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Room-temperature sodium sulfur batteries (RT-NSBs) are among the promising candidates for large-scale energy storage applications because of the natural abundance of the electrode materials and impressive energy density. However, one of the main technical challenges of RT-NSBs is the shuttle effect by which active redox intermediates (i.e., sodium polysulfides Na2Sn, n = 1-8) are dissolved in electrolytes, which hamper the battery reversibility. The interfacial interplays between Na2Sn and the electrodes (or electrolytes) at the atomic level thus play an intrinsic role in elucidating the shuttle effect. This work reports the ab initio calculations to unravel the suppression of the shuttle effect using titanium carbide MXenes (Ti3C2Tx, Tx = F, O) as the cathode additives. The findings reveal that the shuttle phenomenon is efficiently resolved because the immense chemical bonding of Na2Sn-Ti3C2Tx interfaces competitively surpasses the binding magnitudes of Na2Sn-electrolyte interaction. The analysis of the electronic density of states and charge density further manifests that there is charge donation from the Na-3s orbital of Na2Sn to the unfilled F(O)-2p orbitals of metallic Ti3C2Tx. The metallicity of the Ti3C2Tx remains preserved during the entire course of the redox process, ensuring the rapid electrochemical kinetics. Furthermore, the presence of Ti3C2Tx additives drastically reduces the dissociation barrier of the final redox product Na2S, yielding the efficient utilization of sulfur during the discharge process. This work has proposed the unexplored functionality of Ti3C2Tx as the anchoring materials for RT-NSBs.
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Graphdiyne (GDY), a two-dimensional (2D) carbon, uniquely possesses mixed sp-sp2 hybridization, uniform nano-sized porous structure, semiconducting character, and excellent electrical conductivity. These features beneficially promote its applications in many fields, especially gas sensing. Based on density functional theory (DFT) and statistical thermodynamics, this study reports the sensing capabilities of pristine and selected transition metal (i.e., Fe, Sc, and Ti)-decorated GDY to detect environmentally hazardous arsine (AsH3) and phosphide (PH3) gases. We discover that Fe-doped GDY is a high-performance sensing material for detecting AsH3 and PH3 because of its selectivity and ultra-high sensitivity at the part-per-million (ppm) level. The presence of these gases induces measurably drastic changes in the electronic properties of Fe-doped GDY. The promising detection capabilities are fundamentally rooted in the appropriate chemical binding energies (i.e., ranging from -0.80 to -1.80 eV), which are basically rooted in the prominent orbital overlap among Fe-3d and As(P)-4p states. This study has raised the need to design efficient nanosensors using GDY-based materials.
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Sodium-sulfur batteries (NaSBs) have emerged as a promising energy storage technology for large-scale stationary applications such as smart electrical grids due to their exceptionally high energy density and cost-effectiveness. However, one of the challenging problems impeding their practical applications is the sulfur shuttle effect by which the active redox intermediates are gradually dissolved in electrolytes. In this work, we have employed first-principles density functional theory (DFT) calculations to unravel the suppression of the shuttle effect in NaSBs with a two-dimensional (2D) As2S3 monolayer as the anchoring material. We show that semiconducting As2S3 is a suitable anchoring layer to inhibit the dissolution of the polysulfide intermediates in common electrolytes because of its stronger chemical binding with sodium polysulfides than with the electrolytes. The immense adsorption is attributed to the electron donation from the unfilled S-3p states of the polysulfides to As2S3. These mechanisms increase the carrier population and consequently improve the electrical conductivity of As2S3. Hence, the use of As2S3 can both reduce the shuttle effect and enhance the cathode electron conductivity to enable improved cycling stability and coulombic efficiency of the battery.
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Proficient capture of carbon dioxide (CO2) is considered to be a backbone for environment protection through countering the climate change caused by mounting carbon content. Here we present a comprehensive mechanism to design novel functional nanostructures capable of capturing a large amount of CO2 efficiently. By means of van der Waals corrected density functional theory calculations, we have studied the structural, electronic and CO2 storage properties of carbon nitride (g-C6N8) nano sheets functionalized with a range of transition metal (TM) dopants ranging from Sc to Zn. The considered TMs bind strongly to the nano sheets with binding energies exceeding their respective cohesive energies, thus abolishing the possibility of metal cluster formation. Uniformly dispersed TMs change the electronic properties of semiconducting g-C6N8 through the transfer of valence charges from the former to the latter. This leaves all the TM dopants with significant positive charges, which are beneficial for CO2 adsorption. We have found that each TM's dopants anchor a maximum of four CO2 molecules with suitable adsorption energies (-0.15 to -1.0 eV) for ambient condition applications. Thus g-C6N8 nano sheets functionalized with selected TMs could serve as an ideal sorbent for CO2 capture.
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Green phosphorus and its monolayer variant, green phosphorene (GreenP), are the recent members of two-dimensional (2D) phosphorus polymorphs. The new polymorph possesses the high stability, tunable direct bandgap, exceptional electronic transport, and directionally anisotropic properties. All these unique features could reinforce it the new contender in a variety of electronic, optical, and sensing devices. Herein, we present gas-sensing characteristics of pristine and defected GreenP towards major environmental gases (i. e., NH3, NO, NO2, CO, CO2, and H2O) using combination of the density functional theory, statistical thermodynamic modeling, and the non-equilibrium Green's function approach (NEGF). The calculated adsorption energies, density of states (DOS), charge transfer, and Crystal Orbital Hamiltonian Population (COHP) reveal that NO, NO2, CO, CO2 are adsorbed on GreenP, stronger than both NH3 and H2O, which are weakly physisorbed via van der Waals interactions. Furthermore, substitutional doping by sulfur can selectively intensify the adsorption towards crucial NO2 gas because of the enhanced charge transfer between p orbitals of the dopant and the analyte. The statistical estimation of macroscopic measurable adsorption densities manifests that the significant amount of NO2 molecules can be practically adsorbed at ambient temperature even at the ultra-low concentration of part per billion (ppb). In addition, the current-voltage (I-V) characteristics of S-doped GreenP exhibit a variation upon NO2 exposure, indicating the superior sensitivity in sensing devices. Our work sheds light on the promising application of the novel GreenP as promising chemical gas sensors.
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Materials at high pressures and temperatures are of great current interest for warm dense matter physics, planetary sciences, and inertial fusion energy research. Shock-compression equation-of-state data and optical reflectivities of the fluid dense oxide, Gd3Ga5O12 (GGG), were measured at extremely high pressures up to 2.6 TPa (26 Mbar) generated by high-power laser irradiation and magnetically-driven hypervelocity impacts. Above 0.75 TPa, the GGG Hugoniot data approach/reach a universal linear line of fluid metals, and the optical reflectivity most likely reaches a constant value indicating that GGG undergoes a crossover from fluid semiconductor to poor metal with minimum metallic conductivity (MMC). These results suggest that most fluid compounds, e.g., strong planetary oxides, reach a common state on the universal Hugoniot of fluid metals (UHFM) with MMC at sufficiently extreme pressures and temperatures. The systematic behaviors of warm dense fluid would be useful benchmarks for developing theoretical equation-of-state and transport models in the warm dense matter regime in determining computational predictions.