Coulomb attraction between electrons and holes in a narrow-gap semiconductor or a semimetal is predicted to lead to an elusive phase of matter dubbed excitonic insulator. However, direct observation of such electronic instability remains extremely rare. Here, we report the observation of incipient divergence in the static excitonic susceptibility of the candidate material Ta2NiSe5 using Raman spectroscopy. Critical fluctuations of the excitonic order parameter give rise to quasi-elastic scattering of B2g symmetry, whose intensity grows inversely with temperature toward the Weiss temperature of TW ≈ 237 K, which is arrested by a structural phase transition driven by an acoustic phonon of the same symmetry at TC = 325 K. Concurrently, a B2g optical phonon becomes heavily damped to the extent that its trace is almost invisible around TC, which manifests a strong electron-phonon coupling that has obscured the identification of the low-temperature phase as an excitonic insulator for more than a decade. Our results unambiguously reveal the electronic origin of the phase transition.

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Electrochemical models of lithium-ion batteries are derived according to the laws of physics; therefore, the parameters represent specific physical quantities such as lithium diffusivities, particle volume fractions, and ion intercalation rates. It is important to estimate these parameters to identify the internal states of a lithium-ion battery for efficient and safe management. Until now, parameter estimation algorithms for electrochemical lithium-ion battery models have been developed without considering the unequal identifiability among the target parameters. Thus, it is highly likely that existing algorithms exhibit inefficient exploration and lead to a slow convergence rate and even large parameter estimation error. For more accurate parameter estimation of an electrochemical lithium-ion battery model, we propose a new adaptive exploration harmony search (AEHS) scheme that provides a wide search space for a longer period of time when estimating parameters with low identifiability. The proposed algorithm is based on improved harmony search; its bandwidth parameters for determining the level of exploration are adjusted according to the individual and joint variabilities computed from the distributions of previously estimated parameters. Such adaptive bandwidth parameters can reduce inefficient exploration and enable fast convergence, allowing exploration that achieves global optimality. Simulation results show that the proposed parameter estimation algorithm produces the highest convergence rate and the smallest parameter estimation error compared with existing schemes. The performance of the proposed scheme is also validated using real data generated from experiments. INDEX TERMS Adaptive exploration harmony search, electrochemical model, lithium-ion battery, meta-heuristic algorithm, parameter estimation, parameter identifiability.