Two-dimensional (2D) materials have revolutionized the field of optoelectronics by offering exceptional properties such as atomically thin structures, high carrier mobility, tunable bandgaps, and strong light–matter interactions. These attributes make them ideal candidates for next-generation photodetectors operating across a broad spectral range—from ultraviolet to mid-infrared. This review comprehensively examines the recent progress in 2D material-based photodetectors, highlighting key material classes including graphene, transition metal dichalcogenides (TMDCs), black phosphorus (BP), MXenes, chalcogenides, and carbides. We explore their photodetection mechanisms—such as photovoltaic, photoconductive, photothermoelectric, bolometric, and plasmon-enhanced effects—and discuss their impact on critical performance metrics like responsivity, detectivity, and response time. Emphasis is placed on material integration strategies, heterostructure engineering, and plasmonic enhancements that have enabled improved sensitivity and spectral tunability. The review also addresses the remaining challenges related to environmental stability, scalability, and device architecture. Finally, we outline future directions for the development of high-performance, broadband, and flexible 2D photodetectors for diverse applications in sensing, imaging, and communication technologies.

Gas sensing is essential for detecting and measuring gas concentrations across various environments, with applications in environmental monitoring, industrial safety, and healthcare. The integration of two-dimensional (2D) materials, organic materials, and metal oxides has significantly advanced gas sensor technology, enhancing its sensitivity, selectivity, and response times at room temperature. This review examines the progress in optically activated gas sensors, with emphasis on 2D materials, metal oxides, and organic materials, due to limited studies on their use in optically activated gas sensors, in contrast to other traditional gas-sensing technologies. We detail the unique properties of these materials and their impact on improving the figures of merit (FoMs) of gas sensors. Transition metal dichalcogenides (TMDCs), with their high surface-to-volume ratio and tunable band gap, show exceptional performance in gas detection, especially when activated by UV light. Graphene-based sensors also demonstrate high sensitivity and low detection limits, making them suitable for various applications. Although organic materials and hybrid structures, such as metal–organic frameworks (MoFs) and conducting polymers, face challenges related to stability and sensitivity at room temperature, they hold potential for future advancements. Optically activated gas sensors incorporating metal oxides benefit from photoactive nanomaterials and UV irradiation, further enhancing their performance. This review highlights the potential of the advanced materials in developing the next generation of gas sensors, addressing current research gaps and paving the way for future innovations.

Radiative heat transfer plays a pivotal role in many applications across various length scales, with its behavior significantly altering as systems change from the far‐field to the near‐field regime. In the far‐field, radiative heat transfer is governed by traditional laws such as Planck's and Stefan–Boltzmann's laws, which assume that the gap between objects involved in radiative exchange is larger than the thermal wavelength (λ_th), limiting the energy transfer to propagating electromagnetic waves. However, in the near‐field, where distances are smaller than the λ_th, evanescent wave coupling enables heat transfer rates that exceed the blackbody limit by several orders of magnitude. This near‐field enhancement opens new avenues for nanoscale thermal management, energy harvesting, and radiative cooling applications. This review synthesizes the key developments in radiative heat transfer theories, experimental advancements, and practical applications, spanning from early traditional studies to modern innovations leveraging fluctuational electrodynamics. Material‐specific mechanisms, such as surface phonon polaritons, and their role in enhancing radiative heat transfer are also explored while integrating machine learning techniques to optimize near‐field systems. By highlighting these mechanisms and exploring emerging research directions, this work aims to inspire new researchers to enter this dynamic field and provide a roadmap for advancing next‐generation technologies in energy efficiency and nanoscale thermal management.

