Ag2S atomic switch-based 'tug of war' for decision making

A scalable solution recipe for a Ag-based neuromorphic device

Integration and scalability have posed significant problems in the advancement of brain-inspired intelligent systems. Here, we report a self-formed Ag device fabricated through a chemical dewetting process using an Ag organic precursor, which offers easy processing, scalability, and flexibility to address the above issues to a certain extent. The conditions of spin coating, precursor dilution, and use of solvents were varied to obtain different dewetted structures (broadly classified as bimodal and nearly unimodal). A microscopic study is performed to obtain insight into the dewetting mechanism. The electrical behavior of selected bimodal and nearly unimodal devices is related to the statistical analysis of their microscopic structures. A capacitance model is proposed to relate the threshold voltage (Vth) obtained electrically to the various microscopic parameters. Synaptic functionalities such as short-term potentiation (STP) and long-term potentiation (LTP) were emulated in a representative nearly unimodal and bimodal device, with the bimodal device showing a better performance. One of the cognitive behaviors, associative learning, was emulated in a bimodal device. Scalability is demonstrated by fabricating more than 1000 devices, with 96% exhibiting switching behavior. A flexible device is also fabricated, demonstrating synaptic functionalities (STP and LTP).

Low-Temperature Predicted Structures of Ag2S (Silver Sulfide)

Silver sulfide phases, such as body-centered cubic argentite and monoclinic acanthite, are widely known. Traditionally, acanthite is regarded as the only low-temperature phase of silver sulfide. However, the possible existence of other low-temperature phases of silver sulfide cannot be ruled out. Until now, there have been only a few suggestions about low-temperature Ag2S phases that differ from monoclinic acanthite. The lack of a uniform approach has hampered the prediction of such phases. In this work, the use of such an effective tool as an evolutionary algorithm for the first time made it possible to perform a broad search for the model Ag2S phases of silver sulfide, which are low-temperature with respect to cubic argentite. The possibility of forming Ag2S phases with cubic, tetragonal, orthorhombic, trigonal, monoclinic, and triclinic symmetry is considered. The calculation of the cohesion energy and the formation enthalpy show, for the first time, that the formation of low-symmetry Ag2S phases is energetically most favorable. The elastic stiffness constants cij of all predicted Ag2S phases are computed, and their mechanical stability is determined. The densities of the electronic states of the predicted Ag2S phases are calculated. The prediction of low-temperature Ag2S structures indicates the possibility of synthesizing new silver sulfide phases with improved properties.

Modeling and characterization of stochastic resistive switching in single Ag2S nanowires

Chalcogenide resistive switches (RS), such as Ag₂S, change resistance due to the growth of metallic filaments between electrodes along the electric field gradient. Therefore, they are candidates for neuromorphic and volatile memory applications. This work analyzed the RS of individual Ag₂S nanowires (NWs) and extended the basic RS model to reproduce experimental observations. The work models resistivity of the device as a percolation of the conductive filaments. It also addressed continuous fluctuations of the resistivity with a stochastic change in volume fractions of the filaments in the device. As a result, these fluctuations cause unpredictable patterns in current-voltage characteristics and include a spontaneous change in resistance of the device during the linear sweep that conventional memristor models with constant resistivity cannot represent. The parameters of the presented stochastic model of a single Ag₂S NW were fitted to the experimental data and reproduced key features of RS in the physical devices. Moreover, the model suggested a non-core shell structure of the Ag₂S NWs. The outcome of this work is aimed to aid in simulating large self-assembled memristive networks and help to extend existing RS models.

Investigation on the formation process of metal atomic filament for metal sulfide atomic switches by electrical measurement

We have studied the formation process of the metal atomic filament for metal sulfide atomic switches by electrical measurement. The switching between ON and OFF states of the atomic switch is controlled by the application of the bias voltage for the atomic switches. The SET (OFF → ON) and RESET (ON → OFF) voltages were investigated for the atomic switch where the Ag₂S or Cu₂S layer were sandwiched between the Pt and Ag or Cu electrodes. The SET and RESET voltages of the Ag/Cu₂S/Pt and Cu/Ag₂S/Pt were close to those of the Ag/Ag₂S/Pt atomic switch, and different from those of the Cu/Cu₂S/Pt atomic switch. These results indicated that the dominant chemical species of the making and breaking part of the metal filament was Ag, and that the source of the metal filament was both the sulfide layer and the metal electrode.

Ionic decision-maker created as novel, solid-state devices

Decision-making is being performed frequently in areas of computation to obtain better performance in a wide variety of current intelligent activities. In practical terms, this decision-making must adapt to dynamic changes in environmental conditions. However, because of limited computational resources, adaptive decision-making is generally difficult to achieve using conventional computers. The ionic decision-maker reported here, which uses electrochemical phenomena, has excellent dynamic adaptabilities, as demonstrated by its ability to solve multiarmed bandit problems (MBPs) in which a gambler given a choice of slot machines must select the appropriate machines to play so as to maximize the total reward in a series of trials. Furthermore, our ionic decision-maker successfully solves dynamic competitive MBPs, which cause serious loss due to the collision of selfish users in communication networks. The technique used in our devices offers a shift toward decision-making using the motion of ions, an approach that could find myriad applications in computer science and technology, including artificial intelligence.

Admittance of Atomic and Molecular Junctions and Their Signal Transmission

Atom-sized contacts of metals are usually characterized by their direct current (DC) conductance. However, when atom-sized contacts are used as device interconnects and transmit high frequency signals or fast pulses, the most critical parameter is not their DC conductance but their admittance Y(ω), in particular its imaginary part ImY(ω). In this article, I will present a brief survey of theoretical and experimental results on the magnitude of Y(ω) for atom-sized contacts of metals. Theoretical contact models are first described and followed by numerical evaluation of ImY(ω) based on these models. As for experiments on Y(ω), previous experiments conducted under time-varying biases are surveyed, and then the results of direct signal transmission through atom-sized contacts are discussed. Both theoretical and experimental results indicate that ImY(ω) is negligibly small for typical atom-sized contacts for signal frequencies up to 1 GHz.

Nanostructured silver sulfide: synthesis of various forms and their application

The results of experimental studies on nanostructured silver sulfide are analyzed and generalized. The influence of small particle size on nonstoichiometry of silver sulfide is discussed. Methods for the synthesis of various forms of nanostructured Ag2S including nanopowders, stable colloidal solutions, quantum dots, core – shell nanoparticles and heteronanostructures are described. The advantages and drawbacks of different synthetic procedures are analyzed. Main fields of application of nanostructured silver sulfide are considered.

The bibliography includes 184 references.