Ab Initio Molecular Dynamics Trajectories Research Articles

Axial H-Bonding Solvent Controls Inhomogeneous Spectral Broadening, While Peripheral H-Bonding Solvent Controls Vibronic Broadening: Cresyl Violet in Methanol.

The dynamics of the nuclei of both a chromophore and its condensed-phase environment control many spectral features, including the vibronic and inhomogeneous broadening present in spectral line shapes. For the cresyl violet chromophore in methanol, we here analyze and isolate the effect of specific chromophore-solvent interactions on simulated spectral densities, reorganization energies, and linear absorption spectra. Employing both chromophore and its condensed-phase environment control many spectral features, including the vibronic and inhomogeneous broadening present in spectral line shapes. For the cresyl violet chromophore in methanol, we here analyze and isolate the effect of specific chromophore-solvent interactions on simulated spectral densities, reorganization energies, and linear absorption spectra. Employing both force field and ab initio molecular dynamics trajectories along with the inclusion of only certain solvent molecules in the excited-state calculations, we determine that the methanol molecules axial to the chromophore are responsible for the majority of inhomogeneous broadening, with a single methanol molecule that forms an axial hydrogen bond dominating the response. The strong peripheral hydrogen bonds do not contribute to spectral broadening, as they are very stable throughout the dynamics and do not lead to increased energy-gap fluctuations. We also find that treating the strong peripheral hydrogen bonds as molecular mechanical point charges during the molecular dynamics simulation underestimates the vibronic coupling. Including these peripheral hydrogen bonding methanol molecules in the quantum-mechanical region in a geometry optimization increases the vibronic coupling, suggesting that a more advanced treatment of these strongly interacting solvent molecules during the molecular dynamics trajectory may be necessary to capture the full vibronic spectral broadening.

Effect of Cage Occupancies on Molecular Vibrations of Methane in Structure H Clathrate Hydrate: Ab Initio Molecular Dynamics Simulation.

The structure H (sH) of methane hydrate, which has a distinctive structure with large (LL) cages capable of encapsulating multiple methane molecules, has been suggested as a methane reservoir in large icy bodies such as Titan, making it important in planetary science. This high-pressure phase, which exists in the GPa range, lends itself to the study of methane states and dynamics using powerful experimental techniques such as IR and Raman spectroscopy. However, the interpretation of the vibrational spectra of methane in the sH structure has been challenging because of the spectral complexities. The signals attributed to the methane molecules in the LL cage, as well as those of the other two cage types, overlap in the spectra. In this study, we investigated the microscopic origins of the shape of the C-H stretching vibration spectrum of methane in the LL cage using ab initio molecular dynamics (AIMD) simulations. For a single methane molecule in the LL cage, the ν3 band of the C-H stretching mode was observed at a higher frequency typical of isolated molecules in vacuum due to the large size of the LL cage. As the number of methane molecules in the LL cage increased beyond one, a tendency to blue-shift with increasing methane occupancy was observed, consistent with a loose-cage-tight-cage model. By characterizing the time correlation function of methane stretching vibrations based on the solvation number of methane and water molecules proximal to methane within the LL cage, we showed that the complicated spectral line shape observed in cases of higher methane occupancy in the LL cage resulted from the wider variation of the solvation shell states. Analysis of the solvation structures of the AIMD trajectories provided interpretations of the experimental spectral line shape, demonstrating the complementary nature of AIMD to the experiment and its effectiveness in analysis.

Ab Initio Characterization of the CO2-Water Interface Using Unsupervised Machine Learning for Dimensionality Reduction.

