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Abstract Since the first isolation of graphene, the importance of van der Waals (vdW) interactions has become increasingly recognized in the burgeoning field of layered materials. In this work, infrared nanoimaging techniques and theoretical modeling are used to unravel the critical role played by interfacial vdW interactions in governing the stability of violet phosphorus (VP)—a recently rediscovered wide bandgap p‐type semiconductor—when exfoliated on different substrates. It is demonstrated that vdW interactions with the underlying substrate can have a profound influence on the stability of exfoliated VP flakes and investigate how these interactions are affected by flake thickness, substrate properties (e.g., substrate hydrophilicity, surface roughness), and the exfoliation process. These findings highlight the key role played by interfacial vdW interactions in governing the stability and physical properties of layered materials, and can be used to guide substrate selection in the preparation and study of this important class of materials.

Abstract Violet phosphorus (VP) is garnering attention for its appealing physical properties and potential applications in optoelectronics. A comprehensive investigation of the photodegradation and thermal effects of exfoliated VP on SiO2/Si substrates is presented. The degradation rate of VP is strongly influenced by the wavelength and exposure duration of light. Light illumination of VP above the bandgap leads to faster degradation, attributed to interactions with reactive oxygen species. Power‐dependent photoluminescence (PL) measurements at low temperature (T = 4 K) show neutral exciton (X0) and trion (T) intensities linearly increase with excitation power, while the energy difference between peak energies decreases. The T/X0 spectral weight ratio increases from 0.28 at 300 K to 0.69 at 4 K, suggesting enhanced T formation due to reduced phonon scattering. Temperature‐dependent Raman is used to investigate the phonon properties of VP. Tracking peak positions of 9 Raman modes with temperature, the linear first‐order temperature coefficient is obtained and found to be linear for all modes. The results provide a deeper understanding of VP's degradation behavior and implications for optoelectronic applications.

Habituation and sensitization represent nonassociative learning mechanisms in both non‐neural and neural organisms. They are essential for a range of functions from survival to adaptation in dynamic environments. Design of hardware for neuroinspired computing strives to emulate such features driven by electric bias and can also be incorporated into neural network algorithms. Herein, cellular‐like learning in oxygen‐deficient NiOx devices is demonstrated. Both habituation learning and sensitization response can be achieved in a single device by simply controlling the magnitude of the electric field. Spontaneous memory relaxations and dynamic redistribution of oxygen vacancies under electric bias enable such learning behavior of NiOx under sequential training. These characteristics in simple device arrays are implemented to learn alphabets as well as demonstrate simulated algorithmic use cases in digit recognition. Transition metal oxides with carefully prepared defect concentrations can be highly sensitive to electronic structure perturbations under moderate electrical stimulus and serve as building blocks for next‐generation neuroinspired computing hardware.