Enhancing P2/O3 Biphasic Cathode Performance for Sodium-Ion Batteries: A Metaheuristic Approach to Multi-Element Doping Design.

Sodium-ion batteries (SIBs) have emerged as a compelling alternative to lithium-ion batteries (LIBs), exhibiting comparable electrochemical performance while capitalizing on the abundant availability of sodium resources. In SIBs, P2/O3 biphasic cathodes, despite their high energy, require furthur improvements in stability to meet current energy demands. This study introduces a systematic methodology that leverages the meta-heuristically assisted NSGA-II algorithm to optimize multi-element doping in electrode materials, aiming to transcend conventional trial-and-error methods and enhance cathode capacity by the synergistic integration of P2 and O3 phases. A comprehensive phase analysis of the meta-heuristically designed cathode material Na0.76Ni0.20Mn0.42Fe0.30Mg0.04Ti0.015Zr0.025O2 (D-NFMO) is presented, showcasing its remarkable initial reversible capacity of 175.5 mAh g-1 and exceptional long-term cyclic stability in sodium cells. The investigation of structural composition and the stabilizing mechanisms is performed through the integration of multiple characterization techniques. Remarkably, the irreversible phase transition of P2→OP4 in D-NFMO is observed to be dramatically suppressed, leading to a substantial enhancement in cycling stability. The comparison with the pristine cathode (P-NFMO) offers profound insights into the long-term electrochemical stability of D-NFMO, highlighting its potential as a high-voltage cathode material utilizing abundant earth elements in SIBs. This study opens up new possibilities for future advancements in sodium-ion battery technology.

Exploiting High-Voltage Stability of Dual-Ion Aqueous Electrolyte Reinforced by Incorporation of Fiberglass into Zwitterionic Hydrogel Electrolyte.

Rechargeable zinc aqueous batteries are key alternatives for replacing toxic, flammable, and expensive lithium-ion batteries in grid energy storage systems. However, these systems possess critical weaknesses, including the short electrochemical stability window of water and intrinsic fast zinc dendrite growth. Hydrogel electrolytes provide a possible solution, especially cross-linked zwitterionic polymers that possess strong water retention ability and high ionic conductivity. Herein, an in situ prepared fiberglass-incorporated dual-ion zwitterionic hydrogel electrolyte with an ionic conductivity of 24.32 mS cm-1 , electrochemical stability window up to 2.56 V, and high thermal stability is presented. By incorporating this hydrogel electrolyte of zinc and lithium triflate salts, a zinc//LiMn0.6 Fe0.4 PO4 pouch cell delivers a reversible capacity of 130 mAh g-1 in the range of 1.0-2.2 V at 0.1C, and the test at 2C provides an initial capacity of 82.4 mAh g-1 with 71.8% capacity retention after 1000 cycles with a coulombic efficiency of 97%. Additionally, the pouch cell is fire resistant and remains safe after cutting and piercing.

Unprecedented Cyclability and Moisture Durability of NaCrO2 Sodium-Ion Battery Cathode via Simultaneous Al Doping and Cr2O3 Coating.

Although there are many cathode candidates for sodium-ion batteries (NIBs), NaCrO2 remains one of the most attractive materials due to its reasonable level of capacity, nearly flat reversible voltages, and high thermal stability. However, the cyclic stability of NaCrO2 needs to be further improved in order to compete with other state-of-the-art NIB cathodes. In this study, we show that Cr2O3-coated and Al-doped NaCrO2, which is synthesized through a simple one-pot synthesis, can achieve unprecedented cyclic stability. We confirm the preferential formation of a Cr2O3 shell and a Na(Cr1-2xAl2x)O2 core, rather than xAl2O3/NaCrO2 or Na1/1+2x(Cr1/1+2xAl2x/1+2x)O2, through spectroscopic and microscopic methods. The core/shell compounds exhibit superior electrochemical properties compared to either Cr2O3-coated NaCrO2 without Al dopants or Al-doped NaCrO2 without shells because of their synergistic contributions. As a result, Na(Cr0.98Al0.02)O2 with a thin Cr2O3 layer (5 nm) shows no capacity fading during 1000 charge/discharge cycles while maintaining the rate capability of pristine NaCrO2. In addition, the compound is inert against humid air and water. We also discuss the reasons for the excellent performance of Cr2O3-coated Na(Cr1-2xAl2x)O2.

