Spin–phonon coupling plays an important role in single-molecule magnets and molecular qubits. However, there have been few detailed studies of its nature. Here, we show for the first time distinct couplings of g phonons of CoII(acac)2(H2O)2 (acac = acetylacetonate) and its deuterated analogs with zero-field-split, excited magnetic/spin levels (Kramers doublet (KD)) of the S = 3/2 electronic ground state. The couplings are observed as avoided crossings in magnetic-field-dependent Raman spectra with coupling constants of 1–2 cm−1. Far-IR spectra reveal the magnetic-dipole-allowed, inter-KD transition, shifting to higher energy with increasing field. Density functional theory calculations are used to rationalize energies and symmetries of the phonons. A vibronic coupling model, supported by electronic structure calculations, is proposed to rationalize the behavior of the coupled Raman peaks. This work spectroscopically reveals and quantitates the spin–phonon couplings in typical transition metal complexes and sheds light on the origin of the spin–phonon entanglement.

The general and practical inversion of diffraction data–producing a computer model correctly representing the material explored–is an important unsolved problem for disordered materials. Such modeling should proceed by using our full knowledge base, both from experiment and theory. In this paper, we describe a robust method to jointly exploit the power of ab initio atomistic simulation along with the information carried by diffraction data. The method is applied to two very different systems: amorphous silicon and two compositions of a solid electrolyte memory material silver-doped GeSe3. The technique is easy to implement, is faster and yields results much improved over conventional simulation methods for the materials explored. By direct calculation, we show that the method works for both poor and excellent glass forming materials. It offers a means to add a priori information in first-principles modeling of materials, and represents a significant step toward the computational design of non-crystalline materials using accurate interatomic interactions and experimental information.

We introduce a novel structural modeling technique: Force Enhanced Structural Refinement (FESR). The technique incorporates interatomic forces in Reverse Monte Carlo (RMC) simulations for structural refinement by fitting experimental diffraction data using the conventional RMC algorithm, and minimizes the total-energy and forces from an interatomic potential. We illustrate the usefulness of the approach by studying a-SiO2 and a-Si. The structural and electronic properties of the FESR models agree well with experimental neutron and x-ray diffraction data, and the results obtained from previous molecular-dynamics simulations of a-SiO2 and a-Si. We have shown that the method is more efficient than the conventional molecular-dynamics simulations via 'melt-quench'. The computational time in FESR has been observed to scale quadratically with the number of atoms.

In this paper, we offer large and realistic models of amorphous carbon spanning densities from 0.95 g/cm 3 to 3.5 g/cm 3 . The models are designed to agree as closely as possible with experimental diffraction data while simultaneously attaining a local minimum of a density functional Hamiltonian. The structure varies dramatically from interconnected wrapped and defective sp 2 sheets at 0.95 g/cm 3 to a nearly perfect tetrahedral topology at 3.5 g/cm 3 . Force Enhanced Atomic Refinement (FEAR) was used and is shown here to be computationally superior and more experimentally realistic than conventional ab initio melt quench methods. We thoroughly characterize our models by computing structural, electronic and vibrational spectra. The vibrational density of states of the 0.95 g/cm 3 model is strikingly similar to monolayer amorphous graphene. Our sp 2 /sp 3 ratios are close to experimental predictions where available, a consequence of compelling a satisfactory fit for pair correlation function. arXiv:1712.01437v1 [cond-mat.dis-nn]

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