Large-scale transcriptome analysis in chickpea (Cicer arietinum L.), an orphan legume crop of the semi-arid tropics of Asia and Africa

Chickpea (Cicer arietinum L.) is an important legume crop in the semi-arid regions of Asia and Africa. Gains in crop productivity have been low however, particularly because of biotic and abiotic stresses. To help enhance crop productivity using molecular breeding techniques, next generation sequencing technologies such as Roche/454 and Illumina/Solexa were used to determine the sequence of most gene transcripts and to identify drought-responsive genes and gene-based molecular markers. A total of 103 215 tentative unique sequences (TUSs) have been produced from 435 018 Roche/454 reads and 21 491 Sanger expressed sequence tags (ESTs). Putative functions were determined for 49 437 (47.8%) of the TUSs, and gene ontology assignments were determined for 20 634 (41.7%) of the TUSs. Comparison of the chickpea TUSs with the Medicago truncatula genome assembly (Mt 3.5.1 build) resulted in 42 141 aligned TUSs with putative gene structures (including 39 281 predicted intron/splice junctions). Alignment of ∼37 million Illumina/Solexa tags generated from drought-challenged root tissues of two chickpea genotypes against the TUSs identified 44 639 differentially expressed TUSs. The TUSs were also used to identify a diverse set of markers, including 728 simple sequence repeats (SSRs), 495 single nucleotide polymorphisms (SNPs), 387 conserved orthologous sequence (COS) markers, and 2088 intron-spanning region (ISR) markers. This resource will be useful for basic and applied research for genome analysis and crop improvement in chickpea

Demonstration of versatile nonvolatile logic gates in 28nm HKMG FeFET technology

Logic-in-memory circuits promise to overcome the von-Neumann bottleneck, which constitutes one of the limiting factors to data throughput and power consumption of electronic devices. In the following we present four-input logic gates based on only two ferroelectric FETs (FeFETs) with hafnium oxide as the ferroelectric material. By utilizing two complementary inputs, a XOR and a XNOR gate are created. The use of only two FeFETs results in a compact and nonvolatile design. This realization, moreover, directly couples the memory and logic function of the FeFET. The feasibility of the proposed structures is revealed by electrical measurements of HKMG FeFET memory arrays manufactured in 28nm technology

Junction tuning by ferroelectric switching in silicon nanowire Schottky-barrier field effect transistors

We report on a novel silicon nanowire-based field effect transistor with integrated ferroelectric gate oxide. The concept allows tuning the carrier transport in a non-volatile approach by switching the polarization in the ferroelectric layer close to the source Schottky-junction. We interpret the results in terms of tuning the transmissibility of the Schottky-junction for charge carriers. The experimental results provide a first step towards the integration of memory-in-logic concepts with reconfigurable nanowire transistors

Variants of Ferroelectric Hafnium Oxide based Nonvolatile Memories

Ferroelectricity is very attractive for nonvolatile memories since it allows non-volatility paired with a field driven switching mechanism enabling a very low-power write operation. Non-volatile memories based on ferroelectric lead-zirconium-titanate (PZT) (see fig. la) are available on the market for more than a quarter of a century now [1]. Yet they are limited to niche applications due to the compatibility issues of the ferroelectric material with CMOS processes and the associated limited scalability [2]. The discovery of ferroelectricity in doped hafnium oxide has revived the activities towards a variety of scalable ferroelectric nonvolatile memory device

Novel ferroelectric FET based synapse for neuromorphic systems

A compact nanoscale device emulating the functionality of biological synapses is an essential element for neuromorphic systems. Here we present for the first time a synapse based on a single ferroelectric FET (FeFET) integrated in a 28nm HKMG technology, having hafnium oxide as the ferroelectric and a resistive element in series. The gradual and non-volatile ferroelectric switching is exploited to mimic the synaptic weight. We demonstrate both the spike-timing dependent plasticity (STDP) and the signal transmission and discuss the effect of the spike properties and circuit design on STDP

Next generation ferroelectric materials for semiconductor process integration and their applications

Ferroelectrics are a class of materials that possess a variety of interactions between electrical, mechanical, and thermal properties that have enabled a wealth of functionalities. To realize integrated systems, the integration of these functionalities into semiconductor processes is necessary. To this end, the complexity of well-known ferroelectric materials, e.g., the perovskite class, causes severe issues that limit its applications in integrated systems. The discovery of ferroelectricity in hafnium oxide-based materials brought a renewed interest into this field during the last decade. Very recently, ferroelectricity was also verified in aluminum scandium nitride extending the potential of seeing a wealth of ferroelectric functions in integrated electronics in the future. This paper discusses the prospects of both material systems in various applications. © 2021 Author(s).N

Physical and circuit modeling of HfO2 based ferroelectric memories and devices

The discovery of ferroelectric properties in polycrystalline HfO2 has revived the interest in ferroelectric (FE) memories, which shows scaling feasibility allowing targeting high-density storage applications. In order to provide engineering guidelines for FE memory devices it is crucial to establish a correlation between the electrical device performances and the underlying physical mechanisms. In this work, we will discuss physical and circuit modeling approaches for FE memories connecting the FE HfO2 materials properties to the electrical performances of memory cells, artificial synapse for neuromorphic and in memory computing applications