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Sodium-ion batteries are considered as potential alternatives to conventional lithium-ion batteries. To realize their large-scale practical applications, it is essential to identify suitable anode candidates exhibiting promising electrochemical properties such as high specific capacity, low diffusion energy barrier, and excellent cyclic stability. In this work, using density functional theory (DFT) calculations and ab initio molecular dynamics simulations, we examine α-graphyne - a carbon-based 2D material - as a potential anode candidate. Our results show that AGY exhibits an ultra-low diffusion barrier of 0.23 eV along both the horizontal and vertical directions and a low average anodic voltage of 0.36 V. Our AIMD studies at 300 K show excellent thermodynamical stability with the loading of four sodium atoms, resulting in a theoretical specific capacity (TSC) of 279 mA h g -1 . Doping studies show that varying the nature of acetylenic links of AGY with electron-rich (nitrogen) or electron-deficient (boron) elements, the adsorption strength and diffusion barriers for Na atoms on AGY can be tuned. Furthermore, treating AGY as a case study, we find that conventional DFT studies are expected to overestimate the TSC by a huge margin. Specific to AGY, this overestimation can be up to ∼300%. We identify that ignoring the probable formation of temperature-driven metal clusters is the main reason behind such overestimations. Furthermore, we develop a scheme to calculate TSC with higher accuracy. The scheme, which can be easily generalized to the universal class of electrodes, is evolved by concurrently employing AIMD simulations, DFT calculations and cluster analysis.

The cooperative mechanism is of paramount importance in the synthesis of supramolecular polymers with desired characteristics, including molecular mass, polydispersity, and morphology. It is primarily driven by the presence of intermolecular interactions, which encompass strong hydrogen bonding, metal-ligand interactions, and dipole-dipole interactions. In this study, we utilize density functional theory and energy decomposition analysis to investigate the cooperative behavior of perylene diimide (PDI) oligomers with alkyl chains at their imide positions, which lack the previously mentioned interactions. Our systematic examination reveals that dispersion interactions originating from the alkyl side-chain substituents play an important role in promoting cooperativity within these PDIs. This influence becomes even more pronounced for alkyl chain lengths beyond hexyl groups. The energy decomposition analysis reveals that the delicate balance between dispersion energy and Pauli repulsion energy is the key driver of cooperative behavior in PDIs. Additionally, we have developed a mathematical model capable of predicting the saturated binding energies for PDI oligomers of varying sizes and alkyl chain lengths. Overall, our findings emphasize the previously undervalued significance of dispersion forces in cooperative supramolecular polymerization, enhancing our overall understanding of the cooperative mechanism., (© 2024 Wiley-VCH GmbH.)

We present a catalyst-free route for the reduction of carbon dioxide integrated with the formation of a carbon-carbon bond at the air/water interface of negatively charged aqueous microdroplets, at ambient temperature. The reactions proceed through carbanion generation at the α-carbon of a ketone followed by nucleophilic addition to CO 2 . Online mass spectrometry reveals that the product is an α-ketoacid. Several factors, such as the concentration of the reagents, pressure of CO 2 gas, and distance traveled by the droplets, control the kinetics of the reaction. Theoretical calculations suggest that water in the microdroplets facilitates this unusual chemistry. Furthermore, such a microdroplet strategy has been extended to seven different ketones. This work demonstrates a green pathway for the reduction of CO 2 to useful carboxylated organic products., (© 2024 Wiley-VCH GmbH.)