In situ health monitoring of multiscale structures and its instantaneous verification using mechanoluminescence and dual machine learning.

Extensive changes in the legal, commercial and technical requirements in engineering fields have necessitated automated real-time structural health monitoring (SHM) and instantaneous verification. An integrated system with mechanoluminescence (ML) and dual artificial intelligence (AI) modules with subsidiary finite element method (FEM) simulation is designed for in situ SHM and instantaneous verification. The ML module detects the exact position of a crack tip and evaluates the significance of existing cracks with a plastic stress-intensity factor (PSIF; K P ). ML fields and their corresponding K p M L values are referenced and verified using the FEM simulation and bidirectional generative adversarial network (GAN). Well-trained forward and backward GANs create fake FEM and ML images that appear authentic to observers; a convolutional neural network is used to postulate precise PSIFs from fake images. Finally, the reliability of the proposed system to satisfy existing commercial requirements is validated in terms of tension, compact tension, AI, and instrumentation.

Argyrodite configuration determination for DFT and AIMD calculations using an integrated optimization strategy.

When constructing a partially occupied model structure for use in density functional theory (DFT) and ab initio molecular dynamics (AIMD) calculations, the selection of appropriate configurations has been a vexing issue. Random sampling and the ensuing low-Coulomb-energy entry selection have been routine. Here, we report a more efficient way of selecting low-Coulomb-energy configurations for a representative solid electrolyte, Li6PS5Cl. Metaheuristics (genetic algorithm, particle swarm optimization, cuckoo search, and harmony search), Bayesian optimization, and modified deep Q-learning are utilized to search the large configurational space. Ten configuration candidates that exhibit relatively low Coulomb energy values and thereby lead to more convincing DFT and AIMD calculation results are pinpointed along with computational cost savings by the assistance of the above-described optimization algorithms, which constitute an integrated optimization strategy. Consequently, the integrated optimization strategy outperforms the conventional random sampling-based selection strategy.

Optimal Composition of Li Argyrodite with Harmonious Conductivity and Chemical/Electrochemical Stability: Fine-Tuned Via Tandem Particle Swarm Optimization.

A tandem (two-step) particle swarm optimization (PSO) algorithm is implemented in the argyrodite-based multidimensional composition space for the discovery of an optimal argyrodite composition, i.e., with the highest ionic conductivity (7.78 mS cm-1 ). To enhance the industrial adaptability, an elaborate pellet preparation procedure is not used. The optimal composition (Li5.5 PS4.5 Cl0.89 Br0.61 ) is fine-tuned to enhance its practical viability by incorporating oxygen in a stepwise manner. The final composition (Li5.5 PS4.23 O0.27 Cl0.89 Br0.61 ), which exhibits an ionic conductivity (σion ) of 6.70 mS cm-1 and an activation barrier of 0.27 eV, is further characterized by analyzing both its moisture and electrochemical stability. Relative to the other compositions, the exposure of Li5.5 PS4.23 O0.27 Cl0.89 Br0.61 to a humid atmosphere results in the least amount of H2 S released and a negligible change in structure. The improvement in the interfacial stability between the Li(Ni0.9 Co0.05 Mn0.05 )O2 cathode and Li5.5 PS4.23 O0.27 Cl0.89 Br0.61 also results in greater specific capacity during fast charge/discharge. The structural and chemical features of Li5.5 PS4.5 Cl0.89 Br0.61 and Li5.5 PS4.23 O0.27 Cl0.89 Br0.61 argyrodites are characterized using synchrotron X-ray diffraction, Raman spectroscopy, and X-ray photoelectron spectroscopy. This work presents a novel argyrodite composition with favorably balanced properties while providing broad insights into material discovery methodologies with applications for battery development.

Unravelling the Nature of the Intrinsic Complex Structure of Binary-Phase Na-Layered Oxides.

