, we conducted systematic molecular dynamics simulations to explore the effect of wettability, confinement, and chain length on polymer flow through graphene-like nanochannels. Altering the wetting properties of these membranes that structurally represent graphene results in substantial changes in the behavior of polymers of disparate chain lengths. Longer hydrocarbon chains (n-dodecane) exhibit negligible wettability-dependent structuring in narrower nanochannels compared to shorter chains (n-hexane) culminating in higher average velocities and interfacial slippage of n-dodecane under less wettable conditions. We demonstrate that the wettability compensation comes from chain entanglement attributed to entropic factors. This study reveals a delicate balance between wettability-dependent enthalpy and chain-length-dependent entropy, resulting in a unique nanoscale flow paradigm, thus not only having far-reaching implications in the superior discernment of polymeric flow in sub-micrometer regimes but also potentially revolutionizing various applications in the oil industry, including innovative oil transport, oil extraction, ion transport polymers, and separation membranes.

Elucidating the microscopic origin of observed anti-correlation between the protein-protein and protein-water interaction energies

Water as a solvent plays an important role in dictating the structure and dynamics of the large biomolecules like proteins. It has been proposed that the protein dynamics and energetics are closely coupled to the water molecules in the hydration shell. In particular, it has been shown earlier that the fluctuations in intra-protein (protein-protein) interaction energy is strongly anti-correlated with the protein-water interaction energy (solvation energy). Moreover, the dynamical signatures of water gets reflected into the protein dynamics in terms of a dominant power law behavior. In this work, we have carried out systematic molecular dynamics (MD) simulations of three different protein systems to understand the key physical factors that contribute to such anti-correlations. First, we compare the dynamics in globular folded proteins like Lysozyme with intrinsically disordered peptides (IDPs) like Amyloid beta to show that enhanced conformational fluctuations lead to significantly stronger anti-correlation. Trp-cage miniprotein shows a similar behavior distributed over two sub-ensembles of folded and unfolded states. We also investigate what type of interactions and molecular processes are responsible for the observed anti-correlation. In particular, we observe that the extent of correlation decreases significantly in the order of charged, polar and non-polar amino acid residues. Charged residues that form salt bridge interactions show a dominant anti-correlation. Surprisingly, a few non-polar (hydrophobic and buried) residues demonstrate significant anti-correlation as well. We attribute this to the structural fluctuations that lead to an equilibrium between buried and solvent exposed states of these residues, where the protein-protein and protein-water interactions compensate each other. Our studies indicate that the molecular origin of the observed anti-correlation can be vary depending on the type of the interaction. The overall coupling/correlation is dominated by the electrostatic interactions and charged residues due to a general dielectric screening effect, whereas a few buried hydrophobic residues may also show such coupling due to structural dynamics between buried and exposed states.

Towards understanding the crack suppression mechanism in brittle materials with high grinding speed at different temperatures

Ductile-regime grinding has been used to eliminate the formation of subsurface cracks by setting an extremely small depth of cut (DOC). The critical DOC is affected by multiple factors, including the grinding speed and material temperature. The underlying mechanism of DOC affected by the grinding speed is still unclear. To reveal the role of grinding speed and material temperature during the formation of cracks, we conducted a series of single-point grinding experiments with the different grinding speeds (26.7–192.3 m/s) and the initial material temperatures (25–200 °C). The experimental results showed that cracks were suppressed with an increase in the grinding speed and initial material temperature even when the DOC was much deeper than the critical DOC determined by the ductile-regime grinding. To understand the mechanisms underlying crack nucleation and suppression, we conducted systematic molecular dynamics simulations. Both simulation and experimental results showed that a crack can be formed by a single slip band. The crack nucleates from a microvoid within the slip band. With the aid of the local tensile stress on one side of the slip band tip, the crack nucleation forms an opening crack. The crack suppression is primarily caused by the high‐pressure field during high‐speed grinding, where the high‐pressure field superposes the local tensile stress to forming a compressive stress state that prevents crack nucleation. In addition, the brittle‐ductile transition is induced by the high temperature on the surface during high‐speed grinding. This study provides insights into building the DOC criterion for different grinding speeds and temperatures based on a ‘bottom-up’ approach.

