Showing papers by "Sergei Tretiak published in 2020"
TL;DR: This Review will describe recent theoretical advances including treatment of electronic decoherence in surface-hopping methods, the role of solvent effects, trivial unavoided crossings, analysis of data based on transition densities, and efficient computational implementations of these numerical methods.
Abstract: Optically active molecular materials, such as organic conjugated polymers and biological systems, are characterized by strong coupling between electronic and vibrational degrees of freedom. Typically, simulations must go beyond the Born-Oppenheimer approximation to account for non-adiabatic coupling between excited states. Indeed, non-adiabatic dynamics is commonly associated with exciton dynamics and photophysics involving charge and energy transfer, as well as exciton dissociation and charge recombination. Understanding the photoinduced dynamics in such materials is vital to providing an accurate description of exciton formation, evolution, and decay. This interdisciplinary field has matured significantly over the past decades. Formulation of new theoretical frameworks, development of more efficient and accurate computational algorithms, and evolution of high-performance computer hardware has extended these simulations to very large molecular systems with hundreds of atoms, including numerous studies of organic semiconductors and biomolecules. In this Review, we will describe recent theoretical advances including treatment of electronic decoherence in surface-hopping methods, the role of solvent effects, trivial unavoided crossings, analysis of data based on transition densities, and efficient computational implementations of these numerical methods. We also emphasize newly developed semiclassical approaches, based on the Gaussian approximation, which retain phase and width information to account for significant decoherence and interference effects while maintaining the high efficiency of surface-hopping approaches. The above developments have been employed to successfully describe photophysics in a variety of molecular materials.
221 citations
TL;DR: This work demonstrates a thin-film x-ray detector comprised with highly crystalline two-dimensional Ruddlesden-Popper phase layered perovskites fabricated in a fully depleted p-i-n architecture that shows high diode resistivity leading to a high x-rays detecting sensitivity up to 0.276 C Gyair−1 cm−3.
Abstract: Solid-state radiation detectors, using crystalline semiconductors to convert radiation photons to electrical charges, outperform other technologies with high detectivity and sensitivity. Here, we demonstrate a thin-film x-ray detector comprised with highly crystalline two-dimensional Ruddlesden-Popper phase layered perovskites fabricated in a fully depleted p-i-n architecture. It shows high diode resistivity of 1012 ohm·cm in reverse-bias regime leading to a high x-ray detecting sensitivity up to 0.276 C Gyair−1 cm−3. Such high signal is collected by the built-in potential underpinning operation of primary photocurrent device with robust operation. The detectors generate substantial x-ray photon–induced open-circuit voltages that offer an alternative detecting mechanism. Our findings suggest a new generation of x-ray detectors based on low-cost layered perovskite thin films for future x-ray imaging technologies.
133 citations
TL;DR: The ANI-1x and ANi-1ccx ML-based general-purpose potentials for organic molecules were developed through active learning; an automated data diversification process, and are provided to aid research and development of ML models for chemistry.
Abstract: Maximum diversification of data is a central theme in building generalized and accurate machine learning (ML) models. In chemistry, ML has been used to develop models for predicting molecular properties, for example quantum mechanics (QM) calculated potential energy surfaces and atomic charge models. The ANI-1x and ANI-1ccx ML-based general-purpose potentials for organic molecules were developed through active learning; an automated data diversification process. Here, we describe the ANI-1x and ANI-1ccx data sets. To demonstrate data diversity, we visualize it with a dimensionality reduction scheme, and contrast against existing data sets. The ANI-1x data set contains multiple QM properties from 5 M density functional theory calculations, while the ANI-1ccx data set contains 500 k data points obtained with an accurate CCSD(T)/CBS extrapolation. Approximately 14 million CPU core-hours were expended to generate this data. Multiple QM calculated properties for the chemical elements C, H, N, and O are provided: energies, atomic forces, multipole moments, atomic charges, etc. We provide this data to the community to aid research and development of ML models for chemistry. Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.12046440
117 citations
TL;DR: The current state of the field is discussed by summarizing the most extensively studied carrier transport mechanisms such as electron-phonon scattering limited dynamics, ferroelectric effects, Rashba-type band splitting, and polaronic transport.
Abstract: Metal halide perovskites (MHPs) have rapidly emerged as leading contenders in photovoltaic technology and other optoelectronic applications owing to their outstanding optoelectronic properties. After a decade of intense research, an in-depth understanding of the charge carrier transport in MHPs is still an active topic of debate. In this Perspective, we discuss the current state of the field by summarizing the most extensively studied carrier transport mechanisms, such as electron-phonon scattering limited dynamics, ferroelectric effects, Rashba-type band splitting, and polaronic transport. We further extensively discuss the emerging experimental and computational evidence for dominant polaronic carrier dynamics in MHPs. Focusing on both small and large polarons, we explore the fundamental aspects of their motion through the lattice, protecting the photogenerated charge carriers from the recombination process. Finally, we outline different physical and chemical approaches considered recently to study and exploit the polaron transport in MHPs.
