Publications by authors named "Joohong Lee"

Article Synopsis
  • The research focuses on a new type of memristive device using Dabconium ammonium triiodide (DABCO-NH-I), which is touted for its reliability and durability compared to traditional organic materials used in wearable electronics.
  • DABCO-NH-I has a unique hexagonal crystal structure and a low dielectric constant, allowing it to operate at low voltages while achieving a high on/off switching ratio of about 10, making it suitable for multi-level data storage.
  • With improved thermal conductivity, the device effectively dissipates heat generated during operation, demonstrating reliable performance over at least 10 cycles at varying temperatures, thus addressing challenges faced by existing organic devices.
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Halide perovskite-based resistive switching memory (memristor) has potential in an artificial synapse. However, an abrupt switch behavior observed for a formamidinium lead triiodide (FAPbI)-based memristor is undesirable for an artificial synapse. Here, we report on the δ-FAPbI/atomic-layer-deposited (ALD)-SnO bilayer memristor for gradual analogue resistive switching.

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Metal halide perovskite solar cells (PSCs) are infamous for their batch-to-batch and lab-to-lab irreproducibility in terms of stability and performance. Reproducible fabrication of PSCs is a critical requirement for market viability and practical commercialization. PSC irreproducibility plagues all levels of the community; from institutional research laboratories, start-up companies, to large established corporations.

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The importance of light management for perovskite solar cells (PSCs) has recently been emphasized because their power conversion efficiency approaches their theoretical thermodynamic limits. Among optical strategies, anti-reflection (AR) coating is the most widely used method to reduce reflectance loss and thus increase light-harvesting efficiency. Monolayer MgFis a well-known AR material because of its optimal refractive index, simple fabrication process, and physical and chemical durabilities.

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Sn-based perovskite light-emitting diodes (PeLEDs) have emerged as promising alternatives to Pb-based PeLEDs with their rapid increase in performance owing to the various research studies on inhibiting Sn oxidation. However, the absence of defect passivation strategies for Sn-based perovskite LEDs necessitates further research in this field. We performed systematic studies to investigate the design rules for defect passivation agents for Sn-based perovskites by incorporating alkali/multivalent metal salts with various cations and anions.

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Chemical bath deposition (CBD) is widely used to deposit tin oxide (SnO ) as an electron-transport layer in perovskite solar cells (PSCs). The conventional recipe uses thioglycolic acid (TGA) to facilitate attachments of SnO particles onto the substrate. However, nonvolatile TGA is reported to harm the operational stability of PSCs.

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Cations with suitable sizes to occupy an interstitial site of perovskite crystals have been widely used to inhibit ion migration and promote the performance and stability of perovskite optoelectronics. However, such interstitial doping inevitably leads to lattice microstrain that impairs the long-range ordering and stability of the crystals, causing a sacrificial trade-off. Here, we unravel the evident influence of the valence states of the interstitial cations on their efficacy to suppress the ion migration.

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With recent advances in biotechnology and sequencing technology, the microbial community has been intensively studied and discovered to be associated with many chronic as well as acute diseases. Even though a tremendous number of studies describing the association between microbes and diseases have been published, text mining methods that focus on such associations have been rarely studied. We propose a framework that combines machine learning and natural language processing methods to analyze the association between microbes and diseases.

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