Phase transformation and incidental effects of metastable crystalline TiAlN on the material removal mechanism

Spinodal decomposition of Ti1−xAlxN crystal structure significantly impacts their physical properties, particularly at the atomic scale. In this study, we employed systematic three-dimensional molecular dynamics simulations to understand the process of material removal in TiAlN. Orthogonal simulations were conducted with cutting depth and Al content as variables to analyze their impact on the phase transformation mechanism and the resulting surface finish. The simulations reveal that the aluminum content and depth of cut significantly influence the phase transformation process of supersaturated TiAlN crystals through spinodal decomposition. It is observed that the aluminum content has a maximum stable solubility of approximately 0.6 in TiAlN crystals, above which the system undergoes significant spinodal decomposition during cutting to produce hexagonal phases with lower hardness. Increasing the aluminum content leads to wider phase change and deeper sub-surface damage in the system. On the other hand, the cutting depth will promote phase transformation by affecting the stress distribution, thereby increasing the root mean square roughness of the height profile.

Impact of BA.1, BA.2, and BA.4/BA.5 Omicron mutations on therapeutic monoclonal antibodies

The emergence of Omicron SARS-CoV-2 subvariants (BA.1, BA.2, BA.4, and BA.5), with an unprecedented number of mutations in their receptor-binding domain (RBD) of the spike-protein, has fueled a resurgence of COVID-19 infections, posing a major challenge to the efficacy of existing vaccines and monoclonal antibody (mAb) therapeutics. We conducted a systematic molecular dynamics (MD) simulation to investigate how the RBD mutations of these subvariants affect the interactions with broad mAbs including AstraZeneca (COV2-2196 and COV2-2130), Brii Biosciences (BRII-196), Celltrion (CT-P59), Eli Lilly (LY-CoV555 and LY-CoV016), Regeneron (REGN10933 and REGN10987), Vir Biotechnology (S309), and S2X259. Our results show a complete loss of binding for COV2-2196, BRII-196, CT-P59, and LY-CoV555 with all Omicron RBDs. Additionally, REGN10987 totally loses its binding with BA.1, but retains a partial binding with BA.2 and BA.4/5. The binding reduction is significant for LY-CoV016 and REGN10933 but moderate for COV2-2130. S309 and S2X259 retain their binding with BA.1 but exhibit decreased binding with other subvariants. We introduce a mutational escape map for each mAb to identify the key RBD sites and the corresponding critical mutations. Overall, our findings suggest that the majority of therapeutic mAbs have diminished or missing activity against Omicron subvariants, indicating the urgent need for a new therapeutic mAb with a better design.

Molecular Dynamics Simulations of Ideal Living Polymerization: Terminal Model and Kinetic Aspects.

Living polymerization is an important synthetic approach to achieving precise control of synthesized polymers, which is crucial for their applications. The molecular weight distribution (MWD) prescribes the macroscopic properties of polymers and hence is a key feature to characterize polymerization. In this work, we present a systematic molecular dynamics simulation study of ideal living polymerization in bulk and surface-initiated systems based on a terminal stochastic reaction model. The evolution of polymer dispersity and MWD along with the polymerization process is examined. We demonstrate that MWD is generally well captured by the Schulz-Zimm distribution for bulk and surface-initiated systems with low grafting densities. However, as the grafting density in the surface-initiated case increases, heterogeneity in chain growth emerges due to the kinetic trapping of reactive sites, which causes the starving of short chains and the thriving of minority long chains such that a shoulder region shows up in MWD. This effect can be enhanced by kinetic compressing induced by polymerization. In addition, the interplay of bonding reaction kinetics and other kinetic properties (e.g., mass transfer and polymer relaxation) is further explored, alongside the influences of bonding probability and reactant concentration. We expect that this investigation will aid in our understanding of typical kinetic aspects of living polymerization.