Precise characterization of the supercritical CO2-water interface under high pressure and temperature conditions is crucial for the geological storage of carbon dioxide (CO2) in deep saline aquifers. Molecular dynamics (MD) simulations offer a valuable approach to gaining insight into the CO2-water interface at a microscopic level. However, no attempt has been made to characterize the CO2-water interface with the accuracy afforded by ab initio calculations. In this study, we performed ab initio MD (AIMD) simulations to investigate the structural and dynamical properties of the CO2-water interface, comparing the results with those obtained from classical force-field MD (FF-MD) simulations. Molecular orientation at the interface was well reproduced in both AIMD and FF-MD simulations. Characteristic structural fluctuations of water at the interface were unveiled by applying multidimensional scaling and time-dependent principal component analysis to the AIMD trajectories; however, they were not prominent in the FF-MD simulations. Furthermore, our study demonstrated a marked difference in the residence time of molecules in the interface region between AIMD and FF-MD simulations, indicating that time-dependent properties of the CO2-water interface strongly depend on the description of the intermolecular forces.

Laterally Resolved Free Energy Profiles and Vibrational Spectra of Chemisorbed H Atoms on Pt(111).

A scheme to compute laterally resolved free energy surfaces and spectral signatures of specifically adsorbed ions on electrode surfaces from their ab initio molecular dynamics (AIMD) trajectories is proposed. Considering H-covered Pt(111) electrodes, both in contact with water and vacuum and for various H coverages, we systematically explore the impact of explicit water and H-coverage on site occupancy, providing direct insight into the proportion of underpotential and overpotential deposited hydrogen adsorbates. Extending this approach further, we can obtain laterally resolved vibrational spectra of the Pt-H stretch modes. We discuss how the difference between the free energy basins of the on-top and fcc-hollow adsorption sites explains the features of the experimentally observed spectral fingerprints in this system. These fingerprints do not contain only information about the stable and metastable adsorption sites but also about intermediate short-lived adsorbate configurations. Our results also show that for these properties chemisorbed H2O acts as a spectator and does not qualitatively influence the relative stabilities of the adsorption sites and their spectral fingerprints.

Interfacial Electrochemical Lithiation and Dissolution Mechanisms at a Sulfurized Polyacrylonitrile Cathode Surface.

Advances in sulfurized-polyacrylonitrile (SPAN)-based cathode materials promise safer and more efficient lithium-sulfur (Li-S) battery performance. To elucidate electrolyte-cathode interfacial electrochemistry and polysulfide (PS) dissolution, we emulate discharge SPAN reactions via ab initio molecular dynamics (AIMD) simulations. Plausible structures and their lithiation profiles are cross-validated via Raman/IR spectroscopy and density functional theory (DFT). Lithium bis(fluorosulfonyl)imide (LiFSI) plays versatile roles in the Li-SPAN cell electrochemistry, primarily as the major source in forming the cathode-electrolyte interphase (CEI), further verified via X-ray photoelectron spectroscopy and AIMD. Besides being a charge carrier and CEI composer, LiFSI mediates the PS generation processes in SPAN electrochemical lithiation. Analysis of AIMD trajectories during progressive lithiation reveals that, compared to carbonates, ether solvents enable stronger solvation and chemical stabilization for both salt and SPAN structures. Differentiated CEI formation and electrochemical lithiation decomposition pathways and products are profoundly associated with the intrinsic nature of lithium bonding with oxygen and sulfur.

Size dependent lithium-ion conductivity of solid electrolytes in machine learning molecular dynamics simulations

Solid-state electrolytes are key ingredients in next-generation devices for energy storage and release. Machine learning molecular dynamics (MLMD) has shown great promise in studying the diffusivity of mobile ions in solid-state electrolytes, with much higher efficiency than conventional ab initio molecular dynamics (AIMD). In this work, we combine an efficient embedded atom neural network (EANN) approach and an uncertainty-driven active learning algorithm that optimally selects data points from high-temperature AIMD trajectories to construct ML potentials for solid-state electrolytes and validate this strategy in a benchmark system, Li3YCl6, for which several controversy theoretical results exist. Through systematic MLMD simulations, we find that a typically used small supercell in AIMD simulations fails to predict the supersonic transition at a critical temperature, leading to a significant overestimation of the Li+ conductivity in Li3YCl6 at room temperature. Fortunately, thanks to the scalability of the EANN potential, extended MLMD simulations in a sufficiently large cell does yield a notable change of temperature-dependence in conductivity at ∼420 K and a much lower room-temperature conductivity in excellent with experiment. Interestingly, our results are all based on a semi-local PBE density functional, which was argued unable to predict the superionic transition. We analyze possible reasons of the seemingly inconsistent MLMD results reported in literature with different ML potentials. This work paves the way of simply using high-temperature AIMD data to generate more reliable MLMD results of low-temperature ionic conductivities in solid-state electrolytes.