The layered sodium transition metal oxide, NaTMO2 (TM = transition metal), with a binary or ternary phases has displayed outstanding electrochemical performance as a new class of strategy cathode materials for sodium-ion batteries (SIBs). Herein, an in-depth phase analysis of developed Na1-x TMO2 cathode materials, Na0.76 Ni0.20 Fe0.40 Mn0.40 O2 with P2- and O3-type phases (NFMO-P2/O3) is offered. Structural visualization on an atomic scale is also provided and the following findings are unveiled: i) the existence of a mixed-phase intergrowth layer distribution and unequal distribution of P2 and O3 phases along two different crystal plane indices and ii) a complete reversible charge/discharge process for the initial two cycles that displays a simple phase transformation, which is unprecedented. Moreover, first-principles calculations support the evidence of the formation of a binary NFMO-P2/O3 compound, over the proposed hypothetical monophasic structures (O3, P3, O'3, and P2 phases). As a result, the synergetic effect of the simultaneous existence of P- and O-type phases with their unique structures allows an extraordinary level of capacity retention in a wide range of voltage (1.5-4.5 V). It is believed that the insightful understanding of the proposed materials can introduce new perspectives for the development of high-voltage cathode materials for SIBs.

Zinc Anodes Modified by One-Molecular-Thick Self-Assembled Monolayers for Simultaneous Suppression of Side-Reactions and Dendrite-Formation in Aqueous Zinc-Ion Batteries.

Repeated charge/discharge in aqueous zinc-ion batteries (ZIBs) commonly results in surface corrosion/passivation and dendrite formation on zinc anodes, which is a major challenge for the commercialization of zinc-based batteries. In this work, metallic Zn modified by self-assembled monolayers is described as a viable anode for ZIBs. ω-mercaptoundecanoic acid that is spontaneously adsorbed on Zn (MUDA/Zn) contributes to the simultaneous suppression of side reactions and dendrite formation in ZIBs. Though one-molecular-thick, densely packed alkyl chains prohibit H2 O and H+ from making direct contact with the underlying Zn, and surface carboxylate moieties (-COO- ) effectively repel anionic species (OH- ) in a solution, which renders a Zn anode inert against zincate formation within a wide range of pH. In contrast, the electrostatic attraction between surface-carboxylates and cations increases the concentration of Zn2+ on the surface of MUDA/Zn to facilitate Zn plating/stripping with less overpotentials. The high concentration of Zn2+ also results in an increased number of nucleation sites, which enhances the lateral growth of Zn with no formation of dendrites. As a result, MUDA/Zn shows excellent stability during prolonged Zn plating/stripping within a wide range of pH. The advantageous properties of MUDA/Zn are also retained in full-cells coupled with δ-MnO2 cathodes.

Digital Image Correlation Compatible Mechanoluminescent Skin for Structural Health Monitoring.

Monitoring structural health using mechanoluminescent (ML) effects is widely considered as a potential full-field and direct visualizing optical method with high spatial and temporal resolution and simple setup in a noncontact manner. The challenges and uncertainties in the mapping of ML field to effective strain field, however, tend to limit significant commercial ML applications for structural health monitoring systems. Here, however, quantification problems are resolved using the digital image correlation (DIC) method. Specifically, an image containing mechanically induced photon information is processed using a DIC algorithm to measure the strain field components, which enables the establishment of a calibration curve when the ML field is mapped onto the effective strain field using pixel level information. The results show a linear relationship between effective strain and ML intensity despite the plastic flow in ML skin. Furthermore, the calibration curve allows for easy conversion of ML field to effective-strain field at the crack-tip plastic zone of the alloy structure, retaining its spatial resolution. The compatibility of ML skin with the DIC algorithm not only enables the quantification of the ML effects of several organic/inorganic ML materials, but may also be useful in elucidating the fundamentals of the trap-controlled mechanism.

A machine-learning-based alloy design platform that enables both forward and inverse predictions for thermo-mechanically controlled processed (TMCP) steel alloys.

Predicting mechanical properties such as yield strength (YS) and ultimate tensile strength (UTS) is an intricate undertaking in practice, notwithstanding a plethora of well-established theoretical and empirical models. A data-driven approach should be a fundamental exercise when making YS/UTS predictions. For this study, we collected 16 descriptors (attributes) that implicate the compositional and processing information and the corresponding YS/UTS values for 5473 thermo-mechanically controlled processed (TMCP) steel alloys. We set up an integrated machine-learning (ML) platform consisting of 16 ML algorithms to predict the YS/UTS based on the descriptors. The integrated ML platform involved regularization-based linear regression algorithms, ensemble ML algorithms, and some non-linear ML algorithms. Despite the dirty nature of most real-world industry data, we obtained acceptable holdout dataset test results such as R2 > 0.6 and MSE < 0.01 for seven non-linear ML algorithms. The seven fully trained non-linear ML models were used for the ensuing 'inverse design (prediction)' based on an elitist-reinforced, non-dominated sorting genetic algorithm (NSGA-II). The NSGA-II enabled us to predict solutions that exhibit desirable YS/UTS values for each ML algorithm. In addition, the NSGA-II-driven solutions in the 16-dimensional input feature space were visualized using holographic research strategy (HRS) in order to systematically compare and analyze the inverse-predicted solutions for each ML algorithm.