Size- and Chirality-Dependent Structural and Mechanical Properties of Single-Walled Phenine Nanotubes

Phenine nanotubes (PNTs) have recently been synthesized as a promising new one-dimensional material for high-performance electronics. The periodically distributed vacancy defects in PNTs result in novel semiconducting properties, but may also compromise their mechanical properties. However, the role of these defects in modifying the structural and mechanical properties is not yet well understood. To address this, we conducted systematic molecular dynamics simulations investigating the structural evolution and mechanical responses of PNTs under various conditions. Our results demonstrated that the twisting of linear carbon chains in both armchair and zigzag PNTs led to interesting structural transitions, which were sensitive to chiralities and diameters. Additionally, when subjected to tensile and compressive loading, PNTs’ cross-sectional geometry and untwisting of linear carbon chains resulted in distinct mechanical properties compared to carbon nanotubes. Our findings provide comprehensive insights into the fundamental properties of these new structures while uncovering a new mechanism for modifying the mechanical properties of one-dimensional nanostructures through the twisting–untwisting of linear carbon chains.

Organic near‐infrared photodetectors with photoconductivity‐enhanced performance

AbstractOrganic near‐infrared (NIR) photodetectors with essential applications in medical diagnostics, night vision, remote sensing, and optical communications have attracted intensive research interest. Compared with most conventional inorganic counterparts, organic semiconductors usually have higher absorption coefficients, and their thin active layer could be sufficient to absorb most incident light for effective photogeneration. However, due to the relatively poor charge mobility of organic materials, it remains challenging to inhibit the photogenerated exciton recombination and effectively extract carriers to their respective electrodes. Herein, this challenge was addressed by increasing matrix conductivities of a ternary active layer (D–A–D structure NIR absorber [2TT‐oC6B]:poly(N,N′‐bis‐4‐butylphenyl‐N,N′‐bisphenyl)benzidin [PolyTPD]:[6,6]‐phenyl‐C61‐butyric acid methyl ester [PCBM] = 1:1:1) upon in situ incident light illumination, significantly accelerating charge transport through percolated interpenetrating paths. The greatly enhanced photoconductivity under illumination is intrinsically related to the unique donor–acceptor molecular structures of PolyTPD and 2TT‐oC6B, whereas stable intermolecular interaction has been verified by systematic molecular dynamics simulation. In addition, an ultrafast charge transfer time of 0.56 ps from the NIR aggregation‐induced luminogens of 2TT‐oC6B absorber to PolyTPD and PCBM measured by femtosecond transient absorption spectroscopy is beneficial for effective exciton dissociation. The solution‐processed organic NIR photodetector exhibits a fast response time of 83 μs and a linear dynamic range value of 111 dB under illumination of 830 nm. Therefore, our work has opened up a pioneering window to enhance photoconductivity through in situ photoirradiation and benefit NIR photodetectors as well as other optoelectronic devices.

Optimization of interfacial mixing for thermal transport along Si/Ge heterostructures: A molecular dynamics study

Interfaces can play critical roles in the dissipation of heat, generated during the electronic nanodevices operation. Therefore, engineering of the interfacial thermal resistance is a key factor in the thermal management design of nanoelectronics. In this research, the engineering of the interfacial thermal resistance of silicon/germanium heterostructure is explored, by varying the content of silicon or germanium atoms at the interphase (mixing region). For this goal, we conducted systematic non-equilibrium molecular dynamics simulations. For a specific interphase length, it is noticeably predicted that the interfacial thermal resistance versus the percentage of germanium atoms shows an optimal minimum value. By substituting germanium atoms with silicon atoms, but with preserving their atomic mass, it is interestingly shown that the interfacial thermal resistance increases significantly, although the optimal value for the interfacial thermal resistance is still observable. By altering the length of the interphase region and the samples’ temperature (300 and 600 K), the optimal interfacial thermal conductance in terms of the percentage of germanium atoms in the mixing region was also detectable. The findings of this work can be useful in the thermal management engineering of nanodevices, especially in nanoelectronics.