Ab Initio Molecular Dynamics Simulations of Aqueous LiTFSI Solutions─Structure, Hydrogen Bonding, and IR Spectra.

Simulations of Density Functional Theory-based ab initio molecular dynamics (AIMD) have been performed for a series of aqueous lithium bis(trifluoromethylsulfonyl)imide (LiTFSI) solutions with concentrations ranging from salt-in-water to water-in-salt systems. Analysis of the structure of electrolytes has revealed a preference of Li+ cations to interact with water molecules. In concentrated LiTFSI solutions, water molecules form small associates. The total number of hydrogen bonds (HBs) in the system decreases with salt concentrations, with bonds to water acceptors being only partially replaced by interactions with TFSI anions. Infrared (IR) spectra in the region of the O-H stretching frequency calculated from AIMD trajectories are in good agreement with experimental data. Statistics of oscillations of individual O-H bonds have shown correlations between vibrational frequencies and the structure of HBs formed by water. The changes in the IR spectrum have been related to the varying contributions of different local environments of the water molecules. The abundances of the three spectral components calculated from the simulations agree well with the decomposition of the experimental IR spectra reported in the literature.

(Battery Division Student Research Award Sponsored by Mercedes-Benz Research & Development) Rationalizing Fast Lithium-ion Diffusion in Inorganic Lithium Superionic Conductors

All-solid-state batteries are gaining attention due to the potential advantage that solid electrolytes provide in terms of safety and energy density. Understanding the mechanism of fast lithium-ion diffusion in inorganic materials has become one of the key challenges in materials science. Among various factors that affect lithium mobility, the topology of the crystal structure strongly dictates which materials can accommodate fast lithium-ion motion. Despite this, the intrinsic mechanism that connects the lithium-ion diffusion to the structural feature of the crystal structure and motion of the non-diffusing framework remains unclear, hindering the rational design of novel fast-conducting solid electrolytes.This talk focuses on the fundamental understanding of the structure-property relationship of lithium-ionic conductivities. We first discuss the structural factors governing fast lithium-ion diffusion in oxide materials. We find that both the topology of the lithium-ion diffusion network as well as the connectivity of the non-diffusing framework strongly affect lithium-ions diffusion in oxide materials. Structural features that allow lithium superionic conductivity in oxide materials are identified, which led to the discovery of 16 novel fast lithium-ion conducting frameworks.In the second part of the talk, we present our statistical framework for understanding the correlation between anion-group rotational motion and lithium-ion translational motion. Using event-detection algorithms on long ab-initio molecular dynamics trajectories, we detect and differentiate various types of rotational motion of anion groups. This allows us to obtain a statistically rigorous understanding of how each type of anion group rotational motion affects lithium-ion diffusion events. These fundamental understandings provide design guidelines towards the development of fast-diffusing inorganic materials optimal for all-solid-state batteries.

