RESUMO
The conversion of CO2 into liquid fuels, using only sunlight and water, offers a promising path to carbon neutrality. An outstanding challenge is to achieve high efficiency and product selectivity. Here, we introduce a wireless photocatalytic architecture for conversion of CO2 and water into methanol and oxygen. The catalytic material consists of semiconducting nanowires decorated with core-shell nanoparticles, with a copper-rhodium core and a chromium oxide shell. The Rh/CrOOH interface provides a unidirectional channel for proton reduction, enabling hydrogen spillover at the core-shell interface. The vectorial transfer of protons, electrons, and hydrogen atoms allows for switching the mechanism of CO2 reduction from a proton-coupled electron transfer pathway in aqueous solution to hydrogenation of CO2 with a solar-to-methanol efficiency of 0.22%. The reported findings demonstrate a highly efficient, stable, and scalable wireless system for synthesis of methanol from CO2 that could provide a viable path toward carbon neutrality and environmental sustainability.
RESUMO
Computing in the analog regime using nonlinear ferroelectric resistive memory arrays can potentially alleviate the energy constraints and complexity/footprint challenges imposed by digital von Neumann systems. Yet the current ferroelectric resistive memories suffer from either low ON/OFF ratios/imprint or limited compatibility with mainstream semiconductors. Here, for the first time, ferroelectric and analog resistive switching in an epitaxial nitride heterojunction comprising ultrathin (≈5 nm) nitride ferroelectrics, i.e., ScAlN, with potentiality to bridge the gap between performance and compatibility is demonstrated. High ON/OFF ratios (up to 105 ), high uniformity, good retention, (<20% variation after > 105 s) and cycling endurance (>104 ) are simultaneously demonstrated in a metal/oxide/nitride ferroelectric junction. It is further demonstrated that the memristor can provide programmability to enable multistate operation and linear analogue computing as well as image processing with high accuracy. Neural network simulations based on the weight update characteristics of the nitride memory yielded an image recognition accuracy of 92.9% (baseline 96.2%) on the images from Modified National Institute of Standards and Technology. The non-volatile multi-level programmability and analog computing capability provide first-hand and landmark evidence for constructing advanced memory/computing architectures based on emerging nitride ferroelectrics, and promote homo and hybrid integrated functional edge devices beyond silicon.
RESUMO
Achieving ferroelectricity in III-nitride (III-N) semiconductors by alloying with rare-earth elements, e.g., scandium, has presented a pivotal step toward next-generation electronic, acoustic, photonic, and quantum devices and systems. To date, however, the conventional growth of single-crystalline nitride semiconductors often requires the use of sapphire, Si, or SiC substrate, which has prevented their integration with the workhorse complementary metal oxide semiconductor (CMOS) technology. Herein, we demonstrate single-crystalline ferroelectric nitride semiconductors grown on CMOS compatible metal-molybdenum. Significantly, we find that a unique epitaxial relationship between wurtzite and body-centered cubic crystal structure can be well maintained, enabling the realization of single-crystalline wurtzite ferroelectric nitride semiconductors on polycrystalline molybdenum that was not previously possible. Robust and wake-up-free ferroelectricity has been measured, for the first time, in the epitaxially grown ScAlN directly on metal. We further propose and demonstrate a ferroelectric GaN/ScAlN heterostructure for synaptic memristor, which shows the capability of emulating the spike-time-dependent plasticity in a biological synapse. This work provides a viable path for the integration of III-N architectures with the mature CMOS technology and sheds light on the promising applications of ferroelectric nitride memristors in neuromorphic computing.
RESUMO
Monolithic integration of wurtzite III-nitrides with nonpolar silicon (Si), the two most-produced semiconductor materials, is essential and critical for a broad range of applications in electronics, optoelectronics, quantum photonics, and renewable energy. To date, however, it has remained challenging to achieve III-nitride heterostructures on Si with controlled lattice-polarity. Herein, we show that such critical challenges of III-nitrides on Si can be fundamentally addressed through a unique interfacial modulated lattice-polarity-controlled epitaxy (IMLPCE). It is discovered that the lattice-polarity of aluminum nitride (AlN) grown on Si(111) is primarily determined by the AlSiN interlayer: N-polar and Al-polar AlN can be achieved by suppressing and promoting the AlSiN interlayer formation, respectively. Furthermore, we develop a unique active-nitrogen-free in situ annealing process to mitigate the AlSiN layer formation at the GaN/AlN interface, which can eliminate the inverted domain formation commonly seen in N-polar GaN on AlN/Si. This study provides an alternative approach for controlling the lattice-polarity of III-nitrides on Si substrates and will enable their seamless integration with the mature Si-based device technology.