Engineering topics

Yuan, Yifan

Publications and source records attributed to Yuan, Yifan.

6 records

DOE OSTI2024

Proton Conducting Neuromorphic Materials and Devices

Neuromorphic computing and artificial intelligence hardware generally aims to emulate features found in biological neural circuit components and to enable the development of energy-efficient machines. In the biological brain, ionic currents and temporal concentration gradients control information flow and storage. It is therefore of interest to examine materials and devices for neuromorphic computing wherein ionic and electronic currents can propagate. Protons being mobile under an external electric field offers a compelling avenue for facilitating biological functionalities in artificial synapses and neurons. In this review, we first highlight the interesting biological analog of protons as neurotransmitters in various animals. We then discuss the experimental approaches and mechanisms of proton doping in various classes of inorganic and organic proton-conducting materials for the advancement of neuromorphic architectures. Since hydrogen is among the lightest of elements, characterization in a solid matrix requires advanced techniques. We review powerful synchrotron-based spectroscopic techniques for characterizing hydrogen doping in various materials as well as complementary scattering techniques to detect hydrogen. First-principles calculations are then discussed as they help provide an understanding of proton migration and electronic structure modification. Outstanding scientific challenges to further our understanding of proton doping and its use in emerging neuromorphic electronics are pointed out.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Hydrogen-induced tunable remanent polarization in a perovskite nickelate

Materials with field-tunable polarization are of broad interest to condensed matter sciences and solid-state device technologies. Here, using hydrogen (H) donor doping, we modify the room temperature metallic phase of a perovskite nickelate NdNiO 3 into an insulating phase with both metastable dipolar polarization and space-charge polarization. We then demonstrate transient negative differential capacitance in thin film capacitors. The space-charge polarization caused by long-range movement and trapping of protons dominates when the electric field exceeds the threshold value. First-principles calculations suggest the polarization originates from the polar structure created by H doping. We find that polarization decays within ~1 second which is an interesting temporal regime for neuromorphic computing hardware design, and we implement the transient characteristics in a neural network to demonstrate unsupervised learning. These discoveries open new avenues for designing ferroelectric materials and electrets using light-ion doping.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Spatial Interactions in Hydrogenated Perovskite Nickelate Synaptic Networks

A key aspect of how the brain learns and enables decision-making processes is through synaptic interactions. Electrical transmission and communication in a network of synapses are modulated by extracellular fields generated by ionic chemical gradients. Emulating such spatial interactions in synthetic networks can be of potential use for neuromorphic learning and the hardware implementation of artificial intelligence. Here, in this work, we demonstrate that in a network of hydrogen-doped perovskite nickelate devices, electric bias across a single junction can tune the coupling strength between the neighboring cells. Electrical transport measurements and spatially resolved diffraction and nanoprobe X-ray and scanning microwave impedance spectroscopic studies suggest that graded proton distribution in the inhomogeneous medium of hydrogen-doped nickelate film enables this behavior. We further demonstrate signal integration through the coupling of various junctions.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Complex Oxides for Brain–Inspired Computing: A Review

The fields of brain-inspired computing, robotics, and, more broadly, artificial intelligence (AI) seek to implement knowledge gleaned from the natural world into human-designed electronics and machines. In this review, the opportunities presented by complex oxides, a class of electronic ceramic materials whose properties can be elegantly tuned by doping, electron interactions, and a variety of external stimuli near room temperature, are discussed. The review begins with a discussion of natural intelligence at the elementary level in the nervous system, followed by collective intelligence and learning at the animal colony level mediated by social interactions. An important aspect highlighted is the vast spatial and temporal scales involved in learning and memory. The focus then turns to collective phenomena, such as metal-to-insulator transitions (MITs), ferroelectricity, and related examples, to highlight recent demonstrations of artificial neurons, synapses, and circuits and their learning. First-principles theoretical treatments of the electronic structure, and in situ synchrotron spectroscopy of operating devices are then discussed. The implementation of the experimental characteristics into neural networks and algorithm design is then revewed. Finally, outstanding materials challenges that require a microscopic understanding of the physical mechanisms, which will be essential for advancing the frontiers of neuromorphic computing, are highlighted.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Synthesis and electrical behavior of VO 2 thin films grown on SrRuO 3 electrode layers

VO 2 thin films were grown on conducting oxide underlayer SrRuO 3 buffered SrTiO 3 (111) and Si/SiO 2 substrates, respectively, using sputtering. X-ray diffraction phi-scans revealed the epitaxial nature of the VO 2 films grown on SrRuO 3 buffered SrTiO 3 and polycrystalline structure for films grown on SrRuO 3 buffered Si/SiO 2 . X-ray photoelectron spectroscopy confirms a dominant presence of V 4+ in both films and establishes a high-quality growth of single-phase VO 2 films. Temperature and electric-field driven metal-insulator-transition in both the in-plane and out-of-plane configurations were investigated. Depending on the configuration, the resistance change across the metal-insulator-transition varies from a factor of 1.57–3. The measured resistance in each state as well as the magnitude of resistance change were similar during temperature and electric-field driven metal-insulator-transition. To shed light on the suppressed metal-insulator-transition characteristics due to the current shunting effect from conducting SrRuO 3 bottom electrode, a distributed resistance network model is proposed and benchmarked against reports from the literature. Here, the results demonstrate the growth of high-quality VO 2 on conducting SrRuO 3 layers and their electrical behavior, which is of particular interest for all-oxide electronic devices utilizing phase transitions such as resistive memory and neuromorphic oscillators.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Highly Oriented Organic Ferroelectric Films with Single-Crystal-Level Properties from Restrained Crystallization

Device applications often require thin film growth with quasi-two-dimensional morphology and crystallization which are not always compatible. In this work, we exploit the method of low-temperature deposition followed by restrained crystallization (LDRC) in the growth of crystalline organic molecular thin films, which tend to grow three-dimensionally with random orientations. We demonstrate that, for 2-methylbenzimidazole (MBI), a molecular ferroelectric that tends to crystalize in spherulites, the quasi-two-dimensional films can be grown using LDRC with highly oriented polar axes and single-crystal-level ferroelectric properties. The crystallization process was shown to occur during the post-deposition annealing process using the in situ electrical measurements. The limited diffusion, low nucleation density, and low activation energy was found critical for the formation of the plate-shaped quasi-two-dimensional films. These results mark an important step in elucidating the LDRC as an effective and general approach for fabricating films with balanced crystallinity and morphology which are critical for applications.

36 MATERIALS SCIENCE↗