Understanding the bond dissociation energies (BDEs) of per- and polyfluoroalkyl substances (PFAS) helps in devising their efficient degradation pathways. However, there is only limited experimental data on the PFAS BDEs, and there are uncertainties associated with the BDEs computed using density functional theory. Although quantum chemical methods like the G4 composite method can provide highly accurate BDEs (< 1 kcal mol -1 ), they are limited to small system sizes. To address DFT's accuracy limitations and G4's system size constraints, we examined the connectivity-based hierarchy (CBH) scheme and found that it can provide BDEs that are reasonably close to the G4 accuracy while retaining the computational efficiency of DFT. To further improve the accuracy, we modified the CBH scheme and demonstrated that BDEs calculated using it have a mean-absolute deviation of 0.7 kcal mol -1 from G4 BDEs. To validate the reliability of this new scheme, we computed the ground state free energies of seven PFAS compounds and BDEs for 44 C-C and C-F bonds at the G4 level of theory. Our results suggest that the modified CBH scheme can accurately compute the BDEs of both small and large PFAS at near G4 level accuracy, offering promise for more effective PFAS degradation strategies., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The variational quantum eigensolver (VQE) is a widely employed method to solve electronic structure problems in the current noisy intermediate-scale quantum (NISQ) devices. However, due to inherent noise in the NISQ devices, VQE results on NISQ devices often deviate significantly from the results obtained on noiseless statevector simulators or traditional classical computers. The iterative nature of VQE further amplifies the errors in each loop. Recent works have explored ways to integrate deep neural networks (DNN) with VQE to mitigate iterative errors, albeit primarily limited to the noiseless statevector simulators. In this work, we trained DNN models across various quantum circuits and examined the potential of two DNN-VQE approaches, DNN1 and DNNF, for predicting the ground state energies of small molecules in the presence of device noise. We carefully examined the accuracy of the DNN1, DNNF, and VQE methods on both noisy simulators and real quantum devices by considering different ansatzes of varying qubit counts and circuit depths. Our results illustrate the advantages and limitations of both VQE and DNN-VQE approaches. Notably, both DNN1 and DNNF methods consistently outperform the standard VQE method in providing more accurate ground state energies in noisy environments. However, despite being more accurate than VQE, the energies predicted using these methods on real quantum hardware remain meaningful only at reasonable circuit depths (depth = 15, gates = 21). At higher depths (depth = 83, gates = 112), they deviate significantly from the exact results. Additionally, we find that DNNF does not offer any notable advantage over VQE in terms of speed. Consequently, our study recommends DNN1 as the preferred method for obtaining quick and accurate ground state energies of molecules on current quantum hardware, particularly for quantum circuits with lower depth and fewer qubits., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)

There is continuous demand for energy storage devices with high energy densities in consumer electronics, electric vehicles, and the grid energy market. Although commercial lithium-ion batteries (LIBs) satisfy the current needs, the limited availability of their raw materials and the moderate specific charge capacities (SCCs) of LIBS have motivated scientists to search for alternate anode materials for LIBs and create technologies beyond LIBs. In this work, we studied the potential of six cobalt anti-MXenes (CoAs, CoB, CoP, CoS, CoSe, and CoSi), a class of newly discovered 2D materials, as anode materials for lithium, sodium, and potassium ion batteries (LIBs, NIBs, and KIBs). We found that these materials are good electrical conductors and have high adsorption stability for alkali metal ions, which helps to prevent the formation of dendrites and increase the cycle life of the battery. They also show moderate to low migration energy barriers (MEBs), indicating the potential for faster charge-discharge kinetics. We also explain the slightly counter-intuitive result of observing low MEBs along with high adsorption stability. Furthermore, Co-anti-MXenes can adsorb multiple alkali atoms per formula unit, resulting in high specific charge capacities and low average anodic voltages. For example, as anode materials for lithium-ion batteries, CoP and CoSi have SCC values of 1075.4 mA h g -1 and 934 mA h g -1 , and anodic voltages as low as 0.28 V and 0.43 V, respectively. Moreover, even the maximally metalated Co-anti-MXenes did not show agglomeration tendency at room temperature. Furthermore, the volume expansion of these materials is minimum for both Li and Na adsorption. As a whole, we find that Co-anti-MXenes are promising as anode materials for alkali metal ion batteries.

Restricted migration of reactive species limits chemical transformations within interstellar and cometary ices. We report the migration of CO 2 from clathrate hydrate (CH) cages to amorphous solid water (ASW) in the presence of tetrahydrofuran (THF) under ultrahigh vacuum (UHV) and cryogenic conditions. Thermal annealing of sequentially deposited CO 2 and H 2 O ice, CO 2 @H 2 O, to 90 K resulted in the partitioning of CO 2 in 5 12 and 5 12 6 2 CH cages (CO 2 @5 12 , CO 2 @5 12 6 2 ). However, upon preparing a composite ice film composed of CO 2 @5 12 , CO 2 @5 12 6 2 and THF distributed in the water matrix at 90 K, and annealing the mixture for 6 h at 130 K produced mixed CO 2 -THF CH, where THF occupied the 5 12 6 4 cages (THF@5 12 6 4 ) exclusively while CO 2 in 5 12 6 2 cages (CO 2 @5 12 6 2 ) got transferred to the ASW matrix and CO 2 in the 5 12 cages (CO 2 @5 12 ) remained as is. This cage-matrix exchange may create a more conducive environment for chemical transformations in interstellar environments.

