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Discover how researchers use self-rolling ferroic oxide films to revolutionize data storage. This innovative method increases storage density by up to 45 times, potentially achieving ultrahigh-density information storage of 10 Tbit per square inch, paving the way for next-gen memory technology.
Phase change memory is an emerging technology with great potential for advancing analog in-memory computing, particularly in deep neural networks and neuromorphic computing.
Organic semiconductors (OSCs) are a class of semiconductor materials consisting of conjugated molecules or polymers. Compared to inorganic semiconductors, OSCs have distinctive advantages including being solution-processable, suitable for low-cost and large-area fabrication of electronics, and applicable to flexible/stretchable electronics, among others. Given the importance of doping techniques for semiconductors, it is highly attractive to establish doping methodologies for OSCs similar to that for silicon. This would simplify the difficulty and cost of synthesizing different types of OSCs for various applications, as well as lead to interesting structures such as organic PN homojunctions.
We are in the early stages of neural computing and have time to think through the ethical issues involved. Among other things, if neural computers become common, we will grapple with tissue donation issues. Scientists have found that human neurons were faster at learning than neurons from mice. Might there also be differences in performance depending on whose neurons are used? Might Apple and Google be able to make lightning-fast computers using neurons from our best and brightest today? Would someone be able to secure tissues from deceased genius's like Albert Einstein to make specialized limited-edition neural computers?
Resistive-switching memory (RSM) is an emerging candidate for next-generation memory and computing devices, such as storage-class memory devices, multilevel memories and as a synapse in neuromorphic computing. A significant challenge in the global research efforts towards better energy technologies is efficient and accurate device modeling. Now, researchers have created a new modeling toolkit which can predict the current of a new type of memory with excellent accuracy.
The bottleneck in atomic-scale data storage area may be broken by a simple technique, thanks to recent innovative studies. Through a simple, efficient and low-cost technique involving the focused laser beam and ozone treatment, researchers can manipulate the properties of nanomaterials, thereby 'writing' information onto monolayer materials. The result is a demonstration of the thinnest light disk with rewritable data storage and encryption functionalities at the atomic level.
Researchers have developed a theory of piezoelectrics with the goal to increase coherence times in quantum computers. In new work, they elucidate the mechanism of energy absorption taking place in quantum computers, and recommends optimal materials for these devices. The new theory predicts qubit coherence times that are over 100 times greater than the current state of the art. This shows that material improvements can go a long way towards improving the quality of quantum computing devices, bringing quantum advantage one step closer.
Researchers demonstrate that dust-sized photovoltaic cells grown on silicon substrate can be heterogeneously integrated with other chiplets using a high-throughput wafer-level packaging process. The ability to integrate various nanoelectronic chiplets - such as processor, memory, and photovoltaics - in an industrial-scale wafer-level-packaging process, unlocks the potential of large-scale manufacturing of these compact integrated systems with high performance and ultralow cost.