98 citations
TL;DR: In this paper, the dominant non-radiative carrier recombination and dephasing processes in Ruddlesden-Popper (RP) and DJ monolayered lead halide perovskites were compared at room temperature.
Abstract: Two-dimensional (2D) halide perovskites are promising materials for environmentally stable next-generation optoelectronic device applications. Besides the widely investigated Ruddlesden–Popper (RP) phases, Dion–Jacobson (DJ) phases are attracting considerable attention due to their rapid emergence as efficient solar cell materials. However, there is very little atomistic understanding of the charge carrier dynamics under ambient conditions for these DJ-phases, limiting the possibilities to tune their optoelectronic performances through compositional engineering routes. Here, by combining nonadiabatic molecular dynamics with time-domain density functional theory methods at room temperature, we compare the dominant non-radiative carrier recombination and dephasing processes in RP and DJ monolayered lead halide perovskites. Our systematic study demonstrates that performance-limiting nonradiative carrier recombination processes greatly depends on the electron–phonon interactions induced by structural fluctuations and instantaneous charge localization in these materials. The stiffer interlayer packing due to the presence of single spacer dications, which separates the lead iodide slabs, reduces the thermal fluctuations in the DJ-phase to a greater extent than that in the RP-phase 2D-perovskites. Specific electronic coupling between the closely spaced lead iodide layers enhances the delocalization of band-edge charge densities in DJ-phase systems. Compared to the RP-phase, reduced inelastic electron–phonon scattering in DJ-phase perovskites significantly limits intrinsic non-radiative recombination processes. The consequent enhancement in the photogenerated charge carrier lifetime makes DJ-phase perovskites potentially suitable for various optoelectronic devices. The computational insights gained from this study allow us to outline a set of robust design principles for DJ-phase perovskites to strategically tune their optoelectronic properties.
61 citations
TL;DR: The primary intent behind the NEXMD was to simulate nonadiabatic molecular dynamics, but the code can also perform geometry optimizations, adiabatic excited state dynamics, and single-point calculations all in vacuum or in a simulated solvent.
Abstract: We present a versatile new code released for open community use, the nonadiabatic excited state molecular dynamics (NEXMD) package. This software aims to simulate nonadiabatic excited state molecular dynamics using several semiempirical Hamiltonian models. To model such dynamics of a molecular system, the NEXMD uses the fewest-switches surface hopping algorithm, where the probability of transition from one state to another depends on the strength of the derivative nonadiabatic coupling. In addition, there are a number of algorithmic improvements such as empirical decoherence corrections and tracking trivial crossings of electronic states. While the primary intent behind the NEXMD was to simulate nonadiabatic molecular dynamics, the code can also perform geometry optimizations, adiabatic excited state dynamics, and single-point calculations all in vacuum or in a simulated solvent. In this report, first, we lay out the basic theoretical framework underlying the code. Then we present the code's structure and workflow. To demonstrate the functionality of NEXMD in detail, we analyze the photoexcited dynamics of a polyphenylene ethynylene dendrimer (PPE, C30H18) in vacuum and in a continuum solvent. Furthermore, the PPE molecule example serves to highlight the utility of the getexcited.py helper script to form a streamlined workflow. This script, provided with the package, can both set up NEXMD calculations and analyze the results, including, but not limited to, collecting populations, generating an average optical spectrum, and restarting unfinished calculations.
46 citations
TL;DR: This work combines nonadiabatic molecular dynamics and time-domain density functional theory to investigate the fundamental mechanisms of carrier recombination processes in monolayer bromide perovskites with dissimilar organic spacer molecules and finds a strong correlation between temperature-induced structural fluctuations and nonradiative carrier recombinations rates.
Abstract: Two-dimensional (2D) halide perovskites have displayed unique emission properties, making them potential candidates for next-generation light-emitting devices. Here, we combine nonadiabatic molecular dynamics and time-domain density functional theory to investigate the fundamental mechanisms of carrier recombination processes. Considering monolayer bromide perovskites with dissimilar organic spacer molecules, n-butylammonium (BA) and phenylethylammonium (PEA) cations, we find a strong correlation between temperature-induced structural fluctuations and nonradiative carrier recombination rates in these materials. The more flexible geometry of (BA)2PbBr4 compared to that of (PEA)2PbBr4, results in faster electron-hole recombination and shorter carrier lifetime, diminishing the photoluminescence quantum yield for softer 2D perovskites. Reduced structural fluctuations in relatively rigid (PEA)2PbBr4 not only indicate of a longer carrier lifetime but also suggest a narrower emission line width, implying a higher purity of the emitted light. Our ab initio modeling of excited state properties in 2D perovskites conveys material designing strategies to fine-tune perovskite emissions for solid-state lighting applications.
