From Chalcogen Bonding to S-π Interactions in Hybrid Perovskite Photovoltaics.

The stability of hybrid organic-inorganic halide perovskite semiconductors remains a significant obstacle to their application in photovoltaics. To this end, the use of low-dimensional (LD) perovskites, which incorporate hydrophobic organic moieties, provides an effective strategy to improve their stability, yet often at the expense of their performance. To address this limitation, supramolecular engineering of noncovalent interactions between organic and inorganic components has shown potential by relying on hydrogen bonding and conventional van der Waals interactions. Here, the capacity to access novel LD perovskite structures that uniquely assemble through unorthodox S-mediated interactions is explored by incorporating benzothiadiazole-based moieties. The formation of S-mediated LD structures is demonstrated, including one-dimensional (1D) and layered two-dimensional (2D) perovskite phases assembled via chalcogen bonding and S-π interactions. This involved a combination of techniques, such as single crystal and thin film X-ray diffraction, as well as solid-state NMR spectroscopy, complemented by molecular dynamics simulations, density functional theory calculations, and optoelectronic characterization, revealing superior conductivities of S-mediated LD perovskites. The resulting materials are applied in n-i-p and p-i-n perovskite solar cells, demonstrating enhancements in performance and operational stability that reveal a versatile supramolecular strategy in photovoltaics.

MiMiC: A high-performance framework for multiscale molecular dynamics simulations.

MiMiC is a framework for performing multiscale simulations in which loosely coupled external programs describe individual subsystems at different resolutions and levels of theory. To make it highly efficient and flexible, we adopt an interoperable approach based on a multiple-program multiple-data (MPMD) paradigm, serving as an intermediary responsible for fast data exchange and interactions between the subsystems. The main goal of MiMiC is to avoid interfering with the underlying parallelization of the external programs, including the operability on hybrid architectures (e.g., CPU/GPU), and keep their setup and execution as close as possible to the original. At the moment, MiMiC offers an efficient implementation of electrostatic embedding quantum mechanics/molecular mechanics (QM/MM) that has demonstrated unprecedented parallel scaling in simulations of large biomolecules using CPMD and GROMACS as QM and MM engines, respectively. However, as it is designed for high flexibility with general multiscale models in mind, it can be straightforwardly extended beyond QM/MM. In this article, we illustrate the software design and the features of the framework, which make it a compelling choice for multiscale simulations in the upcoming era of exascale high-performance computing.

Multiscale biomolecular simulations in the exascale era.

The complexity of biological systems and processes, spanning molecular to macroscopic scales, necessitates the use of multiscale simulations to get a comprehensive understanding. Quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations are crucial for capturing processes beyond the reach of classical MD simulations. The advent of exascale computing offers unprecedented opportunities for scientific exploration, not least within life sciences, where simulations are essential to unravel intricate molecular mechanisms underlying biological processes. However, leveraging the immense computational power of exascale computing requires innovative algorithms and software designs. In this context, we discuss the current status and future prospects of multiscale biomolecular simulations on exascale supercomputers with a focus on QM/MM MD. We highlight our own efforts in developing a versatile and high-performance multiscale simulation framework with the aim of efficient utilization of state-of-the-art supercomputers. We showcase its application in uncovering complex biological mechanisms and its potential for leveraging exascale computing.

Oxidative Defect Detection Within Free and Packed DNA Systems: A Quantum Mechanical/Molecular Mechanics (QM/ MM) Approach.

Base excision repair enzymes (BERs) detect and repair oxidative DNA damage with efficacy despite the small size of the defects and their often only minor structural impact. A charge transfer (CT) model for rapid scanning of DNA stretches has been evoked to explain the high detection rate in the face of numerous, small lesions. The viability of CT DNA defect detection is explored via hybrid QM/MM computational studies that leverage the accuracy of quantum mechanics (QM) for a region of interest and the descriptive power of molecularmechanics (MM) for the remainder of the system. We find that the presence of an oxidative lesion lowers theredox free energy of oxidation by approximately 1.0 eV regardless of DNA compaction (free DNA versus packed DNA in nucleosome core particles) and damage location indicating the high feasibility of a CT-based process for defect detection in DNA.

