Ferroelectric tunnel junction (FTJ) has attracted considerable attention for its potential applications in nonvolatile memory and neuromorphic computing. However, the experimental exploration of FTJs with high ON/OFF ratios is a challenging task due to the vast search space comprising of ferroelectric and electrode materials, fabrication methods and conditions and so on. Here, machine learning (ML) is demonstrated to be an effective tool to guide the experimental search of FTJs with high ON/OFF ratios. A dataset consisting of 152 FTJ samples with nine features and one target attribute (i.e., ON/OFF ratio) is established for ML modeling. Among various ML models, the gradient boosting classification model achieves the highest prediction accuracy. Combining the feature importance analysis based on this model with the association rule mining, it is extracted that the utilizations of {graphene/graphite (Gra) (top), LaNiO₃ (LNO) (bottom)} and {Gra (top), Ca0.96Ce0.04MnO₃ (CCMO) (bottom)} electrode pairs are likely to result in high ON/OFF ratios in FTJs. Moreover, two previously unexplored FTJs: Gra/BaTiO₃ (BTO)/LNO and Gra/BTO/CCMO, are predicted to achieve ON/OFF ratios higher than 1000. Guided by the ML predictions, the Gra/BTO/LNO and Gra/BTO/CCMO FTJs are experimentally fabricated, which unsurprisingly exhibit ≥1000 ON/OFF ratios (∼8540 and ∼7890, respectively). This study demonstrates a new paradigm of developing high-performance FTJs by using ML.Ferroelectric tunnel junction (FTJ) has attracted considerable attention for its potential applications in nonvolatile memory and neuromorphic computing. However, the experimental exploration of FTJs with high ON/OFF ratios is a challenging task due to the vast search space comprising of ferroelectric and electrode materials, fabrication methods and conditions and so on. Here, machine learning (ML) is demonstrated to be an effective tool to guide the experimental search of FTJs with high ON/OFF ratios. A dataset consisting of 152 FTJ samples with nine features and one target attribute (i.e., ON/OFF ratio) is established for ML modeling. Among various ML models, the gradient boosting classification model achieves the highest prediction accuracy. Combining the feature importance analysis based on this model with the association rule mining, it is extracted that the utilizations of {graphene/graphite (Gra) (top), LaNiO₃ (LNO) (bottom)} and {Gra (top), Ca0.96Ce0.04MnO₃ (CCMO) (bottom)} electrode pairs are likely to result in high ON/OFF ratios in FTJs. Moreover, two previously unexplored FTJs: Gra/BaTiO₃ (BTO)/LNO and Gra/BTO/CCMO, are predicted to achieve ON/OFF ratios higher than 1000. Guided by the ML predictions, the Gra/BTO/LNO and Gra/BTO/CCMO FTJs are experimentally fabricated, which unsurprisingly exhibit ≥1000 ON/OFF ratios (∼8540 and ∼7890, respectively). This study demonstrates a new paradigm of developing high-performance FTJs by using ML.

开发高性能的近红外可视化器件在生物成像、食物检测、健康监测和环境分析等领域有着重要意义。近红外可视化器件由光探测单元和发光单元组成, 可将人眼不可视的近红外光转换为可见光。其工作机制是, 光探测单元作为发光单元的载流子注入层, 在近红外光下产生光电流, 因而被近红外光照射的区域会产生电荷注入, 在发光单元的对应区域复合发光, 发射可见光。没有近红外光照射时, 光探测单元中不产生光电流, 将抑制发光单元中的电荷注入, 因而不发光。因此, 近红外可视化器件可用于对辐射、反射或吸收近红外光的物质成像。本综述介绍了近红外可视化器件的工作原理和最新进展, 包括基于无机、有机半导体等不同材料的近红外可视化器件。研究发现, 近红外可视化器件的光子转换效率由近红外光探测单元和发光单元的光电转换效率决定。本文归纳了提高近红外可视化器件的光子-光子转换效率的方法和相关工作, 探讨和展望了近红外光的可视化技术在三维图像分析、近红外检测卡、生物成像、健康和环境监测与检测的应用前景。

从实验和理论上研究了InGaAsP多量子阱(Multi-Quantum-Well, MQW)双区共腔(Common Cavity Tandem Section, CCTS)结构半导体激光器的吸收区偏置状态对双稳态特性的影响。实验结果表明: 随着可饱和吸收区上的负偏置电压的增大, 激光器P-I曲线中双稳态特性更加明显, V-I曲线有负微分电阻, 当偏压加至-3 V时, 回滞曲线环宽度增加至13.5 mA, 开关比达到21: 1。理论分析表明, 利用吸收区的高负偏置态和短载流子逃逸时间能获得更好的双稳态特性。最大107: 1的开关比也说明双区共腔激光器能在两稳态之间实现非常明确的转换。

制备了一种以石墨烯量子点(GQDs)∶聚乙烯吡咯烷酮(PVP)混合复合材料作为有机功能层，具有氧化铟锡(ITO)/GQDs∶PVP/铝(Al)夹层结构的阻变器件。通过控制石墨烯量子点在复合体系中的浓度有效地调控阻变器件的低阻态电流与高阻态电流之间的比值(开关比)。当GQDs含量为0.6 wt%时，开关比的最大值可达1.2×104。在室温下对该最优器件进行电流-电压(I-V)特性分析，结果表明，该器件具有高效的阻变特性，可实现 “写入-擦除”操作。对该I-V特性曲线进行拟合，发现器件在不同偏压下的载流子输运机制主要由热电子发射机制、空间电荷限制电流输运机制以及欧姆传导机制共同决定。基于这些导电机制并结合GQDs∶PVP复合材料的能带结构，讨论了GQDs∶PVP复合薄膜中的载流子捕获机制和释放机制；同时，也详细分析了载流子在该器件的捕获释放过程及引发的阻变行为。

本文报道在InP:Fe中皮秒二波耦合的实验研究.文中测量了瞬态二波耦合增益随泵浦光与探测光相对延迟时间改变而变化的曲线,分析了瞬态二波耦合中各种过程的特性,最后还利用皮秒二波耦合实现了低开启光强、高信噪比,透过率达17%的皮秒光开关.