45 citations
TL;DR: Methods by which the morphology of the defect in functionalized SWCNTs can be controlled to reduce emissive diversity and to tune the fluorescence wavelengths are outlined and chirality-dependent trends of emission energies with respect to individual defect morphologies are explored.
Abstract: ConspectusSingle-walled carbon nanotubes (SWCNTs) show promise as light sources for modern fiber optical communications due to their emission wavelengths tunable via chirality and diameter dependency. However, the emission quantum yields are relatively low owing to the existence of low-lying dark electronic states and fast excitonic diffusion leading to carrier quenching at defects. Covalent functionalization of SWCNTs addresses this problem by brightening their infrared emission. Namely, introduction of sp3-hybridized defects makes the lowest energy transitions optically active for some defect geometries and enables further control of their optical properties. Such functionalized SWCNTs are currently the only material exhibiting room-temperature single photon emission at telecom relevant infrared wavelengths. While this fluorescence is strong and has the right wavelength, functionalization introduces a variety of emission peaks resulting in spectrally broad inhomogeneous photoluminescence that prohibits the use of SWCNTs in practical applications. Consequently, there is a strong need to control the emission diversity in order to render these materials useful for applications. Recent experimental and computational work has attributed the emissive diversity to the presence of multiple localized defect geometries each resulting in distinct emission energy. This Account outlines methods by which the morphology of the defect in functionalized SWCNTs can be controlled to reduce emissive diversity and to tune the fluorescence wavelengths. The chirality-dependent trends of emission energies with respect to individual defect morphologies are explored. It is demonstrated that defect geometries originating from functionalization of SWCNT carbon atoms along bonds with strong π-orbital mismatch are favorable. Furthermore, the effect of controlling the defect itself through use of different chemical groups is also discussed. Such tunability is enabled due to the formation of specific defect geometries in close proximity to other existing defects. This takes advantage of the changes in π-orbital mismatch enforced by existing defects and the resulting changes in reactivities toward formation of specific defect morphologies. Furthermore, the trends in emissive energies are highly dependent on the value of mod(n-m,3) for an (n,m) tube chirality. These powerful concepts allow for a targeted formation of defects that emit at desired energies based on SWCNT single chirality enriched samples. Finally, the impact of functionalization with specific types of defects that enforce certain defect geometries due to steric constraints in bond lengths and angles to the SWCNT are discussed. We further relate to a similar effect that is present in systems where high density of surface defects is formed due to high reactant concentration. The outlined strategies suggested by simulations are instrumental in guiding experimental efforts toward the generation of functionalized SWCNTs with tunable emission energies.
40 citations
TL;DR: A highly automated approach to dataset construction is presented and the final ANI-Al potential makes very accurate predictions of radial distribution function in melt, liquid-solid coexistence curve, and crystal properties such as defect energies and barriers.
Abstract: Accuracy of molecular dynamics simulations depends crucially on the interatomic potential used to generate forces. The gold standard would be first-principles quantum mechanics (QM) calculations, but these become prohibitively expensive at large simulation scales. Machine learning (ML) based potentials aim for faithful emulation of QM at drastically reduced computational cost. The accuracy and robustness of an ML potential is primarily limited by the quality and diversity of the training dataset. Using the principles of active learning (AL), we present a highly automated approach to dataset construction. The strategy is to use the ML potential under development to sample new atomic configurations and, whenever a configuration is reached for which the ML uncertainty is sufficiently large, collect new QM data. Here, we seek to push the limits of automation, removing as much expert knowledge from the AL process as possible. All sampling is performed using MD simulations starting from an initially disordered configuration, and undergoing non-equilibrium dynamics as driven by time-varying applied temperatures. We demonstrate this approach by building an ML potential for aluminum (ANI-Al). After many AL iterations, ANI-Al teaches itself to predict properties like the radial distribution function in melt, liquid-solid coexistence curve, and crystal properties such as defect energies and barriers. To demonstrate transferability, we perform a 1.3M atom shock simulation, and show that ANI-Al predictions agree very well with DFT calculations on local atomic environments sampled from the nonequilibrium dynamics. Interestingly, the configurations appearing in shock appear to have been well sampled in the AL training dataset, in a way that we illustrate visually.
40 citations
TL;DR: In this article, the effect of chlorine incorporation on the optical and electronic prop- erties, structural stability, ion-migration as well as the γ-ray radiation detection ability of MAPbBr 3-x Cl x was investigated.