Extensive research has been conducted on near-field radiative heat transfer (NFRHT) due to its wide range of applications in energy conversion, radiative cooling, and thermal diodes. The main objective of studying NFRHT at the nanoscale gap is to enhance system performance. This research proposes a new approach to designing and optimizing a near-field thermophotovoltaic (NFTPV) system using deep-learning techniques. Our study utilizes a fully connected network (FCN) and an automated-machine-learning (AutoML) model to simulate radiative heat transfer, aiming to improve radiative heat flux, power generation, and overall system efficiency. By comparing two emitter configurations, we find that the hyperbolic emitter outperforms other configurations, as evidenced by its impact on various system-performance parameters. Significant achievements have been made through our investigations. For the $\mathrm{Si}\mathrm{C}$-plate emitter configuration, we have achieved a notable power density of $0.589\mathrm{W}/{\mathrm{cm}}^2$ and an efficiency of 23% after accounting for nonradiative recombination at a temperature difference of 600 K with a 100-nm gap. Moreover, the four-period emitter configuration has yielded even more impressive results, with a power density of $0.9452\mathrm{W}/{\mathrm{cm}}^2$ and an efficiency of 30% after accounting for nonradiative recombination. This study demonstrates the immense potential of utilizing FCN and AutoML for theoretical modeling and optimization of structural parameters in NFTPV systems, as well as providing an accurate model for predicting photocurrent generation. By highlighting the capabilities of these advanced techniques, we have hopefully paved the way for further advancements and innovations in NFRHT.

Rydberg atoms are neutral atoms excited to high principal quantum number states, which endows them with exaggerated properties such as large electric dipole moments, long lifetimes, and extreme sensitivity to external electromagnetic fields. These characteristics form the foundation of Rydberg atom-based sensors, an emerging class of quantum devices capable of optically detecting electric fields across frequencies from DC to the terahertz regime. Rydberg-based electrometry operates through both Autler–Townes (AT) splitting of resonant Rydberg transitions and Stark-shift measurements for high-frequency or far-detuned fields, enabling broadband field sensing from DC to the THz regime. Using ladder-type electromagnetically induced transparency (EIT) and AT splitting, these sensors enable non-invasive, SI-traceable measurements of field amplitude, frequency, phase, and polarization. Recent developments have demonstrated broadband electric field probes, voltage calibration standards, and compact RF receivers based on thermal vapor cells and integrated photonic architectures. Furthermore, innovations in multi-photon EIT, superheterodyne readout, and multi wave mixing have expanded the dynamic range and bandwidth of Rydberg-based electrometry. Despite challenges related to environmental perturbations, linewidth broadening, and laser stabilization, ongoing advances in atomic control, hybrid photonic integration, and EIT-based readout promise scalable, chip-compatible sensors. This review summarizes the physical principles, experimental progress, and emerging applications of Rydberg atom-based sensing, emphasizing their potential for next generation quantum metrology, wireless communication, and precision field mapping.

All-inorganic halide perovskites have attracted significant interest in photodetector applications due to their remarkable photoresponse properties. However, the toxicity and instability of lead-based perovskites hinder their commercialization. In this work, we propose cubic Ba₃SbI₃ as a promising, environmentally friendly, lead-free material for next-generation photodetector applications. Ba₃SbI₃ shows good light absorption, low effective masses, and favorable elemental abundance and cost, making it a promising candidate compound for device applications. Its structural, mechanical, electronic, and optical properties were systematically investigated using density functional theory (DFT) with the Perdew–Burke–Ernzerhof (PBE) and hybrid HSE06 functionals. The material was found to be dynamically and mechanically stable, with a direct bandgap of 0.78 eV (PBE) and 1.602 eV (HSE06). Photodetector performance was then simulated in an Al/FTO/In₂S₃/Ba₃SbI₃/Sb₂S₃/Ni configuration using SCAPS-1D. To optimize device efficiency, the width, dopant level, and bulk concentration for each layer of the gadgets were systematically modified, while the effects of interface defects, operating temperature, and series and shunt resistances were also evaluated. The optimized device achieved an open-circuit voltage (Voc) of 1.047 V, short-circuit current density (Jsc) of 31.65 mA/cm², responsivity of 0.605 A W⁻¹, and detectivity of 1.05 × 10¹⁷ Jones. In contrast, in the absence of the Sb₂S₃ layer, the performance was reduced to a Voc of 0.83 V, Jsc of 26.8 mA/cm², responsivity of 0.51 A W⁻¹, and detectivity of 1.5 × 10¹⁵ Jones. These results highlight Ba₃SbI₃ as a promising platform for high-performance, cost-effective, and environmentally benign photodetectors.