Structure and dynamics of liquid water from ab initio simulations: adding Minnesota density functionals to Jacob's ladder.

The accurate representation of the structural and dynamical properties of water is essential for simulating the unique behavior of this ubiquitous solvent. Here we assess the current status of describing liquid water using ab initio molecular dynamics, with a special focus on the performance of all the later generation Minnesota functionals. Findings are contextualized within the current knowledge on DFT for describing bulk water under ambient conditions and compared to experimental data. We find that, contrary to the prevalent idea that local and semilocal functionals overstructure water and underestimate dynamical properties, M06-L, revM06-L, and M11-L understructure water, while MN12-L and MN15-L overdistance water molecules due to weak cohesive effects. This can be attributed to a weakening of the hydrogen bond network, which leads to dynamical fingerprints that are over fast. While most of the hybrid Minnesota functionals (M06, M08-HX, M08-SO, M11, MN12-SX, and MN15) also yield understructured water, their dynamical properties generally improve over their semilocal counterparts. It emerges that exact exchange is a crucial component for accurately describing hydrogen bonds, which ultimately leads to corrections in both the dynamical and structural properties. However, an excessive amount of exact exchange strengthens hydrogen bonds and causes overstructuring and slow dynamics (M06-HF). As a compromise, M06-2X is the best performing Minnesota functional for water, and its D3 corrected variant shows very good structural agreement. From previous studies considering nuclear quantum effects (NQEs), the hybrid revPBE0-D3, and the rung-5 RPA (RPA@PBE) have been identified as the only two approximations that closely agree with experiments. Our results suggest that the M06-2X(-D3) functionals have the potential to further improve the reproduction of experimental properties when incorporating NQEs through path integral approaches. This work provides further proof that accurate modeling of water interactions requires the inclusion of both exact exchange and balanced (non-local) correlation, highlighting the need for higher rungs on Jacob's ladder to achieve predictive simulations of complex biological systems in aqueous environments.

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit.

Second-order Møller-Plesset perturbation theory (MP2) is the most expedient wave function-based method for considering electron correlation in quantum chemical calculations and, as such, provides a cost-effective framework to assess the effects of basis sets on correlation energies, for which the complete basis set (CBS) limit can commonly only be obtained via extrapolation techniques. Software packages providing MP2 energies are commonly based on atom-centered bases with innate issues related to possible basis set superposition errors (BSSE), especially in the case of weakly bonded systems. Here, we present noncovalent interaction energies in the CBS limit, free of BSSE, for 20 dimer systems of the S22 data set obtained via a highly parallelized MP2 implementation in the plane-wave pseudopotential molecular dynamics package CPMD. The specificities related to plane waves for accurate and efficient calculations of gas-phase energies are discussed, and results are compared to the localized (aug-)cc-pV[D,T,Q,5]Z correlation-consistent bases as well as their extrapolated CBS estimates. We find that the BSSE-corrected aug-cc-pV5Z basis can provide MP2 energies highly consistent with the CBS plane wave values with a minimum mean absolute deviation of ∼0.05 kcal/mol without the application of any extrapolation scheme. In addition, we tested the performance of 13 different extrapolation schemes and found that the X-3 expression applied to the (aug-)cc-pVXZ bases provides the smallest deviations against CBS plane wave values if the extrapolation sequence is composed of points D and T, while (X+12)-4 performs slightly better for TQ and Q5 extrapolations. Also, we propose A(X-12)-3+B(X+12)-4 as a reliable alternative to extrapolate total energies from the DTQ, TQ5, or DTQ5 data points. In spite of the general good agreement between the values obtained from the two types of basis sets, it is noticed that differences between plane waves and (aug-)cc-pVXZ basis sets, extrapolated or not, tend to increase with the number of electrons, thus raising the question of whether these discrepancies could indeed limit the attainable accuracy for localized bases in the limit of large systems.

