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Register a new userPredicting the pseudocapacitive windows for MXene electrodes with voltage-dependent cluster expansion models
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MXene transition-metal carbides and nitrides are of growing interest for energy storage applications. These compounds are especially promising for use as pseudocapacitive electrodes due to their ability to convert energy electrochemically at fast rates. Using voltage-dependent cluster expansion models, we predict the charge storage performance of MXene pseudocapacitors for a range of electrode compositions. $M_3C_2O_2$ electrodes based on group-VI transition metals have up to 80% larger areal energy densities than prototypical titanium-based ( e.g. $Ti_3C_2O_2$) MXene electrodes. We attribute this high pseudocapacitance to the Faradaic voltage windows of group-VI MXene electrodes, which are predicted to be 1.2 to 1.8 times larger than those of titanium-based MXenes. The size of the pseudocapacitive voltage window increases with the range of oxidation states that is accessible to the MXene transition metals. By similar mechanisms, the presence of multiple ions in the solvent (Li$^+$ and H$^+$) leads to sharp changes in the transition-metal oxidation states and can significantly increase the charge capacity of MXene pseudocapacitors.
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Natural abundance, impressive chemical characteristics and economic feasibility have rekindled the appeal for rechargeable sodium (Na) batteries as a practical solution for the growing energy demand, environmental sustainability and energy independence. However, the scarcity of viable positive electrode materials remains a huge impediment to the actualization of this technology. In this paper, we explore honeycomb layered oxides adopting the composition Na$_2$Ni$_{2-x}$Co$_x$TeO$_6$ ($x = 0, 0.25$ and $0.50$) as feasible positive electrode (cathode) materials for rechargeable sodium batteries at both room- and elevated temperatures using ionic liquids. Through standard galvanostatic assessments and analyses we demonstrate that substitution of nickel with cobalt in Na$_2$Ni$_2$TeO$_6$ leads to an increase in the discharge voltage to nearly $4$ V (versus Na$^+$ / Na) for the Na$_2$Ni$_{2-x}$Co$_x$TeO$_6$ family of honeycomb layered oxide materials, which surpasses the attained average voltages for most layered oxide positive electrode materials that facilitate Na-ion desertion. We also verify the increased kinetics within the Na$_2$Ni$_{2-x}$Co$_x$TeO$_6$ honeycomb layered oxides during operations at elevated temperatures which lead to an increase in reversible capacity of the rechargeable Na battery. This study underpins the doping of congener transition metal atoms to the honeycomb structure of Na$_2$Ni$_2$TeO$_6$ in addition to elevated-temperature operation as a judicious route to enhance the electrochemical performance of analogous layered oxides.
Van der Waals (vdW) heterostructures, stacking different two-dimensional materials, have opened up unprecedented opportunities to explore new physics and device concepts. Especially interesting are recently discovered two-dimensional magnetic vdW materials, providing new paradigms for spintronic applications. Here, using density functional theory (DFT) calculations, we investigate the spin-dependent electronic transport across vdW magnetic tunnel junctions (MTJs) composed of Fe3GeTe2 ferromagnetic electrodes and a graphene or hexagonal boron nitride (h-BN) spacer layer. For both types of junctions, we find that the junction resistance changes by thousands of percent when the magnetization of the electrodes is switched from parallel to antiparallel. Such a giant tunneling magnetoresistance (TMR) effect is driven by dissimilar electronic structure of the two spin-conducting channels in Fe3GeTe2, resulting in a mismatch between the incoming and outgoing Bloch states in the electrodes and thus suppressed transmission for an antiparallel-aligned MTJ. The vdW bounding between electrodes and a spacer layer makes this result virtually independent of the type of the spacer layer, making the predicted giant TMR effect robust with respect to strain, lattice mismatch, interface distance and other parameters which may vary in the experiment. We hope that our results will further stimulate experimental studies of vdW MTJs and pave the way for their applications in spintronics.
MXenes are two-dimensional materials with a rich set of remarkable chemical and electromagnetic properties, the latter including saturable absorption and intense surface plasmon resonances. To fully harness the functionality of MXenes for applications in optics, electronics and sensing, it is important to understand the interaction of light with MXenes on atomic and femtosecond dimensions. Here, we use ultrafast electron diffraction and high-resolution electron microscopy to investigate the laser-induced structural dynamics of Ti3C2Tx nanosheets. We find an exceptionally fast lattice response with an electron-phonon coupling time of 230 femtoseconds. Repetitive femtosecond laser excitation transforms Ti3C2Tx through a structural transition into a metamaterial with deeply sub-wavelength nanoripples that are aligned with the laser polarization. By a further laser illumination, the material is reversibly photo-switchable between a flat and rippled morphology. The resulting nanostructured MXene metamaterial with directional nanoripples is expected to exhibit an anisotropic optical and electronic response as well as an enhanced chemical activity that can be switched on and off by light.
Polynomial chaos expansions (PCEs) have been used in many real-world engineering applications to quantify how the uncertainty of an output is propagated from inputs. PCEs for models with independent inputs have been extensively explored in the literature. Recently, different approaches have been proposed for models with dependent inputs to expand the use of PCEs to more real-world applications. Typical approaches include building PCEs based on the Gram-Schmidt algorithm or transforming the dependent inputs into independent inputs. However, the two approaches have their limitations regarding computational efficiency and additional assumptions about the input distributions, respectively. In this paper, we propose a data-driven approach to build sparse PCEs for models with dependent inputs. The proposed algorithm recursively constructs orthonormal polynomials using a set of monomials based on their correlations with the output. The proposed algorithm on building sparse PCEs not only reduces the number of minimally required observations but also improves the numerical stability and computational efficiency. Four numerical examples are implemented to validate the proposed algorithm.
Hybrid materials of MXenes (2D carbides and nitrides) and transition-metal oxides (TMOs) have shown great promise in electrical energy storage and 2D heterostructures have been proposed as the next-generation electrode materials to expand the limits of current technology. Here we use first principles density functional theory to investigate the interfacial structure, energetics, and electronic properties of the heterostructures of MXenes (Tin+1CnT2; T=terminal groups) and anatase TiO2. We find that the greatest work-function differences are between OH-terminated-MXene (1.6 eV) and anatase TiO2(101) (6.4 eV), resulting in the largest interfacial electron transfer (~0.9 e/nm2 across the interface) from MXene to the TiO2 layer. This interface also has the strongest adhesion and further strengthened by hydrogen bond formation. For O-, F-, or mixed O-/F- terminated Tin+1Cn MXenes, electron transfer is minimal and interfacial adhesion is weak for their heterostructures with TiO2. The strong dependence of the interfacial properties of the MXene/TiO2 heterostructures on the surface chemistry of the MXenes will be useful to tune the heterostructures for electric-energy-storage applications.
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