Ultrafast Phase-Change for Data Storage Applications

Ph.DDOCTOR OF PHILOSOPH

Tailoring transient-amorphous states: towards fast and power-efficient phase-change memory and neuromorphic computing.

A new methodology for manipulating transient-amorphous states of phase-change memory (PCM) materials is reported as a viable means to boost the speed, yet reduce the power consumption of PC memories, and is applicable to new forms of PCM-based neuromorphic devices. Controlling multiple-pulse interactions with PC materials may provide an opportunity toward developing a new paradigm for ultra-fast neuromorphic computing.We acknowledge financial support from the Engineering and Physical Sciences Research Council (UK).This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/adma.20140269

Ultrasensitive Detection of MCF-7 Cells with a Carbon Nanotube-Based Optoelectronic-Pulse Sensor Framework

Biosensors are of vital significance for healthcare by supporting the management of infectious diseases for preventing pandemics and the diagnosis of life-threatening conditions such as cancer. However, the advancement of the field can be limited by low sensing accuracy. Here, we altered the bioelectrical signatures of the cells using carbon nanotubes (CNTs) via structural loosening effects. Using an alternating current (AC) pulse under light irradiation, we developed a photo-assisted AC pulse sensor based on CNTs to differentiate between healthy breast epithelial cells (MCF-10A) and luminal breast cancer cells (MCF-7) within a heterogeneous cell population. We observed a previously undemonstrated increase in current contrast for MCF-7 cells with CNTs compared to MCF-10A cells with CNTs under light exposure. Moreover, we obtained a detection limit of ∼1.5 × 10^{3} cells below a baseline of ∼1 × 10^{4} cells for existing electrical-based sensors for an adherent, heterogeneous cell population. All-atom molecular dynamics (MD) simulations reveal that interactions between the embedded CNT and cancer cell membranes result in a less rigid lipid bilayer structure, which can facilitate CNT translocation for enhancing current. This as-yet unconsidered cancer cell-specific method based on the unique optoelectrical properties of CNTs represents a strategy for unlocking the detection of a small population of cancer cells and provides a promising route for the early diagnosis, monitoring, and staging of cancer

Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia ®; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-κB localization and IκB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-κB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-κB and degradation of IκB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-κB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes

Data for Ab Initio Molecular-Dynamics Simulation of Neuromorphic Computing in Phase-Change Memory Materials

Raw data to accompany the article Ab Initio Molecular-Dynamics Simulation of Neuromorphic Computing in Phase-Change Memory Materials

Ab Initio Molecular-Dynamics Simulation of Neuromorphic Computing in Phase-Change Memory Materials

We present an in silico study of the neuromorphic-computing behavior of the prototypical phase-change material, Ge2Sb2Te5, using ab initio molecular-dynamics simulations. Stepwise changes in structural order in response to temperature pulses of varying length and duration are observed, and a good reproduction of the spike-timing-dependent plasticity observed in nanoelectronic synapses is demonstrated. Short above-melting pulses lead to instantaneous loss of structural and chemical order, followed by delayed partial recovery upon structural relaxation. We also investigate the link between structural order and electrical and optical properties. These results pave the way toward a first-principles understanding of phase-change physics beyond binary switching.</p

Data for Ab Initio Molecular-Dynamics Simulation of Neuromorphic Computing in Phase-Change Memory Materials

Raw data to accompany the article Ab Initio Molecular-Dynamics Simulation of Neuromorphic Computing in Phase-Change Memory Materials

Nonvolatile Memristive Materials and Physical Modeling for In‐Memory and In‐Sensor Computing

Publication status: PublishedSeparate memory and processing units are utilized in conventional von Neumann computational architectures. However, regarding the energy and the time, it is costly to shuffle data between the memory and the processing entity, and for data‐intensive applications associated with artificial intelligence, the demand is ever increasing. A paradigm shift in traditional architectures is required, and in‐memory computing is one of the non‐von‐Neumann computing strategies. By harnessing physical signatures of the memory, computing workloads are administered in the same memory element. For in‐memory computing, a wide range of memristive material (MM) systems have been examined. Moreover, developing computing schemes that perform in the same sensory network and that minimize the data shuffle between the processing unit and the sensing element is a requirement, to process large volumes of data efficiently and decrease the energy consumption. In this review, an overview of the switching character and system signature harnessed in three archetypal MM systems is rendered, along with an integrated application survey for developing in‐sensor and in‐memory computing, viz., brain‐inspired or analogue computing, physical unclonable functions, and random number generators. The recent progress in theoretical studies that reveal the structural origin of the fast‐switching ability of the MM system is further summarized.</jats:p

Biological-Templating of a Segregating Binary Alloy for Nanowire-Like Phase-Change Materials and Memory

One of the best strategies for achieving faster computers is to mitigate the millisecond-order time delays arising from the transfer and storage of information between silicon- A nd magnetic-based memories. Segregating-binary-alloy (SBA)-type phase-change materials (PCMs), such as gallium antimonide-based systems, can store information on 10 ns time scales by using a single memory structure; however, these materials are hindered by the high consumption of energies and undergo elemental segregation around 620 K. Nanowire-like PCMs can achieve low-energy consumption but are often synthesized by vapor-liquid-solid methods above 720 K, which would cause irreversible corruption of SBA-based PCMs. Here we control the morphology, composition, and functionality of SBA-type germanium-tin oxide systems using template-driven nucleation that leverages the electrostatic-binding specificity of the M13 bacteriophage surface. A wirelike PCM was achieved, with controllable and reliable phase-changing signatures, capable of tens of nanoseconds switching times. This approach addresses some of the critical material compositional and structural constraints that currently diminish the utility of PCMs in universal memory systems

Ultrafast Nanoscale Phase-Change Memory Enabled By Single-Pulse Conditioning

We describe how the crystallization kinetics of a suite of phase-change systems can be controlled by using a single-shot treatment via “initial crystallization” effects. Ultrarapid and highly stable phase-change structures (with excellent characteristics), viz. conventional and sub-10 nm sized cells (400 ps switching and 368 K for 10 year data retention), stackable cells (900 ps switching and 1 × 10⁶ cycles for similar “switching-on” voltages), and multilevel configurations (800 ps switching and resistance-drift power-law coefficients <0.11) have been demonstrated. Material measurements and thermal calculations also reveal the origin of the pretreatment-assisted increase in crystallization rates and the thermal diffusion in chalcogenide structures, respectively