Redox-Based Defect Detection in Packed DNA: Insights from Hybrid Quantum Mechanical/Molecular Mechanics Molecular Dynamics Simulations.

The impact of an 8-oxoguanine (8oxoG) defect on the redox properties of DNA within the nucleosome core particle (NCP) was investigated employing hybrid quantum mechanical/molecular mechanics (QM/MM) molecular dynamics simulations of native and 8oxoG-containing NCP systems with an explicit representation of a biologically relevant environment. Two distinct NCP positions with varying solvent accessibility were considered for 8oxoG insertion. In both cases, it is found that the presence of 8oxoG drastically decreases the redox free energy of oxidation by roughly 1 eV, which is very similar to what was recently reported for free native and 8oxoG-containing DNA. In contrast, the effect of 8oxoG on the reorganization free energy is even smaller for packed DNA (decrease of 0.13 and 0.01 eV for defect-free and defect-containing systems, respectively) compared to the one for free DNA (0.25 eV), consistent with the increased rigidity of the NCP as compared to free DNA. Furthermore, the presence of an 8oxoG defect does not yield any significant changes in the packed DNA structure. Such a conclusion favors the idea that in the case of chromatin, defect-induced changes in DNA redox chemistry can also be exploited to detect damaged bases via DNA-mediated hole transfer.

Low-loss contacts on textured substrates for inverted perovskite solar cells.

Inverted perovskite solar cells (PSCs) promise enhanced operating stability compared to their normal-structure counterparts1-3. To improve efficiency further, it is crucial to combine effective light management with low interfacial losses4,5. Here we develop a conformal self-assembled monolayer (SAM) as the hole-selective contact on light-managing textured substrates. Molecular dynamics simulations indicate that cluster formation during phosphonic acid adsorption leads to incomplete SAM coverage. We devise a co-adsorbent strategy that disassembles high-order clusters, thus homogenizing the distribution of phosphonic acid molecules, and thereby minimizing interfacial recombination and improving electronic structures. We report a laboratory-measured power conversion efficiency (PCE) of 25.3% and a certified quasi-steady-state PCE of 24.8% for inverted PSCs, with a photocurrent approaching 95% of the Shockley-Queisser maximum. An encapsulated device having a PCE of 24.6% at room temperature retains 95% of its peak performance when stressed at 65 °C and 50% relative humidity following more than 1,000 h of maximum power point tracking under 1 sun illumination. This represents one of the most stable PSCs subjected to accelerated ageing: achieved with a PCE surpassing 24%. The engineering of phosphonic acid adsorption on textured substrates offers a promising avenue for efficient and stable PSCs. It is also anticipated to benefit other optoelectronic devices that require light management.

Tautomeric mixture coordination enables efficient lead-free perovskite LEDs.

Lead halide perovskite light-emitting diodes (PeLEDs) have demonstrated remarkable optoelectronic performance1-3. However, there are potential toxicity issues with lead4,5 and removing lead from the best-performing PeLEDs-without compromising their high external quantum efficiencies-remains a challenge. Here we report a tautomeric-mixture-coordination-induced electron localization strategy to stabilize the lead-free tin perovskite TEA2SnI4 (TEAI is 2-thiopheneethylammonium iodide) by incorporating cyanuric acid. We demonstrate that a crucial function of the coordination is to amplify the electronic effects, even for those Sn atoms that aren't strongly bonded with cyanuric acid owing to the formation of hydrogen-bonded tautomeric dimer and trimer superstructures on the perovskite surface. This electron localization weakens adverse effects from Anderson localization and improves ordering in the crystal structure of TEA2SnI4. These factors result in a two-orders-of-magnitude reduction in the non-radiative recombination capture coefficient and an approximately twofold enhancement in the exciton binding energy. Our lead-free PeLED has an external quantum efficiency of up to 20.29%, representing a performance comparable to that of state-of-the-art lead-containing PeLEDs6-12. We anticipate that these findings will provide insights into the stabilization of Sn(II) perovskites and further the development of lead-free perovskite applications.