Evidence of Formation of 1–10 nm Diameter Ice Nanotubes in Double-Walled Carbon Nanotube Capillaries

Water exhibits rich phase behaviors in nanoscale confinement. Since the simulation evidence of the formation of single-walled ice nanotubes (INTs) in single-walled carbon nanotubes was confirmed experimentally, INTs have been recognized as a form of low-dimensional hydrogen-bonding network. However, the single-walled INTs reported in the literature all possess subnanometer diameters (<1 nm). Herein, based on systematic and large-scale molecular dynamics simulations, we demonstrate the spontaneous freezing transition of liquid water to single-walled INTs with diameters reaching ∼10 nm when confined to capillaries of double-walled carbon nanotubes (DW-CNTs). Three distinct classes of INTs are observed, namely, INTs with flat square walls (INTs-FSW), INTs with puckered rhombic walls (INTs-PRW), and INTs with bilayer hexagonal walls (INTs-BHW). Surprisingly, when water is confined in DW-CNT (3, 3)@(13, 13), an INT-FSW freezing temperature of 380 K can be reached, which is even higher than the boiling temperature of bulk water at atmospheric pressure. The freezing temperatures of INTs-FSW decrease as their caliber increases, approaching to the freezing temperature of two-dimensional flat square ice at the large-diameter limit. In contrast, the freezing temperature of INTs-PRW is insensitive to their diameter. Ab initio molecular dynamics simulations are performed to examine the stability of the INT-FSW and INT-PRW. The highly stable INTs with diameters beyond subnanometer scale can be exploited for potential applications in nanofluidic technologies and for mass transport as bioinspired nanochannels.

Theoretical insights into the coordination structures, stabilities and electronic spectra of Cm3+ species at the gibbsite-water interface: A computational study combing ab initio molecular dynamics and wave function theory

The information of structure and stability of actinide species is key to understand the sorption mechanism of actinides at mineral–water interface. Such information is approximately derived from experimental spectroscopic measurements and needs to be accurately obtained by a direct atomic-scale modelling. Herein, systematic first-principles calculations and ab initio molecular dynamics (AIMD) simulations are carried out to study the coordination structures and absorption energies of Cm(III) surface complexes at gibbsite-water interface. Eleven representative complexing sites are investigated. The most stable Cm3+ sorption species are predicted to be a tridentate surface complex in weakly acidic/neutral solution condition and a bidentate one in the alkaline solution condition. Moreover, luminescence spectra of the Cm3+ aqua ion and the two surface complexes are predicted based on the high-accuracy ab initio wave function theory (WFT). The results give a gradually decreasing emission energy in good agreement with experimental observation of a red shift of peak maximum with pH increasing from 5 to 11. This work is a comprehensive computational study involving AIMD and ab initio WFT methods to gain the coordination structures, stabilities, and electronic spectra of actinide sorption species at the mineral–water interface, thus providing important theoretical support for geological disposal of actinide waste.

Molecular dynamics exploration of helium bubble nucleation and growth mechanisms in Fe70Ni11Cr19 austenitic stainless steel.

The growth of helium bubbles impacts structural integrity of materials in nuclear applications. Understanding helium bubble nucleation and growth mechanisms is critical for improved material applications and aging predictions. Systematic molecular dynamics simulations have been performed to study helium bubble nucleation and growth mechanisms in Fe70Ni11Cr19 stainless steels. First, helium cluster diffusivities are calculated at a variety of helium cluster sizes and temperatures for systems with and without dislocations. Second, the process of diffusion of helium atoms to join existing helium bubbles is not deterministic and is hence studied using ensemble simulations for systems with and without vacancies, interstitials, and dislocations. We find that bubble nucleation depends on diffusion of not only single helium atoms, but also small helium clusters. Defects such as vacancies and dislocations can significantly impact the diffusion kinetics due to the trapping effects. Vacancies always increase the time for helium atoms to join existing bubbles due to the short-range trapping effect. This promotes bubble nucleation as opposed to bubble growth. Interestingly, dislocations can create a long-range trapping effect that reduces the time for helium atoms to join existing bubbles. This can promote bubble growth within a certain region near dislocations.

