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The fast response multipoint high-precision temperature measurement is often necessary in many dynamical measurement fields and industrial applications. However, limited by the existing electric circuit architecture, either the AC or DC bridges have the shortcoming that the rates or precisions degenerate markedly in the multi-channel scanning mode. To overcome this disadvantage, a round-robin structural low-cost ratiometric resistance thermometer readout based on several commercial 32-bit sigma-delta analogue-to-digital converters (Σ-Δ ADCs) was presented in this article. The experimental results show that the precision of this readout corresponds to 0.1 mK at 1 Hz when sampling four channel resistors simultaneously, while the precision and rate are not degenerating with the channel number increasing. In addition, the uncertainty of the readout is investigated in this article. It shows that the presented readout can achieve an uncertainty as low as 2.1 mK at 1 Hz (K = 2).

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Controlling Li ion transport in glasses at atomic and molecular levels is key to realizing all‐solid‐state batteries, a promising technology for electric vehicles. In this context, Li3PS4 glass, a promising solid electrolyte candidate, exhibits dynamic coupling between the Li+ cation mobility and the PS43− anion libration, which is commonly referred to as the paddlewheel effect. In addition, it exhibits a concerted cation diffusion effect (i.e., a cation–cation interaction), which is regarded as the essence of high Li ion transport. However, the correlation between the Li+ ions within the glass structure can only be vaguely determined, due to the limited experimental information that can be obtained. Here, this study reports that the Li ions present in glasses can be classified by evaluating their valence oscillations via Bader analysis to topologically analyze the chemical bonds. It is found that three types of Li ions are present in Li3PS4 glass, and that the more mobile Li ions (i.e., the Li3‐type ions) exhibit a characteristic correlation at relatively long distances of 4.0–5.0 Å. Furthermore, reverse Monte Carlo simulations combined with deep learning potentials that reproduce X‐ray, neutron, and electron diffraction pair distribution functions showed an increase in the number of Li3‐type ions for partially crystallized glass structures with improved Li ion transport properties. Our results show order within the disorder of the Li ion distribution in the glass by a topological analysis of their valences. Thus, considering the molecular vibrations in the glass during the evaluation of the Li ion valences is expected to lead to the development of new solid electrolytes.