卤化物
钙钛矿(结构)
材料科学
纳米技术
工程物理
化学工程
无机化学
化学
物理
工程类
作者
Dominik Kowal,Somnath Mahato,Michał Makowski,Sri Hartati,Md Abdul Kuddus Sheikh,Wenzheng Ye,Dennis R. Schaart,Joanna Cybińska,Liang Jie Wong,Arramel Arramel,Muhammad Danang Birowosuto
摘要
Nuclear energy emerges as a promising and environmentally friendly solution to counter the escalating levels of greenhouse gases resulting from excessive fossil fuel usage. Essential to harnessing this energy are nuclear batteries, devices designed to generate electric power by capturing the energy emitted during nuclear decay, including α or β particles and γ radiation. The allure of nuclear batteries lies in their potential for extended lifespan, high energy density, and adaptability in harsh environments where refueling or battery replacement may not be feasible. In this review, we narrow our focus to nuclear batteries utilizing non-thermal converters such as α- or β-voltaics, as well as those employing scintillation intermediates. Recent advancements in state-of-the-art direct radiation detectors and scintillators based on metal perovskite halides (MPHs) and chalcogenides (MCs) are compared to traditional detectors based on silicon and III-V materials, and scintillators based on inorganic lanthanide crystals. Notable achievements in MPH and MC detectors and scintillators, such as nano-Gy sensitivity, 100 photons/keV light yield, and radiation hardness, are highlighted. Additionally, limitations including energy conversion efficiency, power density, and shelf-life due to radiation damage in detectors and scintillators are discussed. Leveraging novel MPH and MC materials has the potential to propel nuclear batteries from their current size and power limitations to miniaturization, heightened efficiency, and increased power density. Furthermore, exploring niche applications for nuclear batteries beyond wireless sensors, low-power electronics, oil well monitoring, and medical fields presents enticing opportunities for future research and development.
科研通智能强力驱动
Strongly Powered by AbleSci AI