Cyan-Light-Emitting Chalcogenometallate Phosphor, KGaS2:Eu2+, for Phosphor-Converted White Light-Emitting Diodes.

A novel KGaS2 phosphor host that emits a cyan light was discovered to fill the cyan gap in the visible spectrum of phosphor-converted white light-emitting diodes (pc-wLEDs). KGaS2, belonging to the chalcogenometallates of the type ABQ2, was synthesized via a solid-state route with compositions optimized to achieve a phosphor host that would achieve the best photoluminescence (PL) properties. The activation with Eu2+ gave rise to PL in the cyan region of the spectrum with a PL maximum at ∼498 nm, as measured under the near-UV (420 nm) and blue (450 nm) excitations. The PL properties at the near-UV excitation are found to be much better, as compared to those obtained at the blue excitation. The Rietveld analysis, using high resolution synchrotron X-ray diffraction calibrated at a wavelength of 1.522 Å and selected area electron diffraction (SAED) pattern analysis of the composition optimized with the highest PL intensity, revealed a centrosymmetric monoclinic structure in the C2/c space group. The stoichiometry of the optimized composition, as estimated using Rietveld refinement, was revealed as KGa0.921S1.882:Eu2+. The decay curve measurement, using time-resolved spectroscopy, yielded a 10% decay time of 0.41 µs, which is much smaller compared with the decay time of the commercially available ß-SIALON phosphor that has a 10% decay time of 1.71 µs. The white pc-LED, fabricated with a cyan phosphor, had a higher value on the color rendering index and a lower value for color correlated temperatures, as compared with the version fabricated without a cyan phosphor, which makes this novel phosphor suitable for applications as a pc-wLED.

Dirty engineering data-driven inverse prediction machine learning model.

Most data-driven machine learning (ML) approaches established in metallurgy research fields are focused on a build-up of reliable quantitative models that predict a material property from a given set of material conditions. In general, the input feature dimension (the number of material condition variables) is much higher than the output feature dimension (the number of material properties of concern). Rather than such a forward-prediction ML model, it is necessary to develop so-called inverse-design modeling, wherein required material conditions could be deduced from a set of desired material properties. Here we report a novel inverse design strategy that employs two independent approaches: a metaheuristics-assisted inverse reading of conventional forward ML models and an atypical inverse ML model based on a modified variational autoencoder. These two unprecedented approaches were successful and led to overlapped results, from which we pinpointed several novel thermo-mechanically controlled processed (TMCP) steel alloy candidates that were validated by a rule-based thermodynamic calculation tool (Thermo-Calc.). We also suggested a practical protocol to elucidate how to treat engineering data collected from industry, which is not prepared as independent and identically distributed (IID) random data.

Ca2+-Based Dual-Carbon Batteries in Ternary Ionic Liquid Electrolytes.

Herein, we propose Ca2+-based dual-carbon batteries (DCBs) that undergo a simultaneous occurrence of reversible accommodations of Ca2+ in a graphite anode (mesocarbon microbeads) and of bis(trifluoromethanesulfonyl)imide (TFSI-) in a graphite cathode (KS6L). For this purpose, we precisely tune electrolytes composed of Ca2+ complexed with a single tetraglyme molecule ([Ca:G4]) in N-butyl-N-methylpyrrolidinium TFSI (Pyr14TFSI) ionic liquid (IL). This ternary electrolyte is required for the enhancement of anodic stability that is needed to accomplish maximal TFSI- intercalation into KS6L at a high potential. A solution of 0.5 M [Ca:G4] in IL ([Ca:G4]/IL) is found to be optimal for DCBs. First, the electrochemical properties and the structural evolution of each graphite in a half-cell configuration are described to demonstrate excellent electrochemical performance. Second, the negligible intercalation of Pyr14+ into an MCMB anode is ascertained in 0.5 M [Ca:G4]/IL. Finally, DCBs are constructed by coupling two electrodes to show high capacity (54.0 mA h g-1 at 200 mA g-1) and reasonable cyclability (capacity fading of 0.022 mA h g-1 cycle-1 at 200 mA g-1 during 300 charge/discharge cycles). This work is the first to examine DCBs based on Ca2+ intercalation and helps pave the way for the development of a new type of next-generation batteries.