Cooperative supramolecular polymerization is important for the synthesis of functional supramolecular homo and block-copolymers of π-systems. Current strategies indicate the need of strong hydrogen bonding (H-bonding) and/or dipolar interactions in the π-systems to achieve cooperativity. In sharp contrast, here we report the cooperative supramolecular polymerization in alkyl chain substituted perylene diimides (alkyl PDIs) driven by dispersive interactions with molecular level understanding. Moreover, alkyl PDIs follow cooperative mechanism with cooperativity similar to the strong H-bonded π-systems (σ ∼10 -5 ) despite the lack of strong H-bonding and dipolar interactions. Computer simulations show that this surprising phenomenon in alkyl PDIs is driven by the efficient dispersive interactions among the alkyl chains and π-cores due to their zigzag arrangement in the supramolecular polymer. Importantly, alkyl PDIs display cooperative supramolecular polymerization in both polar and non-polar solvents which is difficult for H-bonded/dipolar π-systems thus highlighting the advantages of dispersive interactions., (© 2022 Wiley-VCH GmbH.)

Per- and polyfluoroalkyl substances (PFASs) are synthetic contaminants found in drinking groundwater sources and a wide variety of consumer products. Because of their adverse environmental and human health effects, remediation of these persistent compounds has attracted significant recent attention. To gain mechanistic insight into their remediation, we present the first ab initio study of PFAS degradation via hydrated electrons─a configuration that has not been correctly considered in previous computational studies up to this point. To capture these complex dynamical effects, we harness ab initio molecular dynamics (AIMD) simulations to probe the reactivities of perfluorooctanoic (PFOA) and perfluorooctane sulfonic acid (PFOS) with hydrated electrons in explicit water. We complement our AIMD calculations with advanced metadynamics sampling techniques to compute free energy profiles and detailed statistical analyses of PFOA/PFOS dynamics. Although our calculations show that the activation barrier for C-F bond dissociation in PFOS is three times larger than that in PFOA, all the computed free energy barriers are still relatively low, resulting in a diffusion-limited process. We discuss our results in the context of recent studies on PFAS degradation with hydrated electrons to give insight into the most efficient remediation strategies for these contaminants. Most importantly, we show that the degradation of PFASs with hydrated electrons is markedly different from that with excess electrons/charges, a common (but largely incomplete) approach used in several earlier computational studies.

Enzymes are extremely complex catalytic structures with immense biological and technological importance. Nevertheless, their widespread environmental implementation faces several challenges, including high production costs, low operational stability, and intricate recovery and reusability. Therefore, the de novo design of minimalistic biomolecular nanomaterials that can efficiently mimic the biocatalytic function (bionanozymes) and overcome the limitations of natural enzymes is a critical goal in biomolecular engineering. Here, we report an exceptionally simple yet highly active and robust single amino acid bionanozyme that can catalyze the rapid oxidation of environmentally toxic phenolic contaminates and serves as an ultrasensitive tool to detect biologically important neurotransmitters similar to the laccase enzyme. While inspired by the laccase catalytic site, the substantially simpler copper-coordinated bionanozyme is ∼5400 times more cost-effective, four orders more efficient, and 36 times more sensitive compared to the natural protein. Furthermore, the designed mimic is stable under extreme conditions (pH, ionic strength, temperature, storage time), markedly reusable for several cycles, and displays broad substrate specificity. These findings hold great promise in developing efficient bionanozymes for analytical chemistry, environmental protection, and biotechnology., (© 2022. The Author(s).)