Metal3D: a general deep learning framework for accurate metal ion location prediction in proteins.

Metal ions are essential cofactors for many proteins and play a crucial role in many applications such as enzyme design or design of protein-protein interactions because they are biologically abundant, tether to the protein using strong interactions, and have favorable catalytic properties. Computational design of metalloproteins is however hampered by the complex electronic structure of many biologically relevant metals such as zinc . In this work, we develop two tools - Metal3D (based on 3D convolutional neural networks) and Metal1D (solely based on geometric criteria) to improve the location prediction of zinc ions in protein structures. Comparison with other currently available tools shows that Metal3D is the most accurate zinc ion location predictor to date with predictions within 0.70 ± 0.64 Å of experimental locations. Metal3D outputs a confidence metric for each predicted site and works on proteins with few homologes in the protein data bank. Metal3D predicts a global zinc density that can be used for annotation of computationally predicted structures and a per residue zinc density that can be used in protein design workflows. Currently trained on zinc, the framework of Metal3D is readily extensible to other metals by modifying the training data.

MiMiCPy: An Efficient Toolkit for MiMiC-Based QM/MM Simulations.

MiMiC is a highly flexible, extremely scalable multiscale modeling framework. It couples the CPMD (quantum mechanics, QM) and GROMACS (molecular mechanics, MM) codes. The code requires preparing separate input files for the two programs with a selection of the QM region. This can be a tedious procedure prone to human error, especially when dealing with large QM regions. Here, we present MiMiCPy, a user-friendly tool that automatizes the preparation of MiMiC input files. It is written in Python 3 with an object-oriented approach. The main subcommand PrepQM can be used to generate MiMiC inputs directly from the command line or through a PyMOL/VMD plugin for visually selecting the QM region. Many other subcommands are also provided for debugging and fixing MiMiC input files. MiMiCPy is designed with a modular structure that allows seamless extensions to new program formats depending on the requirements of MiMiC.

Surrogate Based Genetic Algorithm Method for Efficient Identification of Low-Energy Peptide Structures.

Identification of the most stable structure(s) of a system is a prerequisite for the calculation of any of its properties from first-principles. However, even for relatively small molecules, exhaustive explorations of the potential energy surface (PES) are severely hampered by the dimensionality bottleneck. In this work, we address the challenging task of efficiently sampling realistic low-lying peptide coordinates by resorting to a surrogate based genetic algorithm (GA)/density functional theory (DFT) approach (sGADFT) in which promising candidates provided by the GA are ultimately optimized with DFT. We provide a benchmark of several computational methods (GAFF, AMOEBApro13, PM6, PM7, DFTB3-D3(BJ)) as possible prescanning surrogates and apply sGADFT to two test case systems that are (i) two isomer families of the protonated Gly-Pro-Gly-Gly tetrapeptide (Masson, A.; J. Am. Soc. Mass Spectrom.2015, 26, 1444-1454) and (ii) the doubly protonated cyclic decapeptide gramicidin S (Nagornova, N. S.; J. Am. Chem. Soc.2010, 132, 4040-4041). We show that our GA procedure can correctly identify low-energy minima in as little as a few hours. Subsequent refinement of surrogate low-energy structures within a given energy threshold (≤10 kcal/mol (i), ≤5 kcal/mol (ii)) via DFT relaxation invariably led to the identification of the most stable structures as determined from high-resolution infrared (IR) spectroscopy at low temperature. The sGADFT method therefore constitutes a highly efficient route for the screening of realistic low-lying peptide structures in the gas phase as needed for instance for the interpretation and assignment of experimental IR spectra.

