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Curiosity shapes spatial exploration and cognitive map formation in humans

Cognitive maps are thought to arise, at least in part, from our intrinsic curiosity to explore unknown places. However, it remains untested how curiosity shapes aspects of spatial exploration in humans. Combining a virtual reality task with indices of exploration complexity, we found that pre-exploration curiosity states predicted how much individuals spatially explored environments, whereas markers of visual exploration determined post-exploration feelings of interest. Moreover, individual differences in curiosity traits, particularly Stress Tolerance, modulated the relationship between curiosity and spatial exploration, suggesting the capacity to cope with uncertainty enhances the curiosity-exploration link. Furthermore, both curiosity and spatial exploration predicted how precisely participants could recall spatial-relational details of the environment, as measured by a sketch map task. These results provide new evidence for a link between curiosity and exploratory behaviour, and how curiosity might shape cognitive map formation.

Recent advances in high-entropy superconductors

High-entropy materials (HEMs) exhibit significant potential for diverse applications owing to their tunable properties, which can be precisely engineered through the selection of specific elements and the modification of stoichiometric ratios. The discovery of superconductivity in HEMs has garnered considerable interest, leading to accelerated advancements in this field in recent years. This review provides an overview of various high-entropy superconductors, highlighting their distinct features, such as disordered crystal structure, factors affecting the critical temperature (Tc), unconventional superconductivity, and topological bands. A perspective on this field is subsequently proposed, drawing upon insights from recently published academic literature. The objective is to provide researchers with a comprehensive and clear understanding of the newly developed high-entropy superconductivity, thereby catalyzing further advancements in this domain.

First-principles and machine-learning approaches for interpreting and predicting the properties of MXenes

MXenes are a versatile family of 2D inorganic materials with applications in energy storage, shielding, sensing, and catalysis. This review highlights computational studies using density functional theory and machine-learning approaches to explore their structure (stacking, functionalization, doping), properties (electronic, mechanical, magnetic), and application potential. Key advances and challenges are critically examined, offering insights into applying computational research to transition these materials from the lab to practical use.

Iterative printing of bulk metal and polymer for additive manufacturing of multi-layer electronic circuits

In pursuing advancing additive manufacturing (AM) techniques for 3D objects, this study combines AM techniques for bulk metal and polymer on a single platform for one-stop printing of multilayer 3D electronic circuits with two novel aspects. The first innovation involves the embedded integration of electronic circuits by printing low-resistance electrical traces from bulk metal into polymer channels. Cross-section grinding results reveal (92 ± 5)% occupancy of electrically conductive traces in polymer channels despite the different thermal properties of the two materials. The second aspect encompasses the possibility of printing vertical bulk metal vias up to 10 mm in height with the potential for expansion, interconnecting electrically conductive traces embedded in different layers of the 3D object. The work provides comprehensive 3D printing design guidelines for successfully integrating fully embedded electrically conductive traces and the interconnecting vertical bulk metal vias. A smooth and continuous workflow is also introduced, enabling a single-run print of functional multilayer embedded 3D electronics. The design rules and the workflow facilitate the iterative printing of two distinct materials, each defined by unique printing temperatures and techniques. Observations indicate that conductive traces using molten metal microdroplets show a 12-fold reduction in resistance compared to nanoparticle ink-based methods, meaning this technique greatly complements multi-material additive manufacturing (MM-AM). The work presents insights into the behavior of molten metal microdroplets on a polymer substrate when printed through the MM-AM process. It explores their characteristics in two scenarios: When they are deposited side-by-side to form conductive traces and when they are deposited out-of-plane to create vertical bulk metal vias. The innovative application of MM-AM to produce multilayer embedded 3D electronics with bulk metal and polymer demonstrates significant potential for realizing the fabrication of free-form 3D electronics.

Flash Joule heating for synthesis, upcycling and remediation

Electric heating methods are being developed and used to electrify industrial applications and lower their carbon emissions. Direct Joule resistive heating is an energy-efficient electric heating technique that has been widely tested at the bench scale and could replace some energy-intensive and carbon-intensive processes. In this Review, we discuss the use of flash Joule heating (FJH) in processes that are traditionally energy-intensive or carbon-intensive. FJH uses pulse current discharge to rapidly heat materials directly to a desired temperature; it has high-temperature capabilities (>3,000 °C), fast heating and cooling rates (>102 °C s−1), short duration (milliseconds to seconds) and high energy efficiency (~100%). Carbon materials and metastable inorganic materials can be synthesized using FJH from virgin materials and waste feedstocks. FJH is also applied in resource recovery (such as from e-waste) and waste upcycling. An emerging application is in environmental remediation, where FJH can be used to rapidly degrade perfluoroalkyl and polyfluoroalkyl substances and to remove or immobilize heavy metals in soil and solid wastes. Life-cycle and technoeconomic analyses suggest that FJH can reduce energy consumption and carbon emissions and be cost-efficient compared with existing methods. Bringing FJH to industrially relevant scales requires further equipment and engineering development.

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