Abstract: Controlled anion-mixing in halide perovskites has been shown to be an effective route to precisely tuning optoelectronic properties, in order to achieve efficient photo- voltaic, light emission and radiation detection devices. However, an atomistic under- standing behind the precise mechanism impacting the performances of mixed halide perovskite devices, particularly as a radiation detector, is still missing. Combining high-level computational methods and multiple experiments, here we systematically investigate the effect of chlorine (Cl) incorporation on the optical and electronic prop- erties, structural stability, ion-migration as well as the γ-ray radiation detection ability of MAPbBr 3-x Cl x . We observe that precise halide mixing suppresses bromide ion mi- gration and consequently reduces the dark current by close to a factor of two, which significantly improves the resistance of the mixed-anion devices. Furthermore, reduced carrier effective masses and mostly unchanged exciton binding energies indicate en- hanced charge carrier transport for these perovskite alloys. At the atomistic level, modifications to ion migration and charge carrier transport properties improve elec- tronic properties and predominantly contribute to the better response and resolution in high-energy γ-ray detection with MAPbBr 3-x Cl x , as compared to MAPbBr 3 . This study provides a systematic approach to enhance the high-energy radiation detection ability of MAPbBr 3-x Cl x -based devices by understanding the atomistic properties un- derpinning performance.
39 citations
TL;DR: High‐performance layered perovskites LEDs with benzyl ring as spacer where radiative recombination lifetime is longer, compared with much shorter alkyl chain spacer yields are reported.
Abstract: Light-emitting diodes (LEDs) made with quasi-2D/3D and layered perovskites have undergone an unprecedented surge as their external quantum efficiency (EQE) is rapidly approaching other lighting technologies. Manipulating the charge recombination pathway in semiconductors is highly desirable for improving the device performance. This study reports high-performance layered perovskites LEDs with benzyl ring as spacer where radiative recombination lifetime is longer, compared with much shorter alkyl chain spacer yields. Based on detailed optical and X-ray absorption spectroscopy measurements, direct signature of charges localization is observed near the band edge in exchange with the shallow traps in benzyl organics containing layered perovskites. As a result, it boosts the photoluminescence intensity by 7.4 times compared to that made with the alkyl organics. As a demonstration, a bright LED made with the benzyl organics with current efficiency of 23.46 ± 1.52 cd A-1 is shown when the device emits at a high brightness of 6.6 ± 0.93 × 104 cd m-2. The average EQE is 9.2% ± 1.43%, two orders of magnitude higher than the device made with alkyl organics. The study suggests that the choices of organic spacers provide a path toward the manipulation of charge recombination, essential for efficient optoelectronic device fabrications.
TL;DR: High-throughput approaches aiming to theoretically design 2D Si-C crystals in terms of morphology, physicochemical properties and potential applications based on the insights provided by simulations are overviewed.
Abstract: Compared to graphene with semimetallic features, two-dimensional (2D) silicon carbide (Si–C) materials constitute another highly promising family for opto-electronic applications owing to their intrinsic electronic gaps. Recent theoretical studies of 2D Si–C materials thoroughly investigated their structure and properties. Herein, we overview these high-throughput approaches aiming to theoretically design 2D Si–C crystals. Graphene-like siligraphene and non-siligraphene are described in terms of morphology, physicochemical properties and potential applications based on the insights provided by simulations. In addition, the current progress of experimental exploration of 2D Si–C materials and underlying challenges are assessed as well.
TL;DR: PYSEQM as discussed by the authors is an open-source high-performance implementation of Born Oppenheimer molecular dynamics based on semi-empirical quantum mechanics models using PyTorch.
Abstract: A new open-source high-performance implementation of Born Oppenheimer molecular dynamics based on semiempirical quantum mechanics models using PyTorch called PYSEQM is presented PYSEQM was designed to provide researchers in computational chemistry with an open-source, efficient, scalable, and stable quantum-based molecular dynamics engine In particular, PYSEQM enables computation on modern graphics processing unit hardware and, through the use of automatic differentiation, supplies interfaces for model parameterization with machine learning techniques to perform multiobjective training and prediction The implemented semiempirical quantum mechanical methods (MNDO, AM1, and PM3) are described Additional algorithms include a recursive Fermi-operator expansion scheme (SP2) and extended Lagrangian Born Oppenheimer molecular dynamics allowing for rapid simulations Finally, benchmark testing on the nanostar dendrimer and a series of polyethylene molecules provides a baseline of code efficiency, time cost, and scaling and stability of energy conservation, verifying that PYSEQM provides fast and accurate computations
TL;DR: This work proposes a novel approach to reduce ansatz circuit depth in Variational Quantum Eigensolver by adding an additional optimization loop to VQE that permutes qubits in order to solve for the qubit Hamiltonian that minimizes long-range correlations in the ground state.