Hydration dynamics and IR spectroscopy of 4-fluorophenol.

Halogenated groups are relevant in pharmaceutical applications and potentially useful spectroscopic probes for infrared spectroscopy. In this work, the structural dynamics and infrared spectroscopy of para-fluorophenol (F-PhOH) and phenol (PhOH) is investigated in the gas phase and in water using a combination of experiment and molecular dynamics (MD) simulations. The gas phase and solvent dynamics around F-PhOH and PhOH is characterized from atomistic simulations using empirical energy functions with point charges or multipoles for the electrostatics, Machine Learning (ML) based parametrizations and with full ab initio (QM) and mixed Quantum Mechanical/Molecular Mechanics (QM/MM) simulations with a particular focus on the CF- and OH-stretch region. The CF-stretch band is heavily mixed with other modes whereas the OH-stretch in solution displays a characteristic high-frequency peak around 3600 cm-1 most likely associated with the -OH group of PhOH and F-PhOH together with a characteristic progression below 3000 cm-1 due to coupling with water modes which is also reproduced by several of the simulations. Solvent and radial distribution functions indicate that the CF-site is largely hydrophobic except for simulations using point charges which renders them unsuited for correctly describing hydration and dynamics around fluorinated sites. The hydrophobic character of the CF-group is particularly relevant for applications in pharmaceutical chemistry with a focus on local hydration and interaction with the surrounding protein.

Interplay of Kinetic and Thermodynamic Reaction Control Explains Incorporation of Dimethylammonium Iodide into CsPbI3.

CsPbI3 is a promising material for optoelectronics owing to its thermal robustness and favorable bandgap. However, its fabrication is challenging because its photoactive phase is thermodynamically unstable at room temperature. Adding dimethylammonium (DMA) alleviates this instability and is currently understood to result in the formation of DMA x Cs1-x PbI3 perovskite solid solutions. Here, we use NMR of the 133Cs and 13C local structural probes to show that these solid solutions are not thermodynamically stable, and their synthesis under thermodynamic control leads to a segregated mixture of yellow one-dimensional DMAPbI3 phase and δ-CsPbI3. We show that mixed-cation DMA x Cs1-x PbI3 perovskite phases only form when they are kinetically trapped by rapid antisolvent-induced crystallization. We explore the energetics of DMA incorporation into CsPbI3 using first-principles calculations and molecular dynamics simulations and find that this process is energetically unfavorable. Our results provide a complete atomic-level picture of the mechanism of DMA-induced stabilization of the black perovskite phase of CsPbI3 and shed new light on this deceptively simple material.

A theoretical perspective of the ultrafast transient absorption dynamics of CsPbBr3.

Transient absorption spectra (TAS) of lead halide perovskites can provide important insights into the nature of the photoexcited state dynamics of this prototypical class of materials. Here, we perform ground and excited state molecular dynamics (MD) simulations within a restricted open shell Kohn-Sham (ROKS) approach in order to interpret the characteristic features of the TAS of CsPbBr3 . Our results reveal that properties such as the finite temperature band gap, the Stokes shift, and therefore, also the TAS are strongly size-dependent. Our TAS simulations show an early positive red-shifted feature on the fs scale that can be explained by geometric relaxation in the excited state. As excited-state processes can crucially affect the electronic properties of this class of photoactive materials, our observations are an important ingredient for further optimization of lead halide based optoelectronic devices.

Reversible Pressure-Dependent Mechanochromism of Dion-Jacobson and Ruddlesden-Popper Layered Hybrid Perovskites.