Mono-phosphorylation at Ser4 of barrier-to-autointegration factor (Banf1) significantly reduces its DNA binding capability by inducing critical changes in its local conformation and DNA binding surface.

Barrier-to-autointegration factor (Banf1) is a small DNA-bridging protein. The binding status of Banf1 to DNA is regulated by its N-terminal phosphorylation and dephosphorylation, which plays a critical role in cell proliferation. Banf1 can be phosphorylated at Ser4 into mono-phosphorylated Banf1, which is further phosphorylated at Thr3 to form di-phosphorylated Banf1. It was observed decades ago that mono-phosphorylated Banf1 cannot bind to DNA. However, the underlying molecular- and atomic-level mechanisms remain unclear. A clear understanding of these mechanisms will aid in interfering with the cell proliferation process for better global health. Herein, we explored the detailed atomic bases of unphosphorylated Banf1-DNA binding and how mono- and di-phosphorylation of Banf1 impair these atomic bases to eliminate its DNA-binding capability, followed by exploring the DNA-binding capability of mono- and di-phosphorylation Banf1, using comprehensive and systematic molecular modelling and molecular dynamics simulations. This work presented in detail the residue-level binding energies, hydrogen bonds and water bridges between Banf1 and DNA, some of which have not been reported. Moreover, we revealed that mono-phosphorylation of Banf1 causes its N-terminal secondary structure changes, which in turn induce significant changes in Banf1's DNA binding surface, thus eliminating its DNA-binding capability. At the atomic level, we also uncovered the alterations in interactions due to the induction of mono-phosphorylation that result in the N-terminal secondary structure changes of Banf1. Additionally, our modelling showed that phosphorylated Banf1 with their dominant N-terminal secondary structures bind to DNA with a significantly lower affinity and the docked binding pose are not stable in MD simulations. These findings help future studies in predicting effect of mutations in Banf1 on its DNA-binding capability and open a novel avenue for the development of therapeutics such as cancer drugs, targeting cell proliferation by inducing conformational changes in Banf1's N-terminal domain.

Structures and transport properties of supercritical SiO2-H2O and NaAlSi3O8-H2O fluids

Abstract Speciation and transport properties of supercritical fluids is critical for understanding their behavior in the Earth’s interior. Here, we report a systematic first principles molecular dynamics simulation study of the structure, speciation, self-diffusivity (D), and viscosity (η) of SiO2 melt, NaAlSi3O8 melt, SiO2-H2O and NaAlSi3O8-H2O fluids at 2000–3500 K with 0–70 wt% H2O. Our calculations show that as the water content increases, the proportion of Q0 species (Qn species, where n is the number of bridging oxygens in an individual Si/Al-O polyhedra) increases while Q4 decreases. The proportions of Q1, Q2, and Q3 species first increase and then decrease with increasing water content. The diffusivity sequence for the supercritical SiO2-H2O fluids is DH &amp;gt;DO &amp;gt;DSi, and for the supercritical NaAlSi3O8-H2O fluids, on the whole, is DNa ≈ DH &amp;gt;DO &amp;gt;DAl ≈ DSi. The viscosities of the two systems decrease drastically at the beginning of the increase in water content, and then decrease slowly. We demonstrate that the exponential decrease in the viscosity of polymerized silicate melt with increasing water content is due to a sharp decrease in the proportion of Q4 species and increase in Si-O-H. The typical structural feature of supercritical fluid is that it contains a large amount of easy-to-flow partially polymerized or depolymerized protonated silicate units, which leads to a low viscosity while being enriched in silicate. This feature provides supercritical fluids the potential to transport elements that are hard to migrate in aqueous fluids or hydrous silicate melts, such as high field strength elements.