Abstract: The Variational Quantum Eigensolver (VQE) is a method of choice to solve the electronic structure problem for molecules on near-term gate-based quantum computers. However, the circuit depth is expected to grow significantly with problem size. Increased depth can both degrade the accuracy of the results and reduce trainability. In this work, we propose a novel approach to reduce ansatz circuit depth. Our approach, called PermVQE, adds an additional optimization loop to VQE that permutes qubits in order to solve for the qubit Hamiltonian that minimizes long-range correlations in the ground state. The choice of permutations is based on mutual information, which is a measure of interaction between electrons in spin-orbitals. Encoding strongly interacting spin-orbitals into proximal qubits on a quantum chip naturally reduces the circuit depth needed to prepare the ground state. For representative molecular systems, LiH, H$_2$, (H$_2$)$_2$, H$_4$, and H$_3^+$, we demonstrate for linear qubit connectivity that placing entangled qubits in close proximity leads to shallower depth circuits required to reach a given eigenvalue-eigenvector accuracy. This approach can be extended to any qubit connectivity and can significantly reduce the depth required to reach a desired accuracy in VQE. Moreover, our approach can be applied to other variational quantum algorithms beyond VQE.
TL;DR: Low-cost, eco-friendly, and hydrophilic cellulose nanocrystals (CNCs) are proposed as a multifunctional polysulfide stopper for Li-S battery with high performance, and results sufficiently demonstrate that CNCs have significant application potential in Li- S battery technologies.
Abstract: Because of the severe shuttle effect of polysulfides, achieving durable Li-S batteries is still a great challenge, especially under practical operation conditions including the high sulfur content, high loading, and high operation temperature. Herein, for the first time, low-cost, eco-friendly, and hydrophilic cellulose nanocrystals (CNCs) are proposed as a multifunctional polysulfide stopper for Li-S batteries with high performance. CNCs display an intrinsically high aspect ratio and a large surface area and contain a large amount of hydroxyl groups offering a facile platform for chemical interactions. Density functional theory calculations suggest that the electron-rich functional groups on CNCs deliver robust binding energies with polysulfides. In this work, CNCs not only firmly confine sulfur and polysulfides in the cathode as a robust binder, but also further hinder polysulfide shuttling to the Li anode as a polysulfide stopper on a separator. Consequently, the as-prepared Li-S batteries demonstrate outstanding cycling performance even under the conditions of high sulfur content of 90 wt % (63 wt % in the cathode), high loading of 8.5 mg cm-2, and high temperature of 60 °C. These results sufficiently demonstrate that CNCs have significant application potential in Li-S battery technologies.
TL;DR: The study indicates that the interface between methylammonium lead tri-iodide (MAPbI3) single crystals and commonly used high and low work-function metals to achieve photon counting capabilities in a solid-state detector plays a crucial role in solid state detectors operating in photon counting mode.
Abstract: Halide perovskites are promising optoelectronic semiconductors. For applications in solid-state detectors that operate in low photon flux counting mode, blocking interfaces are essential to minimize the dark current noise. Here, we investigate the interface between methylammonium lead tri-iodide (MAPbI3) single crystals and commonly used high and low work function metals to achieve photon counting capabilities in a solid-state detector. Using scanning photocurrent microscopy, we observe a large Schottky barrier at the MAPbI3/Pb interface, which efficiently blocks dark current. Moreover, the shape of the photocurrent profile indicates that the MAPbI3 single-crystal surface has a deep fermi level close to that of Au. Rationalized by first-principle calculations, we attribute this observation to the defects due to excess iodine on the surface underpinning emergence of deep band-edge states. The photocurrent decay profile yields a charge carrier diffusion length of 10-25 μm. Using this knowledge, we demonstrate a single-crystal MAPbI3 detector that can count single γ-ray photons by producing sharp electrical pulses with a fast rise time of <2 μs. Our study indicates that the interface plays a crucial role in solid-state detectors operating in photon counting mode.
TL;DR: The general Quantum Annealer Eigensolver (QAE) algorithm is implemented to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer and is hardware-dominant relying on only one classically optimized parameter.
Abstract: Quantum chemistry is regarded to be one of the first disciplines that will be revolutionized by quantum computing. Although universal quantum computers of practical scale may be years away, various approaches are currently being pursued to solve quantum chemistry problems on near-term gate-based quantum computers and quantum annealers by developing the appropriate algorithm and software base. This work implements the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer. The approach is based on the matrix formulation, efficiently uses qubit resources based on a power-of-two encoding scheme and is hardware-dominant relying on only one classically optimized parameter. We demonstrate the use of D-Wave hardware for obtaining ground and electronically excited states across a variety of small molecular systems. This approach can be adapted for use by a vast majority of electronic structure methods currently implemented in conventional quantum-chemical packages. The results of this work will encourage further development of software such as qbsolv which has promising applications in emerging quantum information processing hardware and is able to address large and complex optimization problems intractable for classical computers.