Publisher Correction: A deep-learning technique for phase identification in multiphase inorganic compounds using synthetic XRD powder patterns.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A deep-learning technique for phase identification in multiphase inorganic compounds using synthetic XRD powder patterns.

Here we report a facile, prompt protocol based on deep-learning techniques to sort out intricate phase identification and quantification problems in complex multiphase inorganic compounds. We simulate plausible powder X-ray powder diffraction (XRD) patterns for 170 inorganic compounds in the Sr-Li-Al-O quaternary compositional pool, wherein promising LED phosphors have been recently discovered. Finally, 1,785,405 synthetic XRD patterns are prepared by combinatorically mixing the simulated powder XRD patterns of 170 inorganic compounds. Convolutional neural network (CNN) models are built and eventually trained using this large prepared dataset. The fully trained CNN model promptly and accurately identifies the constituent phases in complex multiphase inorganic compounds. Although the CNN is trained using the simulated XRD data, a test with real experimental XRD data returns an accuracy of nearly 100% for phase identification and 86% for three-step-phase-fraction quantification.

Aliovalent-doped sodium chromium oxide (Na0.9Cr0.9Sn0.1O2 and Na0.8Cr0.9Sb0.1O2) for sodium-ion battery cathodes with high-voltage characteristics.

NaCrO2 with high rate-capability is an attractive cathode material for sodium-ion batteries (NIBs). However, the amount of reversibly extractable Na+ ions is restricted by half, which results in relatively low energy density for practical NIB cathodes. Herein, we describe aliovalent-doped O3-Na0.9[Cr0.9Sn0.1]O2 (NCSnO) and O3-Na0.8[Cr0.9Sb0.1]O2 (NCSbO), both of which show high-voltage characteristics that translate to an increase in energy density. In contrast to NaCrO2, NCSnO and NCSbO can be reversibly charged to 3.80 and 3.95 V, respectively, delivering 0.5 Na+ along with Cr3+/4+ redox alone. The reversible chargeability to Na0.4[Cr0.9Sn0.1]O2 and Na0.3[Cr0.9Sb0.1]O2 is not associated with the suppression of Cr6+ formation. Both compounds show concentrations of Cr6+ that are higher than that of Na0.3CrO2, with an absence of O3' phases. This implies that aliovalent-doping contributes to a suppression of the Cr6+ migration into tetrahedral sites in the interslab space, which reduces the possibility of irreversible comproportionation. NCSnO and NCSbO deliver capacities comparable to that of NaCrO2, but show a higher average discharge voltage (2.94 V for NaCrO2; 3.14 V for NCSnO; 3.21 V for NCSbO), which leads to a noticeable increase in energy densities. The high-voltage characteristics of NCSnO and NCSbO are also validated via density-functional-theory calculations.

New red-emitting phosphor Rb x K3-x SiF7:Mn4+ (x = 0, 1, 2, 3): DFT predictions and synthesis.

Finding new phosphors through an efficient method is important in terms of saving time and cost related to the development of phosphor materials. The ability to identify new phosphors through preliminary simulations by calculations prior to the actual synthesis of the materials can maximize the efficiency of novel phosphor development. In this paper, we demonstrate the use of density functional theory (DFT) calculations to guide the development of a new red phosphor. We performed first-principles calculations based on DFT for pristine and Mn-doped Rb x K3-x SiF7 (x = 0, 1, 2, 3) and predicted their stability, electronic structure, and luminescence properties. On the basis of the results, we then synthesized the stable Rb2KSiF7:Mn4+ red conversion phosphor and investigated its luminescence, structure, and stability. As a result, we confirmed that Rb2KSiF7:Mn4+ emitted red light with a longer wavelength than that emitted by K3SiF7:Mn4+ and a wavelength similar to that of K2SiF6:Mn4+. These results show that DFT calculations can provide rational insights into the design of a phosphor material before it is synthesized, thereby reducing the time and cost required to develop new red conversion phosphors.