Elucidating the Role of Anion Groups in Lithium-Ion Diffusion

Since the 1960s, the paddlewheel effect has been proposed as a way to enhance lithium-ion diffusion in inorganic materials by using rotor-like anion groups to assist lithium-ion movement(1–5). However, so far the physical mechanism behind how anion-group dynamics affect lithium-ion diffusion has not been clearly understood. In this talk, we clearly define various types of rotational motions of anion-groups. Based on such definition, we detect and differentiate such distinct anion-group rotational motions throughout a total of 10’s of ns ab-initio molecular dynamics trajectories. By performing rigorous statistical analysis of various rotational events as well as lithium-ion diffusion events, we reveal how each type of anion rotational motions are related to lithium-ion diffusion. Our research has finally resolved the ongoing debate about the existence of the paddlewheel effect and provide a clear physical understanding of how anion-group rotations are related to fast ionic diffusion in inorganic materials. L. Karlsson, R. L. McGreevy, Mechanisms of ionic conduction in Li2SO4 and LiNaSO4: Paddle wheel or percolation? Solid State Ionics. 76, 301–308 (1995).A. Kvist, A. Lundén, Electrical Conductivity of Solid and Molten Lithium Sulfate. Zeitschrift Für Naturforschung. 20, 235–238 (1965).Z. Zhang, L. F. Nazar, Exploiting the paddle-wheel mechanism for the design of fast ion conductors. Nat Rev Mater, 1–17 (2022).J. G. Smith, D. J. Siegel, Low-temperature paddlewheel effect in glassy solid electrolytes. Nat Commun. 11, 1483 (2020).M. Jansen, Volume Effect or Paddle‐Wheel Mechanism—Fast Alkali‐Metal Ionic Conduction in Solids with Rotationally Disordered Complex Anions. Angewandte Chemie Int Ed Engl. 30, 1547–1558 (1991).

The Surprising Dynamics of the McLafferty Rearrangement.

We report femtosecond time-resolved measurements of the McLafferty rearrangement following the strong-field tunnel ionization of 2-pentanone, 4-methyl-2-pentanone, and 4,4-dimethyl-2-pentanone. The pump-probe-dependent yields of the McLafferty product ion are fit to a biexponential function with fast (∼100 fs) and slow (∼10 ps) time constants, the latter of which is faster for the latter two compounds. Following nearly instantaneous ionization, the fast time scale is associated with rotation of the molecule to a six-membered cyclic intermediate that facilitates transfer of the γ-hydrogen, while the ∼50-100 times longer time scale is associated with a π-bond rearrangement and bond cleavage between the α- and β-carbons to produce the enol cation. These experimental measurements are supported by ab initio molecular dynamics trajectories, which further confirm the time scale of this important stepwise reaction in mass spectrometry.

Theoretical study of time-resolved photoelectron circular dichroism in the photodissociation of a chiral molecule.

Photoelectron circular dichroism (PECD), the forward-backward asymmetry of the photoelectron angular distribution when ionizing randomly oriented chiral molecules with circularly polarized light, is an established method to investigate chiral properties of molecules in their electronic ground state. Here, we develop a computational strategy for predicting time-resolved PECD (TRPECD) of chemical reactions and demonstrate the method on the photodissociation of 1-iodo-2-methylbutane. Our approach combines multi-configurational quantum-chemical calculations of the relevant potential-energy surfaces of the neutral and singly ionized molecule with ab initio molecular-dynamics (AIMD) calculations. The PECD parameters along the AIMD trajectories are calculated with the aid of electron-molecule scattering calculations based on the Schwinger variational principle implemented in ePolyScat. Our calculations have been performed for two probe wavelengths (133 and 160 nm) accessible through low-order harmonic generation in gases. Our results show that the TRPECD is a highly sensitive probe of photochemical reaction dynamics. Most interestingly, the TRPECD is found to change sign multiple times along the photodissociation coordinate, in agreement with recent experiments on CHBrFI [Svoboda et al., "Femtosecond photoelectron circular dichroism of chemical reactions," Sci. Adv. 8, eabq2811 (2022)]. The computational protocol introduced in the present work is general and readily applicable to other chiral photochemical processes.