TL;DR: This work computationally examines a prototype halide perovskite architecture, NiO/MAPbI3 (MA = CH3NH3+), which has shown excellent photovoltaic performance and in particular a large open-circuit voltage and shows how Li doping greatly improves the performances of the device and further propose alternative dopants.
Abstract: Nickel oxide (NiO) is a commonly used contact material for a variety of thin-film optoelectronic technologies based on organic or hybrid materials. In such setups, interfaces play a crucial role as...
TL;DR: This study provides a baseline for future implementations of higher level frameworks for simulating non-adiabatic molecular dynamics in NWChem and implements an implementation of the fewest-switches surface hopping algorithm in the NWChem computational chemistry program.
Abstract: Computational simulation of nonadiabatic molecular dynamics is an indispensable tool for understanding complex photoinduced processes such as internal conversion, energy transfer, charge separation, and spatial localization of excitons, to name a few. We report an implementation of the fewest-switches surface-hopping algorithm in the NWChem computational chemistry program. The surface-hopping method is combined with linear-response time-dependent density functional theory calculations of adiabatic excited-state potential energy surfaces. To treat quantum transitions between arbitrary electronic Born-Oppenheimer states, we have implemented both numerical and analytical differentiation schemes for derivative nonadiabatic couplings. A numerical approach for the time-derivative nonadiabatic couplings together with an analytical method for calculating nonadiabatic coupling vectors is an efficient combination for surface-hopping approaches. Additionally, electronic decoherence schemes and a state reassigned unavoided crossings algorithm are implemented to improve the accuracy of the simulated dynamics and to handle trivial unavoided crossings. We apply our code to study the ultrafast decay of photoexcited benzene, including a detailed analysis of the potential energy surface, population decay timescales, and vibrational coordinates coupled to the excitation dynamics. We also study the photoinduced dynamics in trans-distyrylbenzene. This study provides a baseline for future implementations of higher-level frameworks for simulating nonadiabatic molecular dynamics in NWChem.
TL;DR: The presented results suggest that the structural and thermodynamic properties of fluids may be determined more accurately through machine learning than through human-guided functional forms.
Abstract: Predicting the functional properties of many molecular systems relies on understanding how atomistic interactions give rise to macroscale observables. However, current attempts to develop predictive models for the structural and thermodynamic properties of condensed-phase systems often rely on extensive parameter fitting to empirically selected functional forms whose effectiveness is limited to a narrow range of physical conditions. In this article, we illustrate how these traditional fitting paradigms can be superseded using machine learning. Specifically, we use the results of molecular dynamics simulations to train machine learning protocols that are able to produce the radial distribution function, pressure, and internal energy of a Lennard-Jones fluid with increased accuracy in comparison to previous theoretical methods. The radial distribution function is determined using a variant of the segmented linear regression with the multivariate function decomposition approach developed by Craven et al. [J. Phys. Chem. Lett. 11, 4372 (2020)]. The pressure and internal energy are determined using expressions containing the learned radial distribution function and also a kernel ridge regression process that is trained directly on thermodynamic properties measured in simulation. The presented results suggest that the structural and thermodynamic properties of fluids may be determined more accurately through machine learning than through human-guided functional forms.
TL;DR: In this article, a new formalism is developed to analytically and accurately model emission through and over barriers associated with depletion layers, nanotip barriers, and metal-insulator-metal (MIM) structures.
Abstract: Tunneling barriers are an essential component of electron sources, sensors, detectors, and vacuum nanoelectronics and a pivotal factor in their performance, but the barriers themselves routinely depart from the analytic models used to model their behavior A new formalism is developed to analytically and accurately model emission through and over barriers associated with depletion layers, nanotip barriers, and metal–insulator–metal (MIM) structures The transmission probability for depletion layers and MIM and metal–oxide–semiconductor (MOS) barriers is accurately modeled as the electron energy exceeds the barrier height using approaches designed for rapid implementation demanded by simulation codes and extensible to general barriers The models supersede conventional thermal and field models in depletion and MIM/MOS barrier studies Thermal-field methods are used to treat the transmission probability and shape factor methods to treat the tunneling factor Analytic formulas for current density are obtained The methods ease device simulation and characterization of current–voltage relations for emerging technologically interesting barriers with better accuracy
TL;DR: In this paper, the performance of perovskite-based γ-ray detectors is investigated under low electric field detector operation, with average rise times of 65 μs, which decreases to 20 μs when a higher electrical field of 500 V cm−1 is applied.
