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Road tunnels are enclosed spaces that most occupants only experience while driving through them. In case of fire, however, occupants potentially need to evacuate on foot from a dangerous and unfamiliar environment. Clear and accurate guidance is important for an efficient and safe evacuation from tunnels. Common cues for evacuation guidance are a signage and audio messages that attract occupants to move on appropriate egress routes and avoid unsafe routes. This paper investigates how different types of visual and auditory signals influence occupants’ exit choices in a simulated tunnel evacuation. Common guidance cues were presented to participants in a mobile Head Mounted Display, and they were asked to choose between two possible exit doors in a simulated road tunnel. Two attracting cues (‘‘EXIT’’ signs, audio instructions), and two detracting cues (‘‘DO NOT ENTER’’ signs; traffic cones placed in front of an exit) were studied in three virtual reality (VR) experiments. In each experiment, the presence and direction of the cues were manipulated, and data from 20 participants were collected. Experiment 1 explored the effects of attracting cues, Experiment 2 detracting cues, and Experiment 3 the combination of attracting and detracting cues. Across all studies, participants tended to follow the guidance provided when there was only one cue. When several competing and even contradictory cues were present, participants were most likely to rely on audio instructions, followed by traffic cones and ‘‘DO NOT ENTER’’ signs, whereas ‘‘EXIT’’ signs were often disregarded. We conclude that participants tend to follow temporary cues that could carry current information, as opposed to permanently installed signage. Some corresponding suggestions are put forward on evacuation system design and strategic planning in a tunnel fire. 

Efficient emergency guidance in buildings is essential for the safe evacuation of occupants. However, occupants may be exposed to contradictory information from signage and other sources of information. This study presents a set of forced-choice VR experiments and a machine learning approach to investigate the effect of competing or conflicting guidance on exit choice in simulated scenarios. In the VR study, participants chose between two potential exits under time pressure in each trial. Attracting cues (“EXIT” signs, audio instructions) and repelling cues (“DO NOT ENTER” signs, traffic cones) were placed in front of the two exits, either individually or in combination. In total, 2,125 datapoints were recorded from 20 participants. To model exit choice, machine learning (random forest, RF) models were applied to predict and interpret the guidance on evacuation choices. The tuned-hyperparameters RF model proposed in this study showed above 75% accuracy to predict evacuation choices facing conflict cues and was superior to default RF and logistic regression models. Interestingly, repelling cues such as “DO NOT ENTER” signs had a stronger impact on exit choice than attracting cues like “EXIT” signs when people have to make choices. Overall, the study offers valuable data and insights into exit choices, revealing that negative cues are more influential than positive ones in emergencies. These findings can significantly inform the design and optimization of egress guidance systems. This bias towards negative information under pressure suggests that evacuation systems should prioritize clear and prominent negative cues to guide occupants effectively. 

Aqueous Li-ion batteries (ALIBs) are an important class of battery chemistries owing to the intrinsic non-flammability of aqueous electrolytes. However, water is detrimental to most cathode materials and could result in rapid cell failure. Identifying the degradation mechanisms and evaluating the pros and cons of different cathode materials are crucial to guide the materials selection and maximize their electrochemical performance in ALIBs. In this study, we investigate the stability of LiFePO₄(LFP), LiMn₂O₄(LMO) and LiNi_0.8Mn_0.1Co_0.1O₂(NMC) cathodes, without protective coating, in three different aqueous electrolytes, i.e., salt-in-water, water-in-salt, and molecular crowding electrolytes. The latter two are the widely reported “water-deficient electrolytes.” LFP cycled in the molecular crowding electrolyte exhibits the best cycle life in both symmetric and full cells owing to the stable crystal structure. Mn dissolution and surface reduction accelerate the capacity decay of LMO in water-rich electrolyte. On the other hand, the bulk structural collapse leads to the degradation of NMC cathodes. LMO demonstrates better full-cell performance than NMC in water-deficient aqueous electrolytes. LFP is shown to be more promising than LMO and NMC for long-cycle-life ALIB full cells, especially in the molecular crowding electrolyte. However, none of the aqueous electrolytes studied here provide enough battery performance that can compete with conventional non-aqueous electrolytes. This work reveals the degradation mechanisms of olivine, spinel, and layered cathodes in different aqueous electrolytes and yields insights into improving electrode materials and electrolytes for ALIBs. 

Abstract Two-dimensional (2D) materials have drawn immense interests in scientific and technological communities, owing to their extraordinary properties and their tunability by gating, proximity, strain and external fields. For electronic applications, an ideal 2D material would have high mobility, air stability, sizable band gap, and be compatible with large scale synthesis. Here we demonstrate air stable field effect transistors using atomically thin few-layer PdSe₂sheets that are sandwiched between hexagonal BN (hBN), with large saturation current > 350 μA/μm, and high field effect mobilities of ~ 700 and 10,000 cm²/Vs at 300 K and 2 K, respectively. At low temperatures, magnetotransport studies reveal unique octets in quantum oscillations that persist at all densities, arising from 2-fold spin and 4-fold valley degeneracies, which can be broken by in-plane and out-of-plane magnetic fields toward quantum Hall spin and orbital ferromagnetism. 

The diffusion layer created by transition metal (TM) dissolution is ubiquitous at the electrochemical solid-liquid interface and plays a key role in determining electrochemical performance. Tracking the spatiotemporal dynamics of the diffusion layer has remained an unresolved challenge. With spatially resolved synchrotron X-ray fluorescence microscopy and micro-X-ray absorption spectroscopy, we demonstrate the in situ visualization and chemical identification of the dynamic diffusion layer near the electrode surface under electrochemical operating conditions. Our method allows for direct mapping of the reactive electrochemical interface and provides insights into engineering the diffusion layer for improving electrochemical performance.