The effect of chemistry and thermal fluctuations on charge injection barriers at aluminum/polyolefin interfaces

Charge injection at metal/polymer interfaces is a critical process in many technological devices, including high voltage capacitors and cables in which polyolefin materials, such as polyethylene (PE) and polypropylene (PP), are often used as insulation materials. We use simulations based on density-functional theory to study charge injection at aluminum/PE and aluminum/PP interfaces. Specifically, we investigate the influence of incorporating a variety of polar chemical impurities at the PE and PP chain ends on electron and hole injection barriers. Crucially, we account for the effect of thermal disorder by considering ensembles of thousands of interface structures obtained from ab initio molecular dynamics trajectories at 373 K. We show that the mean injection barrier can change by up to 1.1 eV for Al/PE and 0.6 eV for Al/PP, as compared to the pristine case, depending on which chemical impurity is introduced. We also show that the spread of injection barriers from thermal fluctuations also depends strongly on the chemistry of the impurity. The observed trends can be understood with a simple model based on thermal fluctuations of the dipole moment density associated with the chemical impurity at the interface. We further verify this model by considering larger interface models with lower impurity densities. Our results demonstrate that small chemical modifications, which may arise from oxidation, for example, have a significant influence on charge injection barriers in metal/polyolefin interfaces.

Accuracy evaluation of different machine learning force field features

Predicting energies and forces using machine learning force field (MLFF) depends on accurate descriptions (features) of chemical environment. Despite the numerous features proposed, there is a lack of controlled comparison among them for their universality and accuracy. In this work, we compared several commonly used feature types for their ability to describe physical systems. These different feature types include cosine feature, Gaussian feature, moment tensor potential (MTP) feature, spectral neighbor analysis potential feature, simplified smooth deep potential with Chebyshev polynomials feature and Gaussian polynomials feature, and atomic cluster expansion feature. We evaluated the training root mean square error (RMSE) for the atomic group energy, total energy, and force using linear regression model regarding to the density functional theory results. We applied these MLFF models to an amorphous sulfur system and carbon systems, and the fitting results show that MTP feature can yield the smallest RMSE results compared with other feature types for either sulfur system or carbon system in the disordered atomic configurations. Moreover, as an extending test of other systems, the MTP feature combined with linear regression model can also reproduce similar quantities along the ab initio molecular dynamics trajectory as represented by Cu systems. Our results are helpful in selecting the proper features for the MLFF development.

Using Diffusion Maps to Analyze Reaction Dynamics for a Hydrogen Combustion Benchmark Dataset.

We use local diffusion maps to assess the quality of two types of collective variables (CVs) for a recently published hydrogen combustion benchmark dataset1 that contains ab initio molecular dynamics (MD) trajectories and normal modes along minimum energy paths. This approach was recently advocated in2 for assessing CVs and analyzing reactions modeled by classical MD simulations. We report the effectiveness of this approach to molecular systems modeled by quantum ab initio MD. In addition to assessing the quality of CVs, we also use global diffusion maps to perform committor analysis as proposed in.2 We show that the committor function obtained from the global diffusion map allows us to identify transition regions of interest in several hydrogen combustion reaction channels.

Sensitivity of the Kβ″ X-ray Emission Line to Coordination Changes in GeO2 and TiO2.

The hard X-ray Kβ″ emission line shows sensitivity with respect to a wide range of cation-ligand coordination, which we investigate in the cases of GeO2 and TiO2 on the basis of ab initio spectral calculations on amorphous and crystalline structures. In compressed amorphous GeO2, the sampling of a large number of instantaneous coordination polyhedra from an ab initio molecular dynamics trajectory reveals that the functional relation between the Kβ″ shift and coordination is close to linear between 4-fold and 7-fold coordination. A similar sensitivity of the Kβ″ emission line exists in the coordination range between six and nine of crystalline high-pressure TiO2 polymorphs. Our results demonstrate the potential of the Kβ″ emission line in research on the structure of amorphous oxide material.