Abstract: DOI: 10.1002/adom.202000233 photo voltaics, perovskite solar cells have already exceeded 23% in power conversion efficiency in a short development period.[1–4] OMHPs have also become popular in many other optoelectronic applications, such as light-emitting diodes,[5,6] photodetectors,[7,8] and lasing applications.[9] Properties such as tunable band gaps,[10,11] low trap state densities,[12] and long carrier diffusion lengths make OMHPs a desirable material for a wide range of optoelectronic applications, as well as being a focus for other semiconducting device applications.[13,14] These fascinating optoelectronic properties have recently sparked a new interest for applications of OMHPs for high-energy radiation detectors, which are considered as a critical technology in many fields, including nuclear safeguards, nuclear forensics, and astrophysics. Notably, current solid-state detector technologies using classical semiconductors have many challenges that must be overcome for wide spread development. For example, Cadmium Zinc Telluride (CZT) is a commercial γ-ray detection semiconductor achieving reasonable resolution (≈2% at 662 keV) at room temperature. However, the complicated and costly high-quality crystal growth for this semiconductor fabrication prohibits its broad adaptation. Another example of a more cost-effective semiconductor is high purity Germanium, (HPGe) which achieves an impressive resolution, (≈0.2% at 662 keV) albeit under operation at liquid nitrogen temperatures.[15] Thus, achieving cost efficient, robust high resolution detection at ambient conditions has been a long-time aim for semiconductor γ-ray detectors. In this arena, lead-halide based perovskites have been proposed as a new generation semiconductors in γ -spectroscopy for its low-cost solution process and simple crystal growth for room temperature detectors.[16–18] The incorporation of high-Z elements (i.e., Pb) underscores the opportunity for enhanced photoelectric interaction probability. Large band gaps and high resistivities are also essential for highly sensitive operation in the resistive mode.[19] Moreover, the long carrier lifetime and decent ambipolar mobility give great potential for single photon counting and pulse mode radiation sensing.[15] Previous reports have shown promising proof-of-principle results for the application of perovskites as ionizing radiation In recent years, hybrid perovskite single crystalline solid-state detectors have shown promise in γ-ray spectroscopy. Here, the γ-ray photon induced electrical pulses are investigated, which are produced by perovskite solid-state detectors made with the commonly used methylammonium lead tribromide crystals with chlorine incorporation. Under low electric field detector operation, slow pulses generated by γ-rays with average rise times of 65 μs are observed, which decreases to 20 μs when a higher electrical field of 500 V cm−1 is applied. However, the baseline becomes noisy quickly, which prevents collection of clean pulses for spectra construction. Further, by systematically measuring the temperature dependence and current–voltage characteristics, such instability is attributed to the local ion migration under electrical field creating a fluctuating dark noise, which presents a major challenge in perovskite γ-ray detector technologies. It is demonstrated that cycling the bias between positive and negative polarity can stabilize the detector, allowing for longer periods of pulse accumulation for generating energy resolved spectra with resolutions of ≈35% at 59.6 keV and ≈25% at 662 keV at room temperature. The study indicates that the main limiting factors of perovskite-based γ-ray detectors are slow rise times and bias instability. These challenges must be properly addressed to achieve reproducible, high-resolution γ-ray detection.
TL;DR: In this article, the authors investigated the operational principles of perovskite single crystal detectors that can efficiently count gamma-ray photon events with electrical pulses, and they found the main dark current originates from the thermally activated electron injection from the impurities, and using high work function contacts can block out the dark noise thus allows for efficient pulse collection at higher electrical fields ∼500 V/cm.
TL;DR: In this article, organic color-center quantum defects in semiconducting carbon nanotube hosts are rapidly emerging as promising candidates for solid-state quantum information technologies, but it is unclear how to exploit them.
Abstract: Organic color-center quantum defects in semiconducting carbon nanotube hosts are rapidly emerging as promising candidates for solid-state quantum information technologies. However, it is unclear wh...
TL;DR: Non-adiabatic excited state molecular dynamics simulations have been performed on a rigid synthetic heterodimer that has been proposed as a simplified model for investigating the role and mechanism of coherent energy transfer in multichromophoric systems.
Abstract: Energy transfer in multichromophoric molecules can be affected by coherences that are induced by the electronic and vibrational couplings between chromophore units. Coherent electron-vibrational dy...
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TL;DR: The existence of the single-layer (SL) dititanium oxide Ti2O (labeled as MOene) that constructs a novel family of MXene based on transition-metal oxides strongly contrasts the conventional ones consisting of transition- metal carbides and/or nitrides is reported.