Per- and polyfluoroalkyl substances (PFASs) are hazardous, carcinogenic, and bioaccumulative contaminants found in drinking water sources. To mitigate and remove these persistent pollutants, recent experimental efforts have focused on photo-induced processes to accelerate their degradation; however, the mechanistic details of these promising degradation processes remain unclear. To shed crucial insight on these electronic-excited state processes, we present the first study of photo-induced degradation of explicitly-solvated PFASs using excited-state, real-time time-dependent density functional theory (RT-TDDFT) calculations. Furthermore, our large-scale RT-TDDFT calculations show that these photo-induced excitations can be highly selective by enabling a charge-transfer process that only dissociates the CF bond while keeping the surrounding water molecules intact. Collectively, the RT-TDDFT techniques used in this work (1) enable a new capability for probing photo-induced mechanisms that cannot be gleaned from conventional ground-state DFT calculations and (2) provide a rationale for understanding ongoing experiments that are actively exploring photo-induced degradation of PFASs and other environmental contaminants., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Borophene, the lightest among all Xenes, possesses extreme electronic mobility along with high carrier density and high Young's modulus. To accomplish device-quality borophene, novel approaches of realization of monolayers need to be urgently explored. In this work, micromechanical exfoliation is discovered to result in mono- and few-layered borophene of device quality. Borophene sheets are successfully fabricated down to monolayer thickness. Distinct crystallographic phases of borophene viz. XRD study reveals crystallographic phase transition from rhombohedral to several other eigen phases of borophene. The role of the destination substrates is held crucial in determining the final phase of the transferred sheet. The exfoliation energy is calculated by density functional theory. Molecular dynamics simulations are used to simulate the exfoliation process. Heterolayers of borophene, with black phosphorene (BP) or with molybdenum disulfide (MoS 2 ) atomic sheets, are found to result in photoexcited coupling quantum states. Gold-coated borophene bestows promising anchoring capability for surface-enhanced Raman spectroscopy (SERS). Successful demonstration of the electronic behavior of micromechanically exfoliated borophene and excitonic behavior of borophene-based heterolayers will guide future generation devices not only in electronics and excitonics, but also in thermal management, electronic packaging, hydrogen storage, hybrid energy storage, and clean energy solutions., (© 2021 Wiley-VCH GmbH.)

Multivalent batteries, such as magnesium-ion, calcium-ion, and zinc-ion batteries, have attracted significant attention as next-generation electrochemical energy storage devices to complement conventional lithium-ion batteries (LIBs). Among them, calcium-ion batteries (CIBs) are the least explored due to difficult reversible Ca deposition-dissolution. In this work, we examined the stability of four different Ca salts with weakly coordinating anions and three different solvents commonly employed in existing battery technologies to identify suitable candidates for CIBs. By employing Born-Oppenheimer molecular dynamics (BOMD) simulations on salt-Ca and solvent-Ca interfaces, we find that the tetraglyme solvent and carborane salt are promising candidates for CIBs. Due to the strong reducing nature of the calcium surface, the other salts and solvents readily decompose. We explain the microscopic mechanisms of salt/solvent decomposition on the Ca surface using time-dependent projected density of states, time-dependent charge-transfer plots, and climbing-image nudged elastic band calculations. Collectively, this work presents the first mechanistic assessment of the dynamical stability of candidate salts and solvents on a Ca surface using BOMD simulations, and provides a predictive path toward designing stable electrolytes for CIBs.

The accurate prediction of band gaps and structural properties in periodic systems continues to be one of the central goals of electronic structure theory. However, band gaps obtained from popular exchange-correlation (XC) functionals (such as LDA and PBE) are severely underestimated partly due to the spurious self-interaction error (SIE) inherent to these functionals. In this work, we present a new formulation and implementation of Wannier function-derived Fermi-Löwdin (WFL) orbitals for correcting the SIE in periodic systems. Since our approach utilizes a variational minimization of the self-interaction energy with respect to the Wannier charge centers (WCC), it is computationally more efficient than the HSE hybrid functional and other self-interaction corrections that require a large number of transformation matrix elements. Calculations on several (17 in total) prototypical molecular solids, semiconductors, and wide-bandgap materials show that our WFL self-interaction correction approach gives better band gaps and bulk moduli compared to semilocal functionals, largely due to the partial removal of self-interaction errors.

