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Verified CAS / Academic Author4 Decoded Studies

Prof. SU Ying

State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology; School of Materials Science and Engineering, Wuhan University of Technology; School of Integrated Circuits and Electronics, Beijing Institute of Technology

Research Publications & English Decoded Briefs

Showing 4 publications
SCIENCE CHINA Materials2026DOI: 10.1007/s40843-026-4279-0

Inkjet Printing Organic Light-Emitting Diodes

Inkjet printing has emerged as a viable additive manufacturing route for organic light-emitting diodes (OLEDs), offering drop-on-demand patterning, high material utilization, and compatibility with large-area flexible substrates. This review critically examines the formulation science, printhead physics, and drying kinetics that govern the quality of inkjet-printed organic layers. We analyze the rheological window required for stable jetting, typically 1–20 mPa·s viscosity and 25–45 mN/m surface tension, and the dimensionless Ohnesorge number (0.1 < Z < 1) that defines satellite-free droplet formation. The coffee-ring effect, driven by capillary flow and solvent evaporation gradients, remains the dominant failure mode for pixel non-uniformity; binary solvent systems and substrate temperature control (40–60 °C) mitigate this. We survey recent progress in printed hole-transport, emissive, and electron-transport layers, with particular attention to cross-linkable hole-transport materials that resist interlayer dissolution. Device performance metrics from printed OLEDs now reach external quantum efficiencies of 15–20% for fluorescent emitters and >25% for phosphorescent systems, with operating lifetimes (T95) exceeding 1,000 hours at 1,000 cd/m². We identify remaining bottlenecks: nozzle clogging from aggregated nanoparticles, film thickness variation across large panels, and the absence of standardized ink formulations. The review concludes with a roadmap for industrial adoption, emphasizing in-line metrology and closed-loop process control as prerequisites for yield parity with vacuum-deposited OLEDs.

SCIENCE CHINA Materials2026DOI: 10.1007/s40843-025-3750-6

Achieving high thermoelectric performance in n-type polycrystalline SnSe via carrier mobility enhancement

SnSe is a promising thermoelectric material for medium-temperature applications due to its ultralow lattice thermal conductivity. However, the poor electrical conductivity of n-type polycrystalline SnSe significantly hinders its practical application. Here, we propose a dual-functional strategy employing InBr3 doping to synergistically enhance electrical transport while suppressing lattice thermal conductivity. For the first time, we demonstrate the successful construction of a Br-enriched conductive network within the SnSe matrix. The incorporation of In3+ and Br− introduces high-density charge carriers, while Br forms percolative conductive networks, resulting in a remarkable enhancement of carrier mobility to ~20.64 cm2 V−1 s−1. Simultaneously, the lattice thermal conductivity is substantially reduced to ~0.25 W m−1 K−1 through the formation of multi-scale defects, including dislocations and Br-rich nanowires, which effectively enhance phonon scattering. As a result, we achieve a peak figure of merit of ZT ~1.41 at 823 K, with an average figure of merit of ~0.42 over the temperature range of 323–823 K. This work provides a universal paradigm for decoupling electron-phonon interactions in thermoelectric materials, offering new insights for the optimization of thermoelectric performance.

Journal of Environmental Engineering Technology2026DOI: 10.13205/j.hjgc.202607017

Carbon Emissions Accounting and Techno-Economic Evaluation of Biochar and Organic Fertilizer Production from Distillers' Grains

Distillers' grains, the largest organic solid waste stream in the brewing industry, require efficient low-carbon valorization to support China's Dual Carbon Goals. This study employs life cycle assessment (LCA) to quantify CO2 emissions and carbon reduction benefits of two mainstream routes: pyrolysis to biochar and fermentation to organic fertilizer. Based on public process data, the total life-cycle CO2 emission for biochar production from 1 t of distillers' grains is 250.02 kg, with a carbon sequestration reduction of 120.29 kg, demonstrating superior long-term carbon fixation. In contrast, organic fertilizer production emits 536.14 kg CO2 per ton, achieving a carbon reduction of only 86.22 kg, indicating inferior mitigation performance. Techno-economic analysis reveals net profits of 471.97 CNY/t for biochar and 822.27 CNY/t for organic fertilizer, showing that the organic fertilizer route offers higher profitability. Both pathways effectively reduce CO2 emissions, with biochar prioritizing environmental sustainability and organic fertilizer excelling economically. This study provides data-driven insights for selecting organic solid waste recycling strategies, promoting low-carbon technologies, and establishing circular economy models in the brewing industry.

SCIENCE CHINA Materials2025DOI: 10.1007/s40843-025-3489-5

Low-power plasmonic SiC nanowire network-based artificial photo-synaptic device for musical classification neural network systems

Artificial synaptic devices for neuromorphic computing must reduce energy consumption to approach biological femtojoule levels. This work reports a SiC/SiO2@Ag nanowire network (NWN) device that emulates both ultraviolet visual and electrical synaptic functions under biased electric field and zero-bias photoexcitation. The NWN architecture and Ag nanoparticle-induced localized surface plasmon resonance (LSPR) enable substantial synaptic responses at ultra-low currents. The device achieves energy consumption of 0.471–0.218 pJ per synaptic event, significantly lower than conventional artificial synapses. In a musical classification task using a spiking neural network with hardware-implemented spike-timing-dependent plasticity (STDP), the system reaches >95% accuracy within 20 training epochs, surpassing software-based STDP and backpropagation after 10 epochs. The SiC NWN structure ensures robust synaptic performance and high precision. These results demonstrate a scalable, energy-efficient hardware foundation for neuromorphic music information processing, with potential for spiking neural networks that mimic biological operational principles.