Shedding light on the metal-phthalocyanine EXAFS spectra through classical and ab initio molecular dynamics.

Extended X-Ray Absorption Fine Structure (EXAFS) theoretical spectra for some 3d transition metal-phthalocyanines-FePc, NiPc, CuPc, and ZnPc-are presented. Their complexity and rigidity make them a good testbed for the development of theoretical strategies that can complement the difficulties present in the experimental spectrum fitting. Classical and ab initio molecular dynamics trajectories are generated and employed as a source of structural information to compute average spectra for each MPc species. The original ZnPc force field employed in the classical molecular dynamics simulations has been modified in order to improve the agreement with the experimental EXAFS spectrum, and the modification strategy-based on MP2 optimized structures-being extended to the rest of MPcs. Both types of trajectories, classical and ab initio, provide very similar results, showing in all cases the main features present in the experimental spectra despite the different simulation timescales employed. Spectroscopical information has been analyzed on the basis of shells and legs contributions, making possible the comparison with the experimental fitting approaches. According to the simulations results, the simple relationships employed in the fitting process to define the dependence of the Debye Waller factors associated with multiple scattering paths with those of single scattering paths are reasonable. However, a lack of multiple backscattering paths contributions is found due to the intrinsic rigidity of the chemical motif (macrocycle). Its consequences in the Debye Waller factors of the fitted contributions are discussed.

Hydrogen Bonding and Infrared Spectra of Ethyl-3-methylimidazolium Bis(trifluoromethylsulfonyl)imide/Water Mixtures: A View from Molecular Dynamics Simulations

Simulations of ab initio molecular dynamics have been performed for mixtures of ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (EMIM-TFSI) ionic liquid and water. Statistics of donors and acceptors of hydrogen bonds has revealed that with increasing water content, hydrogen bonds between EMIM cations and TFSI anions are replaced by bonds to water molecules. In the mixture of liquids, the total number of bonds (from EMIM cations or water molecules) formed by TFSI acceptors increases. IR spectra obtained from ab initio molecular dynamics trajectories are in good agreement with literature data for ionic liquid/water systems. Analysis of oscillations of individual C-H and O-H bonds has shown correlations between vibrational frequencies and hydrogen bonds formed by an EMIM cation or water molecule and has indicated that the changes in the IR spectrum result from the decreased number of water-water hydrogen bonds in the mixture. The tests of DFTB methodology with tailored parameterizations have yielded reasonably good description of the IR spectrum of bulk water, whereas available parameterizations have failed in satisfactory reproduction of the IR spectrum of EMIM-TFSI/water mixtures in the region above 3000 cm-1.

Hybrid Functional and Plane Waves based Ab Initio Molecular Dynamics Study of the Aqueous Fe2+ /Fe3+ Redox Reaction.

Kohn-Sham density functional theory and plane wave basis set based ab initio molecular dynamics (AIMD) simulation is a powerful tool for studying complex reactions in solutions, such as electron transfer (ET) reactions involving Fe2+ /Fe3+ ions in water. In most cases, such simulations are performed using density functionals at the level of Generalized Gradient Approximation (GGA). The challenge in modelling ET reactions is the poor quality of GGA functionals in predicting properties of such open-shell systems due to the inevitable self-interaction error (SIE). While hybrid functionals can minimize SIE, standard plane-wave based AIMD at that level of theory is typically 150 times slower than GGA for systems containing ∼100 atoms. Among several approaches reported to speed-up AIMD simulations with hybrid functionals, the noise-stabilized MD (NSMD) procedure, together with the use of localized orbitals to compute the required exchange integrals, is an attractive option. In this work, we demonstrate the application of the NSMD approach for studying the Fe2+ /Fe3+ redox reaction in water. It is shown here that long AIMD trajectories at the level of hybrid density functionals can be obtained using this approach. Redox properties of the aqueous Fe2+ /Fe3+ system computed from these simulations are compared with the available experimental data for validation.