We apply direct nonadiabatic dynamics simulations to investigate photoinduced charge transfer reactions. Our approach is based on the mixed quantum-classical fewest switches surface hopping (FSSH) method that treats the transferring electron through time-dependent density functional theory and the nuclei classically. The photoinduced excited state is modeled as a transferring single-electron that initially occupies the LUMO of the donor molecule/moiety. This single-particle electronic wave function is then propagated quantum mechanically by solving the time-dependent Schrödinger equation in the basis of the instantaneous molecular orbitals (MOs) of the entire system. The nonadiabatic transitions among electronic states are modeled using the FSSH approach within the classical-path approximation. We apply this approach to simulate the photoinduced charge transfer dynamics in a few well-characterized molecular systems. Our results are in excellent agreement with both the experimental measurements and high-level (yet expensive) theoretical results.

By combining experimental measurements with ab initio molecular dynamics simulations, we provide the first microscopic description of the interaction between metal surfaces and a low-temperature nitrogen-hydrogen plasma. Our study focuses on the dissociation of hydrogen and nitrogen as the main activation route. We find that ammonia forms via an Eley-Rideal mechanism where atomic nitrogen abstracts hydrogen from the catalyst surface to form ammonia on an extremely short time scale (a few picoseconds). On copper, ammonia formation occurs via the interaction between plasma-produced atomic nitrogen and the H-terminated surface. On platinum, however, we find that surface saturation with NH groups is necessary for ammonia production to occur. Regardless of the metal surface, the reaction is limited by the mass transport of atomic nitrogen, consistent with the weak dependence on catalyst material that we observe and has been reported by several other groups. This study represents a significant step toward achieving a mechanistic, microscopic-scale understanding of catalytic processes activated in low-temperature plasma environments.

We present the first application of field programmable gate arrays (FPGAs) as new, customizable hardware architectures for carrying out fast and energy-efficient quantum dynamics simulations of large chemical/material systems. Instead of tailoring the software to fixed hardware, which is the typical case for writing quantum chemistry code for central processing units (CPUs) and graphics processing units (GPUs), FPGAs allow us to directly customize the underlying hardware (even at the level of specific electrical signals in the circuit) to give a truly optimized computational performance for quantum dynamics calculations. By offloading the most intensive and repetitive calculations onto an FPGA, we show that the computational performance of our real-time electron dynamics calculations can even exceed that of optimized commercial mathematical libraries running on high-performance GPUs. In addition to this impressive computational speedup, we show that FPGAs are immensely energy-efficient and consume 4 times less energy than modern GPU or CPU architectures. These energy savings are a practical and important metric for supercomputing centers (many of which exceed over $1 million in power costs alone), as exascale computing capabilities become more widespread and commonplace. Taken together, the implementation techniques and performance metrics of our study demonstrate that FPGAs could play a promising role in upcoming quantum chemistry and materials science applications, particularly for the acceleration and energy-efficient execution of quantum dynamics calculations.

Per- and polyfluoroalkyl substances (PFASs) are synthetic chemicals that are harmful to both the environment and human health. Using self-interaction-corrected Born-Oppenheimer molecular dynamics simulations, we provide the first real-time assessment of PFAS degradation in the presence of excess electrons. In particular, we show that the initial phase of the degradation involves the transformation of an alkane-type C-C bond into an alkene-type C[double bond, length as m-dash]C bond in the PFAS molecule, which is initiated by the trans elimination of fluorine atoms bonded to these adjacent carbon atoms.

Enzymatic activity is crucial for various technological applications, yet the complex structures and limited stability of enzymes often hinder their use. Hence, de novo design of robust biocatalysts that are much simpler than their natural counterparts and possess enhanced catalytic activity has long been a goal in biotechnology. Here, we present evidence for the ability of a single amino acid to self-assemble into a potent and stable catalytic structural entity. Spontaneously, phenylalanine (F) molecules coordinate with zinc ions to form a robust, layered, supramolecular amyloid-like ordered architecture (F-Zn(ii)) and exhibit remarkable carbonic anhydrase-like catalytic activity. Notably, amongst the reported artificial biomolecular hydrolases, F-Zn(ii) displays the lowest molecular mass and highest catalytic efficiency, in addition to reusability, thermal stability, substrate specificity, stereoselectivity and rapid catalytic CO 2 hydration ability. Thus, this report provides a rational path towards future de novo design of minimalistic biocatalysts for biotechnological and industrial applications., Competing Interests: Competing interests The authors declare no competing interests.