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Efficient visual data processing by neuromorphic networks requires volatile artificial synapses that detect and process light inputs, ideally in the same device. Here, we demonstrate microscale back-contacted optoelectronic halide…
Typical mammal brains have some form of random connectivity between neurons. Reservoir computing, a neural network approach, uses random weights within its processing layer along with built-in recurrent connections and short-term, fading…
Metal halide perovskite-based materials have emerged over the past few decades as remarkable solution-processable opto-electronic materials with many intriguing properties and potential applications. These emerging materials have recently…
Next-generation low-cost semiconductors such as halide perovskites exhibit optoelectronic properties dominated by nanoscale variations in their structure, composition and photophysics. While microscopy provides a proxy for ultimate device…
Photonic neuromorphic computing may offer promising applications for a broad range of photonic sensors, including optical fiber sensors, to enhance their functionality while avoiding loss of information, energy consumption, and latency due…
Hardware neural networks could perform certain computational tasks orders of magnitude more energy-efficiently than conventional computers. Artificial neurons are a key component of these networks and are currently implemented with…
In optoelectronic applications, metal halide perovskites (MHPs) are compelling materials because of their highly tuneable and intensely competitive optical properties. Colloidal synthesis enables the controlled formation of various…
Perovskite photovoltaic technologies are approaching commercial deployment, yet single junction and tandem architectures both still have significant room to improve power conversion efficiency and stability. The ability to perform rapid…
The fields of machine learning and artificial intelligence drive researchers to explore energy-efficient, brain-inspired new hardware. Reservoir computing encompasses recurrent neural networks for sequential data processing and matches the…
Metal halide perovskite (MHP) optoelectronics may become a viable alternative to standard Si-based technologies, but the current lack of long-term stability precludes their commercial adoption. Exposure to standard operational stressors…
The great tunability of the properties of halide perovskites presents new opportunities for optoelectronic applications as well as significant challenges associated with exploring combinatorial chemical spaces. In this work, we develop a…
Optical neuromorphic computing offers a promising route to high speed, energy efficient information processing. However, photonic neurons, as the critical components for enhancing computational expressivity, still face significant…
Nowadays we witness a miniaturisation trend in the semiconductor industry backed up by groundbreaking discoveries and designs in nanoscale characterisation and fabrication. To facilitate the trend and produce ever smaller, faster and…
Novel halide perovskites with improved stability and optoelectronic properties can be designed via composition engineering at cation and/or anion sites. Data-driven methods, especially high-throughput first principles computations and…
Analog computing using non-volatile memristors has emerged as a promising solution for energy-efficient deep learning. New materials, like perovskites-based memristors are recently attractive due to their cost-effectiveness, energy…
Metal halide perovskites (MHPs) have had a profound impact on numerous emerging optoelectronic technologies, achieving performance metrics that rival or exceed incumbent materials. This impact is underpinned by the exceptional properties of…
Controlling size and shape of semiconducting nanocrystals advances nanoelectronics and photonics. Quantum confined, inexpensive, solution derived metal halide perovskites offer narrow band, color-pure emitters as integral parts of…
Cesium based halide perovskites, such as CsPbI3 and CsSnI3, have emerged as exceptional candidates for next generation photovoltaic and optoelectronic technologies, but their practical application is limited by temperature dependent phase…
Halide perovskites is a family of semiconductor materials demonstrating prospective properties for optical cooling owing to efficient luminescence at room temperature and strong electron-phonon interaction. On the other hand, perovskite…
The transition to smart wearable and flexible optoelectronic devices communicating with each other and performing neuromorphic computing at the edge is a big goal in next-generation optoelectronics. These devices should perform their…