Multi-scale molecular dynamics of perovskite quantum dots: from atomic fluctuations to predictive stability design.

Enhancing air-stability of CH3NH3PbBr3 perovskite quantum dots by in-situ growth in metal-organic frameworks and their applications in light emitting diodes

Finite temperature ab initio molecular dynamics (AIMD), in which forces are obtained from "on-the-fly" electronic structure calculations, is a widely used technique for studying structural and dynamical properties of chemically active systems. Recently, we introduced an AIMD scheme based on discrete variable representation (DVR) basis sets, which was shown to have improved convergence properties over the conventional plane wave (PW) basis set [Liu,Y.; et al. Phys. Rev. B 2003, 68, 125110]. In the present work, the numerical algorithms for the DVR based AIMD scheme (DVR/AIMD) are provided in detail, and the latest developments of the approach are presented. The accuracy and stability of the current implementation of the DVR/AIMD scheme are tested by performing a simulation of liquid water at ambient conditions. The structural information obtained from the present work is in good agreement with the result of recent AIMD simulations with a PW basis set (PW/AIMD). Advantages of using the DVR/AIMD scheme over the PW/AIMD method are discussed. In particular, it is shown that a DVR/AIMD simulation of liquid water in the complete basis set limit is possible with a relatively small number of grid points.

We review our recent work that employs a series of computational techniques including density functional theory, ab initio molecular dynamics, and classical molecular dynamics to investigate changes in the structure and electronic properties of Pt-based alloy catalysts under oxygen reduction reaction conditions in acid medium. We show density-functional theory-based correlations between surface segregation and the oxidation state of the subsurface atoms, and their effects on metal dissolution. Since the onset of Pt dissolution coincides with that of surface oxidation, surface reconstruction phenomena is evaluated using ab initio and classical molecular dynamics at increasing degrees of oxidation on extended surfaces and nanoparticles, including the effects of water and an acidic solution. Significant reconstruction and compositional changes are observed as the surface is modified by the presence of adsorbates and electrolyte components. Finally we discuss the consequences of dealloying and suggest an explanation for the enhanced activity observed experimentally in the resultant nanoporous structures.

The past decade has witnessed the increasing interest in cesium lead halide perovskite quantum dots (PQDs) for their excellent optical properties with higher photoluminescence efficiency and tunable emission wavelengths widely applied in white LED, photovoltaic devices, etc. Here we report the preparation of CsPbBr3 PQDs by a facile anti-solvent method using conventional quaternary ammonium bromide (CTAB) as a double modifier-both proper alkyl group protection and bromine source donator. The as-formed PQDs are well-monodispersed cubes with a size of 10-15 nm and high photoluminescence quantum yield (PLQY) of up to 43 %. To enhance the stability of PQDs, CsPbBr3 @PS microspheres were formed by electrospraying process. The microspheres not only show excellent luminous properties, but exhibit much higher stability against air and UV light irradiation due to the super hydrophobic property of polystyrene.

Lithium borosilicate (LBS) glass is a prototypical lithium-ion conducting oxide glass available for an all-solid-state buttery. Nevertheless, the atomistic modeling of LBS glass using ab initio (AIMD) and classical molecular dynamics (CMD) simulations has critical limitations due to computational cost and inaccuracy in reproducing the glass microstructures, respectively. To overcome these difficulties, a machine-learning potential (MLP) was examined in this work for modeling LBS glasses using DeepMD. The glass structures obtained by this MLP possessed 4-fold coordinated boron (4B) confirmed well with the experimental data and abundance of three-membered rings. The models were energetically more stable compared with those constructed with a functional force field even though both the models included reasonable 4B. The results confirmed MLP to be superior to model the boron-containing glasses and address the inherent shortcomings of the AIMD and CMD. This study also discusses some limitations of MLP for modeling glasses.

In this Letter, we combine first-principles calculations with the non-adiabatic molecular dynamics (NAMD) method to investigate the photocatalytic and excited-state properties of blue phosphorene (BlueP). Doping with Group III A elements not only maintains an appropriate bandgap and band edge positions for photocatalytic water splitting but also converts the indirect bandgap of BlueP to a direct bandgap, significantly enhancing photon absorption efficiency. The dopants effectively improve optical absorption in the visible and ultraviolet light regions, potentially enabling a solar-to-hydrogen conversion efficiency of 22.3% in the photocatalytic water splitting process. In NAMD calculations, we consider the dynamics of the electron–hole pair recombination process between the valence band maximum and conduction band minimum. We demonstrate the regulatory impact of dopant elements, temperature, and non-adiabatic coupling strength on the exciton lifetime of doped BlueP through ab initio molecular dynamics and NAMD methods. This study reveals the relationship between the charge transfer mechanism and non-adiabatic coupling in low-dimensional materials, offering valuable insights into the excited-state properties of optoelectronic materials. Ultimately, our findings contribute to the development of tunable, long-lived exciton lifetimes and high carrier mobilities in doped BlueP, which hold significant potential for photocatalytic water splitting to generate hydrogen.

