Energy sufficiency for deep decarbonization: A modeling framework
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It is reported that the chemical and electronic structures of 15 different sulfates are studied using S L 2,3 soft X-ray emission spectroscopy (XES). Sulfur L 2,3 XES spectra of sulfates are distinctively different from those of other sulfur compounds, which makes XES a powerful technique for sulfate detection. Furthermore, subtle but distinct differences between the spectra of sulfates with different cations are observed, which allow a further differentiation of the specific compound. Most prominently, the position and width of the emission from "S 3s" derived bands systematically vary for different compounds, which can be understood with electronic structure and spectral calculations based on density functional theory.
The semicrystalline microstructures of donor-acceptor conjugated polymers strongly impact their optoelectronic properties. The control of the microstructure relies on the understandings of the crystallization processes in these polymers, from packing structures to crystallization kinetics. How fast these conjugated polymer chains crystallize and how their chemical structures and pre-existing microstructure history influence their crystallization have so far remained unclear, due to the fast crystallization rate caused by chain rigid structures and strong interactions. Here, ultrafast scanning calorimetry (FSC) is employed to reveal the crystallization behaviors of high perform- ance diketopyrrolopyrrole (DPP)-based conjugated polymers with scanning rates up to 500 000 K/s. Through elaborately designed nonisothermal and isothermal crystallization studies, we probed the fast crystallization kinetics and extracted the two-step crystallization process of these polymers quantitatively. We found that both the rigidity of the chain backbones and the preinduced crystalline microstructures can influence the crystallization rate over an order of magnitude at the same degree of undercooling. We further demonstrated the manipulated crystallization kinetics in the DPP-based polymer films with different amounts of preinduced crystallites and correlate it to the polymers’ charge transport mobility.
Single-crystal materials have attracted growing interest in battery research due to their well-defined crystallographic orientation, absence of grain boundaries, and enhanced mechanical and electrochemical stability. This Review provides a comprehensive overview of recent advances in the synthesis, structural evolution, and performance optimization of single-crystal electrodes and solid electrolytes. Particular focus is placed on the application of advanced X-ray diffraction (XRD) techniques, including operando synchrotron diffraction, reciprocal space mapping, and Bragg coherent diffraction imaging, which have enabled in-depth investigations of lattice strain, cation disorder, phase transitions, and defect formation. Representative case studies across Ni-rich layered oxides, spinel-type cathodes, and garnet-based electrolytes are examined to highlight the structural features unique to single crystals. Additionally, the synergistic integration of XRD with machine learning, tomography, and spectroscopy is discussed as a powerful direction for real-time analysis and predictive modeling. Furthermore, these insights provide critical guidance for the rational design of high-performance single-crystal materials in lithium, sodium, and solid-state battery systems.
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We report the synthesis, characterization, and solution self-assembly of plenary Nb 6 P 2 W 12 -based transition-metal substituted polyoxometalate, which is obtained by simply adding transition metals (Co 2+ ) into aqueous solution containing cluster [(NbO 2 ) 6 P 2 W 12 O 56 ] 12- , which is obtained by an in situ synthetic method. The incorporation of Co 2+ ions significantly affects the crystal structure, resulting in the formation of a 1D chain-like crystal and the first example of a niobotungstate-based cobalt derivative cluster. The behavior and stability of this cluster in solution are confirmed by time-resolved static light scattering, dynamic light scattering, small-angle X-ray scattering, and electrospray mass spectrometry studies.
Quantum embedding theories are promising approaches to investigate strongly correlated electronic states of active regions of large-scale molecular or condensed systems. Notable examples are spin defects in semiconductors and insulators. We present a detailed derivation of a quantum embedding theory recently introduced, which is based on the definition of effective Hamiltonians. The effect of the environment on a chosen active space is accounted for through screened Coulomb interactions evaluated using density functional theory. Importantly, the random phase approximation is not required, and the evaluation of virtual electronic orbitals is circumvented with algorithms previously developed in the context of calculations based on many-body perturbation theory. In addition, we generalize the quantum embedding theory to active spaces composed of orbitals that are not eigenstates of Kohn–Sham Hamiltonians. Finally, we report results for spin defects in semiconductors.
Here, we present a Green’s function formulation of the quantum defect embedding theory (QDET) where a double counting scheme is rigorously derived within the $G_0W_0$ approximation. We then show the robustness of our methodology by applying the theory with the newly derived scheme to several defects in diamond. Additionally, we discuss a strategy to obtain converged results as a function of the size and composition of the active space. Our results show that QDET is a promising approach to investigate strongly correlated states of defects in solids.
Here, we propose a computational protocol for quantum simulations of fermionic Hamiltonians on a quantum computer, enabling calculations on spin defect systems which were previously not feasible using conventional encodings and a unitary coupled-cluster ansatz of variational quantum eigensolvers. We combine a qubit-efficient encoding scheme mapping Slater determinants onto qubits with a modified qubitcoupled cluster ansatz and noise-mitigation techniques. Our strategy leads to a substantial improvement in the scaling of circuit gate counts and in the number of required qubits, and to a decrease in the number of required variational parameters, thus increasing the resilience to noise. We present results for spin defects of interest for quantum technologies, going beyond minimum models for the negatively charged nitrogen vacancy center in diamonds and the double vacancy in 4H silicon carbide (4H-SiC) and tackling a defect as complex as negatively charged silicon vacancy in 4H-SiC for the first time.
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