Transport properties of resistive switching in Ag/Pr0.6Ca0.4MnO3/Al thin film structures

Lähteenlahti, Ville; Schulman, Alejandro; Huhtinen, H.; Paturi, P.

doi:10.1016/j.jallcom.2019.01.279

Cited by 16 publications

(13 citation statements)

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“…The circuit can be used in the positive polarity, where the PF-based conduction dominates. A similar peak shape has also been seen in other perovskite compounds, such as PCMO and LSCO …”

Section: Resultssupporting

confidence: 78%

“…These compounds are versatile for RS applications since as the concentration of divalent A cations x changes, the compounds go through significant changes in the RS properties. Manganite-based RS devices have been shown to possess good device-to-device variability, forming-less operation, and well-controlled analogue resistance states, all of which are beneficial in building neuromorphic circuits …”

Section: Introductionmentioning

confidence: 99%

“…The most commonly studied manganite compound is Pr 1– x Ca x MnO 3 (PCMO) with x = 0.3, which has been proven suitable for both memory and neuromorphic applications with well-performing single devices and large-scale crossbar arrays integrated into existing semiconductor technology. ,,,,− Other members of the mixed-valence manganite family, such as La 1– x Ca x MnO 3 and La 1– x Sr x MnO 3 (LSMO), share a similar RS mechanism but have distinct RS characteristics which vary over the calcium substitution range. Currently, many of the possible cation combinations remain unexplored, and the optimal manganite material for neuromorphic applications remains undecided.…”

Section: Introductionmentioning

confidence: 99%

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Electron Doping Effect in the Resistive Switching Properties of Al/Gd_1–xCa_xMnO₃/Au Memristor Devices

Lähteenlahti

Schulman

Beiranvand

et al. 2021

ACS Appl. Mater. Interfaces

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We report on the resistive switching (RS) properties of Al/Gd 1– x Ca x MnO 3 (GCMO)/Au thin-film memristors. The devices were studied over the whole calcium substitution range x as a function of electrical field and temperature. The RS properties were found to be highly dependent on the Ca substitution. The optimal concentration was determined to be near x = 0.9, which is higher than the values reported for other similar manganite-based devices. We utilize an equivalent circuit model which accounts for the obtained results and allows us to determine that the electrical conduction properties of the devices are dominated by the Poole–Frenkel conduction mechanism for all compositions. The model also shows that lower trap energy values are associated with better RS properties. Our results indicate that the main RS properties of Al/GCMO/Au devices are comparable to those of other similar manganite-based materials, but there are marked differences in the switching behavior, which encourage further exploration of mixed-valence perovskite manganites for RS applications.

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“…The circuit can be used in the positive polarity, where the PF-based conduction dominates. A similar peak shape has also been seen in other perovskite compounds, such as PCMO and LSCO …”

Section: Resultssupporting

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Electron Doping Effect in the Resistive Switching Properties of Al/Gd_1–xCa_xMnO₃/Au Memristor Devices

Lähteenlahti

Schulman

Beiranvand

et al. 2021

ACS Appl. Mater. Interfaces

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show abstract

“…Specifically, resistive exchanging and synaptic properties of gallium-doped ZnO slender movies were explored. The bipolar resistive exchanging with a simple memory like conduct was seen in the created memristive gadgets [10]. Few contributions in liteartures shows that, great synaptic properties, perseverance, and maintenance attributes were watched for 0.5% Ga doped memristive gadget.…”

Section: Com/brain-for-machines-ede15d1f24c1mentioning

confidence: 99%

Comprehensive Evaluation of Neuromorphic Computing

2019

International Journal of Innovative Research in Electronics and

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Due to technological advancements in the field computing and networking as well, neuromorphic computing has been evolving more and more fast. Advance technologies such as neural and peripheral nerves in human body are growing explosively. If this trend goes on the computing networks congestion will increase and it would be difficult to supply large services to the needy patients. To go on with the flow without any traffic problems neuromorphic computing is the best solution. This paper aims to discuss evaluate address the methods to assess various neuromorphic computing system. Here authors are discussing resistive switching and its properties, gallium doped ZnO and behaviour of memristive resistors which are playing crucial role in neuromorphic computing. It's an attempt to address the new systems and their role as well as various issues associated with it which are contributing the computing domain.