Highly stable CsPbBr3 perovskite quantum dots incorporated in aluminum stearate

Owing to their large absorption cross-sections and high photoluminescence quantum yields, lead halide perovskite quantum dots (PQDs) are regarded as a promising candidate for various optoelectronics applications. However, easy degradation of PQDs in water and in a humid environment is a critical hindrance for applications. Here we develop a Pb-S bonding approach to synthesize water-resistant perovskite@silica nanodots keeping their emission in water for over six weeks. A two-photon whispering-gallery mode laser device made of these ultra-stable nanodots retain 80% of its initial emission quantum yield when immersed in water for 13 h, and a two-photon random laser based on the perovskite@silica nanodots powder could still operate after the nanodots were dispersed in water for up to 15 days. Our synthetic approach opens up an entirely new avenue for utilizing PQDs in aqueous environment, which will significantly broaden their applications not only in optoelectronics but also in bioimaging and biosensing.

One-step preparation of excellent flexible ethyl cellulose composite film for LED

Germanium telluride (GeTe) is an important functional material that has been attracting extensive research attention. Challenges such as phase transition processes and crystallization of amorphous GeTe cannot yet be accurately calculated using ab initio molecular dynamics because of the time limitations of density functional theory calculations. Molecular dynamics simulation using empirical potentials can address the aforementioned issues. However, their accuracy relies on the validity of the empirical interatomic potential. With the advancement of computational methodologies within materials science and engineering, machine learning potentials (MLPs) have garnered substantial interest. In this paper, we review the applications of MLPs, including neural network potential, Gaussian approximation potentials, and neuroevolution potential, in studying the phonon properties of GeTe. Our focus includes the crystallization of amorphous GeTe, the mechanisms underlying structural phase transitions, and thermal conductivity. These advancements can offer valuable guidance for the utilization of GeTe in advanced thermal management and contribute to the exploration of MLPs in phonon physics.

We present the absolute enthalpy, entropy, heat capacity, and free energy of liquid water at ambient conditions calculated by the two-phase thermodynamic method applied to ab initio, reactive and classical molecular dynamics simulations. We find that the absolute entropy and heat capacity of liquid water from ab initio molecular dynamics (AIMD) is underestimated, but falls within the range of the flexible empirical as well as the reactive force fields. The origin of the low absolute entropy of liquid water from AIMD simulations is due to an underestimation of the translational entropy by 20% and the rotational entropy by 40% compared to the TIP3P classical water model, consistent with previous studies that reports low diffusivity and increased ordering of liquid water from AIMD simulations. Classical MD simulations with rigid water models tend to be in better agreement with experiment (in particular TIP3P yielding the best agreement), although the TIP4P-ice water model, the only empirical force field that reproduces the experimental melting temperature, has the lowest entropy, perhaps expectedly. This reiterates the limitations of existing empirical water models in simultaneously capturing the thermodynamics of solid and liquid phases. We find that the quantum corrections to heat capacity of water can be as large as 60%. Although certain water models are computed to yield good absolute free energies of water compared to experiments, they are often due to the fortuitous enthalpy-entropy cancellation, but not necessarily due to the correct descriptions of enthalpy and entropy separately.

Due to the increased concern about energy and environmental issues, significant attention has been paid to the development of large-scale energy storage devices to facilitate the utilization of clean energy sources. The redox flow battery (RFB) is one of the most promising systems. Recently, the high cost of transition-metal complex-based RFB has promoted the development of aqueous RFBs with redox-active organic molecules. To expand the working voltage, computational chemistry has been applied to search for organic molecules with lower or higher redox potentials. However, redox potential computation based on implicit solvation models would be challenging due to difficulty in parametrization when considering the complex solvation of supporting electrolytes. Besides, although ab initio molecular dynamics (AIMD) describes the supporting electrolytes with the same level of electronic structure theory as the redox couple, the application is impeded by the high computation costs. Recently, machine learning molecular dynamics (MLMD) has been illustrated to accelerate AIMD by several orders of magnitude without sacrificing the accuracy. It has been established that redox potentials can be computed by MLMD with two separated machine learning potentials (MLPs) for reactant and product states, which is redundant and inefficient. In this work, an automated workflow is developed to construct a universal MLP for both states, which can compute the redox potentials or acidity constants of redox-active organic molecules more efficiently. Furthermore, the predicted redox potentials can be evaluated at the hybrid functional level with much lower costs, which would facilitate the design of aqueous organic RFBs.