Graphite as a Long-Life Ca2+-Intercalation Anode and its Implementation for Rocking-Chair Type Calcium-Ion Batteries.

Herein, graphite is proposed as a reliable Ca2+-intercalation anode in tetraglyme (G4). When charged (reduced), graphite accommodates solvated Ca2+-ions (Ca-G4) and delivers a reversible capacity of 62 mAh g-1 that signifies the formation of a ternary intercalation compound, Ca-G4·C72. Mass/volume changes during Ca-G4 intercalation and the evolution of in operando X-ray diffraction studies both suggest that Ca-G4 intercalation results in the formation of an intermediate phase between stage-III and stage-II with a gallery height of 11.41 Å. Density functional theory calculations also reveal that the most stable conformation of Ca-G4 has a planar structure with Ca2+ surrounded by G4, which eventually forms a double stack that aligns with graphene layers after intercalation. Despite large dimensional changes during charge/discharge (C/D), both rate performance and cyclic stability are excellent. Graphite retains a substantial capacity at high C/D rates (e.g., 47 mAh g-1 at 1.0 A g-1 s vs 62 mAh g-1 at 0.05 A g-1) and shows no capacity decay during as many as 2000 C/D cycles. As the first Ca2+-shuttling calcium-ion batteries with a graphite anode, a full-cell is constructed by coupling with an organic cathode and its electrochemical performance is presented.

Determination of possible configurations for Li0.5CoO2 delithiated Li-ion battery cathodes via DFT calculations coupled with a multi-objective non-dominated sorting genetic algorithm (NSGA-III).

Here, we propose a new and logical approach to systematically treat the configurational diversity in density functional theory (DFT) calculations. To tackle this issue, we select Li0.5CoO2 as a representative example because it is one of the most extensively studied cathodes in Li-ion batteries (LIBs), and it has a huge number of disordered configurations. To delineate the configurations that will match well with the experimentally measured macro-functions of redox potential, band gap energy, and magnetic moment, we adopt a multi-objective, non-dominated sorting, genetic algorithm (NSGA-III) that enables the simultaneous optimization of these three objective functions. The decision variables include configuration of the Li/vacancy, initial input for the magnetic moment distribution reflecting Co3+/Co4+ distribution, and initial input for the lattice parameter and Hubbard U. We use NSGA-III to separate the configurations that exhibit awkward objective function values, which allows us to pinpoint a set of plausible configurations that match the experimentally estimated values of the objective functions. The results reveal a plausible configuration that is a mixture of various ordered/disordered configurations rather than a simple ordered structure.

KCrS2 Cathode with Considerable Cyclability and High Rate Performance: The First K+ Stoichiometric Layered Compound for Potassium-Ion Batteries.

KCrS2 is presented as a stable and high-rate layered material that can be used as a cathode in potassium-ion batteries. As far as it is known, KCrS2 is the only layered material with stoichiometric amounts of K+ , which enables coupling with a graphite anode for full-cell construction. Cr(III)/Cr(IV) redox in KCrS2 is also unique, because LiCrS2 and NaCrS2 are known to experience S2- /S2 2- redox. O3-KCrS2 is first charged to P3-K0.39 CrS2 and subsequently discharged to O'3-K0.8 CrS2 , delivering an initial discharge capacity of 71 mAh g-1 . The following charge/discharge (C/D) shows excellent reversibility between O'3-K0.8 CrS2 and P3-K0.39 CrS2 , retaining ≈90% of the initial capacity during 1000 continuous cycles. The rate performance is also noteworthy. A C/D rate increase of 100-fold (0.05 to 5 C) reduces the reversible capacity only by 39% (71 to 43 mAh g-1 ). The excellent cyclic stability and high rate performance are ascribed to the soft sulfide framework, which can effectively buffer the stress caused by K+ deinsertion/insertion. During the transformation between P3-K0.39 CrS2 and O'3-K0.8 CrS2 , the material resides mostly in the P3 phase, which minimizes the abrupt dimension change and allows facile K+ diffusion through spacious prismatic sites. Structural analysis and density functional theory calculations firmly support this reasoning.