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“…As opposed to the longstanding notion of ordered crystals usually perform better than their disordered counterparts, it is now understood that chemically 'messy' or alloyed perovskite oxides indeed perform exceptionally better in numerous applications. These include ferroelectric photovoltaics 2 , electrocatalysts and photocatalysts 3 , tunable microwave ferroelectrics with shiftable Curie point 4 , solid oxide fuel cells 5,6 and resistive switching memories that are promising to be tailored as memristors and neuromorphic circuit components 7,8 . Thus, perovskite oxides emanate as an imperative class of materials in their own right and carefully engineered disorder can potentially burnish their properties beyond theoretical limits.…”

Section: Introductionmentioning

confidence: 99%

Analogical discovery of disordered perovskite oxides by crystal structure information hidden in unsupervised material fingerprints

Ihalage

Hao

2021

npj Comput Mater

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Compositional disorder induces myriad captivating phenomena in perovskites. Target-driven discovery of perovskite solid solutions has been a great challenge due to the analytical complexity introduced by disorder. Here, we demonstrate that an unsupervised deep learning strategy can find fingerprints of disordered materials that embed perovskite formability and underlying crystal structure information by learning only from the chemical composition, manifested in $$({{\rm{A}}}_{1-{\rm{x}}}{{\rm{A}}^{\prime} }_{{\rm{x}}}){{\rm{BO}}}_{3}$$ ( A 1 − x A ′ x ) BO 3 and $${\rm{A}}({{\rm{B}}}_{1-{\rm{x}}}{{\rm{B}}^{\prime} }_{{\rm{x}}}){{\rm{O}}}_{3}$$ A ( B 1 − x B ′ x ) O 3 formulae. This phenomenon can be capitalized to predict the crystal symmetry of experimental compositions, outperforming several supervised machine learning (ML) algorithms. The educated nature of material fingerprints has led to the conception of analogical materials discovery that facilitates inverse exploration of promising perovskites based on similarity investigation with known materials. The search space of unstudied perovskites is screened from ~600,000 feasible compounds using experimental data powered ML models and automated web mining tools at a 94% success rate. This concept further provides insights on possible phase transitions and computational modelling of complex compositions. The proposed quantitative analysis of materials analogies is expected to bridge the gap between the existing materials literature and the undiscovered terrain.

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Transport properties of resistive switching in Ag/Pr0.6Ca0.4MnO3/Al thin film structures

Cited by 16 publications

References 50 publications

Electron Doping Effect in the Resistive Switching Properties of Al/Gd_1–xCa_xMnO₃/Au Memristor Devices

Electron Doping Effect in the Resistive Switching Properties of Al/Gd_1–xCa_xMnO₃/Au Memristor Devices

Comprehensive Evaluation of Neuromorphic Computing

Analogical discovery of disordered perovskite oxides by crystal structure information hidden in unsupervised material fingerprints

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Transport properties of resistive switching in Ag/Pr0.6Ca0.4MnO3/Al thin film structures

Cited by 16 publications

References 50 publications

Electron Doping Effect in the Resistive Switching Properties of Al/Gd1–xCaxMnO3/Au Memristor Devices

Electron Doping Effect in the Resistive Switching Properties of Al/Gd1–xCaxMnO3/Au Memristor Devices

Comprehensive Evaluation of Neuromorphic Computing

Analogical discovery of disordered perovskite oxides by crystal structure information hidden in unsupervised material fingerprints

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Product

Resources

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Electron Doping Effect in the Resistive Switching Properties of Al/Gd_1–xCa_xMnO₃/Au Memristor Devices

Electron Doping Effect in the Resistive Switching Properties of Al/Gd_1–xCa_xMnO₃/Au Memristor Devices