Theoretical spectroscopy is mandatory for a precise understanding and assignment of experimental spectra recorded at finite temperature. We review here room temperature DFT-based molecular dynamics simulations for the purpose of interpreting finite temperature infrared spectra of peptides of increasing size and complexity, in terms of temperature-dependent conformational dynamics and flexibility, and vibrational anharmonicities (potential energy surface anharmonicities, vibrational mode couplings and dipole anharmonicities). We take examples from our research projects in order to illustrate the main key-points and strengths of dynamical spectra modeling in that context. The calculations are presented in relation to room temperature gas phase IR-MPD experiments and room temperature liquid phase IR absorption experiments. These illustrations of floppy polypeptides have been chosen in order to convey the following ideas: temperature-dependent spectra modeling is pivotal for a precise understanding of gas phase spectra recorded at room temperature, including conformational dynamics and vibrational anharmonicities; harmonic spectroscopy (as commonly performed in the literature) can be misleading and even erroneous for a proper interpretation of spectra recorded at finite temperature; taking into account vibrational anharmonicities is pivotal for a proper interplay between theory and experiments; amide I-III bands are not necessarily the most relevant fingerprints for unraveling the local structures of peptides and more complex systems; liquid phase simulations have unraveled relationships between the zwitterionic properties of the peptide bonds and infrared signatures. The review presents a state-of-the-art account of the domain and offers perspectives and new developments for future still more challenging applications.

The melting curve of the hexagonal close-packed (hcp) phase of lead (Pb) has been determined over a wide pressure range using both ab initio molecular dynamics (AIMD) simulations and classical molecular dynamics (CMD) employing an effective pair potential. The AIMD simulations are based on a density functional theory (DFT) in the generalized gradient approximation (GGA). The Pb melting curve, constructed using a well-established theoretical scheme, is in excellent agreement with the AIMD results. Our calculated equation of state (EOS) of hcp Pb is in excellent agreement with experimental data up to $40\phantom{\rule{0.3em}{0ex}}\mathrm{GPa}$. Our melting curve agrees very well with melting temperatures obtained in both shock-wave and diamond-anvil cell (DAC) experiments, but at higher pressures our curve lies between the two data sets.

Lead halide perovskite quantum dots (PeQDs) are triggering a revolution in display technologies because of their near-unity photoluminescence quantum yield (PLQY), narrow band emission, wide tunable bandgap and facile synthesis. Therefore, they have been extensively investigated as color converters or emissive layers for light-emitting diode (LED) displays. However, the poor stabilities in the phase and structure of PeQDs make them hard to be practically applie, and the ultimate goal is therefore to improve the long-term stability of PeQDs. The poor stability of PeQDs originates from their inherent ionic nature. Under external conditions (such as light, heat, water and oxygen), PeQDs will decompose through interfacial reactions, leading to obvious fluorescence quenching. Although many efforts have been made to prepare robust PeQDs that are, to some extent, resistant to water, air, light, or heat exposure, he overall reliability of PeQDs shows limited improvement under the synergistic effects of multiple factors, which are usually the case in practical LED applications. We report ultrastable CsPbBr3:Sr/PbBr(OH)/molecular sieve composites (Fig. 1) with a high photoluminescence quantum yield of 75% and high overall stability when exposed to water, blue light and heat, owing to (i) the increased formation energy of CsPbBr3 PeQDs by Sr doping and (ii) good encapsulation by PbBr(OH) and molecular sieves. These composites maintain 54% of their initial intensity after being aged at 85°C and 150 mW/cm2 for 720 min, which is superior to commercial green CdSe-based QDs. These promising composites are then used to produce Mini-LED backlights with a high luminous efficacy of 86 lm/W and a color area of ~124% of the National Television Standards Committee or 93% of the Rec. 2020 standards by combining them with red CdSe/CdS/ZnS QDs and a blue Mini-LED chip. We believe that highly reliable PeQDs can be achieved by building well-designed composite structures, thus enabling them to be practically applied in emerging lighting and displays. Figure 1