Abstract: Using the first-principles calculations, we report the existence of the single-layer (SL) di-titanium oxide Ti$_2$O (labeled as MOene) that constructs a novel family of MXene based on transition metal oxides. This MOene material strongly contrasts the conventional ones consisting of transition metal carbides and/or nitrides. SL Ti$_2$O has high thermal and dynamical stabilities due to the strong Ti$-$O ionic bonding interactions. Moreover, this material is an intrinsic electride and exhibits extremely low diffusion barriers of $\sim$12.0 and 6.3 meV for Li- and Na diffusion, respectively. When applied as anode materials in lithium-ion batteries and sodium-ion batteries, it possesses a high energy storage capacity (960.23 mAhg$^{-1}$), surpassing the traditional MXenes-based anodes. The superb electrochemical performance stems from the existed anionic electron on Ti$_2$O surface. Astonishingly, SL Ti$_{2}$O is also determined to be a superconductor with a superconducting transition temperature (\textit{T$_{c}$}) of $\sim$9.8 K, which originates from the soft-mode of the first acoustic phonon branch and enhanced electron-phonon coupling in the low-frequency region. Our finding broadens the family of MXenes and would facilitate more experimental efforts toward future nanodevices.
TL;DR: A covalently linked donor-acceptor molecular dyad system is simulated by using nonadiabatic excited state molecular dynamics simulations to systematically identify the subset of vibrational normal modes that actively participate on the donor → acceptor (S2 → S1) electronic relaxation.
Abstract: Fil: Alfonso Hernandez, Laura. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Patagonia Norte; Argentina. Comision Nacional de Energia Atomica. Centro Atomico Bariloche; Argentina
Abstract: Simulation of electronic dynamics in realistically large molecular systems is a demanding task that has not yet achieved the same level of quantitative prediction already realized for its static counterpart. This is particularly true for processes occurring beyond the Born–Oppenheimer regime. Non-adiabatic molecular dynamics (NAMD) simulations suffer from two convoluted sources of error: numerical algorithms for dynamics and electronic structure calculations. While the former has gained increasing attention, particularly addressing the validity of ad hoc methodologies, the effect of the latter remains relatively unexplored. Indeed, the required accuracy for electronic structure calculations to reach quantitative agreement with experiment in dynamics may be even more strict than that required for static simulations. Here, we address this issue by modeling the electronic energy transfer in a donor–acceptor–donor (D–A–D) molecular light harvesting system using fewest switches surface hopping NAMD simulations. In the studied system, time-resolved experimental measurements deliver complete information on spectra and energy transfer rates. Subsequent modeling shows that the calculated electronic transition energies are “sufficiently good” to reproduce experimental spectra but produce over an order of magnitude error in simulated dynamical rates. We further perform simulations using artificially shifted energy gaps to investigate the complex relationship between transition energies and modeled dynamics to understand factors affecting non-radiative relaxation and energy transfer rates.
TL;DR: In this paper, the authors implemented the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer.
Abstract: Quantum chemistry is regarded to be one of the first disciplines that will be revolutionized by quantum computing. Although universal quantum computers of practical scale may be years away, various approaches are currently being pursued to solve quantum chemistry problems on near-term gate-based quantum computers and quantum annealers by developing the appropriate algorithm and software base. This work implements the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer. The approach is based on the matrix formulation, efficiently uses qubit resources based on a power-of-two encoding scheme and is hardware-dominant relying on only one classically optimized parameter. We demonstrate the use of D-Wave hardware for obtaining ground and excited electronic states across a variety of small molecular systems. The approach can be adapted for use by a vast majority of electronic structure methods currently implemented in conventional quantum-chemical packages. The results of this work will encourage further development of software such as qbsolv which has promising applications in emerging quantum information processing hardware and has expectation to address large and complex optimization problems intractable for classical computers.
TL;DR: It is found that the open-shell method lowers the reaction barrier at the bond-breaking limits resulting in larger calculated photochemical quantum yields compared to the respective closed-shell results.
Abstract: Nonadiabatic Molecular Dynamics (NAMD) of excited states has been widely used in the simulation of photoinduced phenomena. However, the inability to treat bond breaking and forming processes with single-reference electronic structure methods limits their application in photochemistry for extended molecular systems. In this work, the extension of excited-state NAMD for open-shell systems is developed and implemented in the NEXMD software. We present the spin-unrestricted CIS and TD-SCF formalism for the ground and excited states, analytical derivatives, and nonadiabatic derivative couplings for the respective potential energy surfaces. This methodology is employed to study the photochemical reaction of three model molecules. The results demonstrate the advantage of the open-shell approach in modeling photochemical reactions, especially involving bond breaking processes. We find that the open-shell method lowers the reaction barrier at the bond-breaking limits resulting in larger calculated photochemical quantum yields compared to the respective closed-shell results. We also address problems related to spin contamination in the open-shell method, especially when molecular geometries are far from equilibrium.