Layered Dion-Jacobson (DJ) and Ruddlesden-Popper (RP) hybrid perovskites are promising materials for optoelectronic applications due to their modular structure. To fully exploit their functionality, mechanical stimuli can be used to control their properties without changing the composition. However, the responsiveness of these systems to pressure compatible with practical applications (<1 GPa) remains unexploited. Hydrostatic pressure is used to investigate the structure-property relationships in representative iodide and bromide DJ and RP 2D perovskites based on 1,4-phenylenedimethylammonium (PDMA) and benzylammonium (BzA) spacers in the 0-0.35 GPa pressure range. Pressure-dependent X-ray scattering measurements reveal that lattices of these compositions monotonically shrink and density functional theory calculations provide insights into the structural changes within the organic spacer layer. These structural changes affect the optical properties; the most significant shift in the optical absorption is observed in (BzA)2 PbBr4 under 0.35 GPa pressure, which is attributed to an isostructural phase transition. Surprisingly, the RP and DJ perovskites behave similarly under pressure, despite the different binding modes of the spacer molecules. This study provides important insights into how the manipulation of the crystal structure affects the optoelectronic properties of such materials, whereas the reversibility of their response expands the perspectives for future applications.

A multiple time step algorithm for trajectory surface hopping simulations.

A multiple time step (MTS) algorithm for trajectory surface hopping molecular dynamics has been developed, implemented, and tested. The MTS scheme is an extension of the ab initio implementation for Born-Oppenheimer molecular dynamics presented in the work of Liberatore et al. [J. Chem. Theory Comput. 14, 2834 (2018)]. In particular, the MTS algorithm has been modified to enable the simulation of non-adiabatic processes with the trajectory surface hopping (TSH) method and Tully's fewest switches algorithm. The specificities of the implementation lie in the combination of Landau-Zener and Tully's transition probabilities during the inner MTS time steps. The new MTS-TSH method is applied successfully to the photorelaxation of protonated formaldimine, showing that the important characteristics of the process are recovered by the MTS algorithm. A computational speed-up between 1.5 and 3 has been obtained compared to standard TSH simulations, which is close to the ideal values that could be obtained with the computational settings considered.

Recent Advances in First-Principles Based Molecular Dynamics.

First-principles molecular dynamics (FPMD) and its quantum mechanical-molecular mechanical (QM/MM) extensions are powerful tools to follow the real-time dynamics of a broad variety of systems in their ground as well as electronically excited states. The continued advances in computational power have enabled simulations of QM regions of larger sizes for more extended time scales. In addition, development of the parallel algorithms has boosted the performance of QM/MM methods even on existing computer architectures. In the case of density functional-based FPMD, systems of several hundreds to thousands of atoms can now be customarily simulated for tens to hundreds of picoseconds. In spite of this progress, the time scale limitations remain severe, especially when high-rung exchange-correlation functionals or high-level wave function based quantum mechanical methods are used. To ameliorate this, a large number of enhanced sampling methods have been introduced but most of the approaches that have been developed to increase the efficiency of FPMD based simulations sacrifice the real-time dynamics in favor of enhancing sampling. Here, we present some recent advances in boosting the efficiency of FPMD based simulations while keeping the full dynamic information. These include a highly efficient recent implementation of FPMD-based QM/MM simulations that not only enables fully flexible combinations of different electronic structure methods and force fields via a highly efficient communication library, it also fully exploits parallelism for both quantum and classical descriptions. The second type of acceleration methods we discuss is a large family of specially devised multiple-time-step algorithms that make use of suitable breakups of the total nuclear forces into fast components that can be calculated via lower level methods and slowly varying correction forces evaluated with a high-level method at long time intervals. The computational gain of this scheme mostly depends on the cost difference between the two methods and advantageous combinations can yield large speedups without compromising the accuracy of the high-level method. And finally, the third class of FPMD acceleration methods presented here are machine learning models to accelerated FPMD and their powerful combinations with multiple-time-step techniques. The combination of all the approaches enables substantial speedups of FPMD simulations of several orders of magnitude while fully preserving the real-time dynamics and accuracy.