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.

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To expand the unchartered materials space of lead‐free ferroelectrics for smart digital technologies, tuning their compositional complexity via multicomponent alloying allows access to enhanced polar properties. The role of isovalent A‐site in binary potassium niobate alloys, (K,A)NbO3 using first‐principles calculations is investigated. Specifically, various alloy compositions of (K,A)NbO3 are considered and their mixing thermodynamics and associated polar properties are examined. To establish structure‐property design rules for high‐performance ferroelectrics, the sure independence screening sparsifying operator (SISSO) method is employed to extract key features to explain the A‐site driven polarization in (K,A)NbO3. Using a new metric of agreement via feature‐assisted regression and classification, the SISSO model is further extended to predict A‐site driven polarization in multicomponent systems as a function of alloy composition, reducing the prediction errors to less than 1%. With the machine learning model outlined in this work, a polarity‐composition map is established to aid the development of new multicomponent lead‐free polar oxides which can offer up to 25% boosting in A‐site driven polarization and achieving more than 150% of the total polarization in pristine KNbO3. This study offers a design‐based rational route to develop lead‐free multicomponent ferroelectric oxides for niche information technologies.

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To meet the increasing demand for environment-friendly, high-performance energy devices, sodium niobate (\ce{NaNbO3}) is considered one of the most promising lead-free antiferroelectric (AFE) oxide perovskites for such green energy storage...