Graph Theoretic Molecular Fragmentation for Multidimensional Potential Energy Surfaces Yield an Adaptive and General Transfer Machine Learning Protocol.

Over a series of publications we have introduced a graph-theoretic description for molecular fragmentation. Here, a system is divided into a set of nodes, or vertices, that are then connected through edges, faces, and higher-order simplexes to represent a collection of spatially overlapping and locally interacting subsystems. Each such subsystem is treated at two levels of electronic structure theory, and the result is used to construct many-body expansions that are then embedded within an ONIOM-scheme. These expansions converge rapidly with many-body order (or graphical rank) of subsystems and have been previously used for ab initio molecular dynamics (AIMD) calculations and for computing multidimensional potential energy surfaces. Specifically, in all these cases we have shown that CCSD and MP2 level AIMD trajectories and potential surfaces may be obtained at density functional theory cost. The approach has been demonstrated for gas-phase studies, for condensed phase electronic structure, and also for basis set extrapolation-based AIMD. Recently, this approach has also been used to derive new quantum-computing algorithms that enormously reduce the quantum circuit depth in a circuit-based computation of correlated electronic structure. In this publication, we introduce (a) a family of neural networks that act in parallel to represent, efficiently, the post-Hartree-Fock electronic structure energy contributions for all simplexes (fragments), and (b) a new k-means-based tessellation strategy to glean training data for high-dimensional molecular spaces and minimize the extent of training needed to construct this family of neural networks. The approach is particularly useful when coupled cluster accuracy is desired and when fragment sizes grow in order to capture nonlocal interactions accurately. The unique multidimensional k-means tessellation/clustering algorithm used to determine our training data for all fragments is shown to be extremely efficient and reduces the needed training to only 10% of data for all fragments to obtain accurate neural networks for each fragment. These fully connected dense neural networks are then used to extrapolate the potential energy surface for all molecular fragments, and these are then combined as per our graph-theoretic procedure to transfer the learning process to a full system energy for the entire AIMD trajectory at less than one-tenth the cost as compared to a regular fragmentation-based AIMD calculation.

Role of lone-pair electron localization in temperature-induced phase transitions in mimetite.

The crystal structure of mimetite Pb5(AsO4)3Cl, a phosphate with apatite structure-type has been investigated in situ at 123, 173, 273, 288, 353 and 393 K. A careful inspection of the diffraction pattern and subsequent structure refinements indicated that mimetite transforms from the monoclinic to the hexagonal polymorph with increasing temperature. At 123 K, a monoclinic superstructure, mimetite-2M, with cell parameters a = 20.4487 (9), b = 7.4362 (2), c = 20.4513 (9) Å, β = 119.953 (6)°, V = 2694.5 (2) Å3 and space group P21 was observed. From 173 to 353 K, the reflections of the supercell were evident only along one direction of the corresponding hexagonal apatite-cell and the structure transforms to the polymorph mimetite-M with space group P21/b and unit-cell parameters a = 10.2378 (3), b = 20.4573 (7), c = 7.4457 (2) Å, β = 120.039 (5)°, V = 1349.96 (9) Å3. Only at higher temperature, i.e. 393 K, does mimetite adopt the hexagonal space group P63/m characteristic of apatite structure-types. The role of the electron lone pairs of Pb atoms in the phase transition was investigated through the analysis of the electron localization function (ELF) calculated based on the DFT-geometry optimized structures of the three polymorphs. The changes in spatial distribution of the 6s2 electron density during the phase transitions were explored by means of the Wannier Function Centres (WFCs) derived from ab initio molecular dynamics trajectories. In the high-temperature hexagonal structure the 6s2 electrons are spherically symmetric relative to the position of Pb atoms. At low temperature the maximum of 6s2 electron density is displaced relative to the position of Pb atom contributing to the polar interaction in the monoclinic polymorphs.