Small Methods最新文献

Memristors based on green organic materials are needed for advanced wearable neuromorphic computing electronics and to facilitate the development of ecologically benign bioelectronics. Porphyrins, as conjugated macrocyclic green organic compounds, exhibit good biocompatibility and chemical stability and have been employed as the resistive switching (RS) layer in memristors. However, achieving low power consumption and a high switching ratio remains a challenge for the development of porphyrin-based memristors as synaptic devices. Furthermore, their fabrication is typically complex and relies on a rigid or flexible planar substrate. We developed a Cu(II) meso-tetra(4-carboxyphenyl) porphyrin (CuTCPP)-based textile memristor that uses the electrophoretic deposition-assisted self-assembly method. The CuTCPP-based memristor exhibited excellent RS characteristics including an ultra-low RS reset voltage (-0.037 V), high switching ratio (∼5 × 10⁷), low set energy (456.52 fJ), good cycling stability, and data retention performance. The CuTCPP-based memristor emulated numerous biological synaptic functions and demonstrated its capability in performing the four fundamental arithmetic operations and digit image recognition. We used the CuTCPP-based memristor to construct a light-pressure-temperature sensing system to assist the visually impaired with recognizing Braille. The research is expected to lay the foundation for the development of wearable neuromorphic computing electronics and next-generation in-memory computing textile systems.

Cell viability assays are essential tools in biomedical research and drug development. Artificial intelligence (AI) offers the potential to simplify these assays by predicting cell viability directly from brightfield microscopy images, but current models lack generalizability across diverse cell types and treatments. Here, we introduce a strategy called "regularized imaging", where single cells are isolated in nanowells to generate standardized image patches that simplify segmentation and improve training data quality. We trained our model using example images of live and dead cells from a single cell line exposed to four cytotoxic conditions (ethanol, andrographolide, daunorubicin, and serum starvation). Despite this narrow training dataset, the resulting model accurately identified live and dead cells after treatments by previously unseen compounds, successfully replicating dose-response curves comparable to fluorescence live/dead assays. Importantly, this model effectively generalized across diverse cell types, including both adherent and suspension cells. Additionally, microscopy-based cell viability analysis is non-destructive, enabling repeated measurements to perform kinetic studies to distinguish between fast- and slow-acting compounds. Our findings highlight how regularized single-cell imaging enables the training of broadly generalizable AI models to recognize biologically relevant cell features for label-free cell screening workflows.

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Clear signals emerge from a curtain of noise as this work reveals the true electromechanical behavior of ferroelectric materials. By identifying and reconstructing unreliable signals through Bayesian matrix completion, the framework restores physically meaningful responses and hence transforms low signal-to-noise data into coherent insight on nanoscale switching dynamics and material functionality via piezoresponse force microscopy. More in article number 2500318, Bassiri-Gharb and co-workers. Image design by Nicholas Preston.

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In article number 2402202, Song, Weon, and co-workers present a quantitative X-ray microtomography platform for visualizing and analyzing fragile cosmetic films on biomimetic skin. By mapping film thickness, topography, and skin deformation while resolving emulsion droplets, the platform reveals how the performance of the films is governed by their microscale architecture. This approach provides an objective method for evaluating the behavior, texture, and stability of cosmetic films beyond conventional visual and sensory assessment.

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In article number 2501088, Gholipour and co-workers introduce a cost-effective, solution-processed route to programmable photonics using chalcogenide semiconductors. Optical-grade Sb₂S₃ films spin-coated at subwavelength thickness deliver nonvolatile modulation comparable to PVD, yet with markedly lower thermo-optic noise and drift. Patterned as polarization-sensitive nanograting metasurfaces, they enable robust, programmable resonances and point to scalable displays, memory, and hybrid quantum/neuromorphic photonic platforms.

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In article number 2501088, Gholipour and co-workers introduce a cost-effective, solution-processed route to programmable photonics using chalcogenide semiconductors. Optical-grade Sb₂S₃ films spin-coated at subwavelength thickness deliver nonvolatile modulation comparable to PVD, yet with markedly lower thermo-optic noise and drift. Patterned as polarization-sensitive nanograting metasurfaces, they enable robust, programmable resonances and point to scalable displays, memory, and hybrid quantum/neuromorphic photonic platforms.

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In article number 2500816, Liu, Ding, and co-workers present an atomistic simulation framework for unraveling thermal and chemical expansion behaviors in protonic ceramic oxide PrNi_xCo_1−xO_3−δ. Leveraging phonon calculations powered by a machine learning potential method, complex lattice expansions induced by heat, hydration, and composition are disentangled, guiding the design of more stable interfaces in protonic ceramic electrochemical cells.

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In article number 2500816, Liu, Ding, and co-workers present an atomistic simulation framework for unraveling thermal and chemical expansion behaviors in protonic ceramic oxide PrNi_xCo_1−xO_3−δ. Leveraging phonon calculations powered by a machine learning potential method, complex lattice expansions induced by heat, hydration, and composition are disentangled, guiding the design of more stable interfaces in protonic ceramic electrochemical cells.

The integration of two-dimensional (2D) magnetic materials with silicon-based semiconductor technology is a critical advance for next-generation electronics, yet it has been fundamentally hampered by the absence of synthesis methods that are simultaneously compatible with back-end-of-line (BEOL) thermal budgets and capable of direct growth on amorphous substrates. Here, we overcome this long-standing integration barrier by demonstrating, for the first time, the wafer-scale synthesis of the 2D van der Waals (vdW) magnet FePS₃, and more broadly, other transition metal phosphorus trisulfides. Our Si-CMOS compatible, two-step strategy couples magnetron sputtering of a metal precursor with a precisely controlled phosphosulfurization process at a low temperature of 350°C, enabling the direct growth of high-quality, uniform crystalline films on amorphous SiO₂ and sapphire substrates. The synthesized films exhibit prominent ferromagnetism with perpendicular magnetic anisotropy and a Curie temperature of approximately 220 K. This work establishes a technologically viable materials platform, poised to accelerate the integration of 2D magnets into advanced spintronic and quantum computing architectures.

Red blood cells (RBCs) play a crucial role in delivering oxygen to tissues with their distinctive shape. However, the mechanisms underlying cellular deformation and rupture due to stress, which lead to diseases such as acute renal failure, pulmonary hypertension, anemia, and gallstone formation, remain poorly understood. Here, we investigate the mechanism of membrane protrusion and present a highly effective method to restore the morphology and function of damaged RBCs. We propose ultrasound-triggered nanodroplets loaded with oxygen and glucose to increase the local concentrations of these substances around RBCs and facilitate the rapid release of their payloads to repair fatigued RBCs under ultrasound. We identify a critical membrane protrusion length threshold of one-third the cell's diameter, beyond which the skeleton structure fractures and prevents repair. Our findings demonstrate how nanodroplets can efficiently deliver oxygen and glucose to expose membrane connection and trigger cytoskeleton reorganization to repair cellular structure. In an in vitro extracorporeal membrane oxygenation (ECMO) model, our method reduces the percentage of abnormal RBCs to 5% and decreases free hemoglobin concentration by 50%. This work offers new insights into RBC rejuvenation and strongly supports the potential of ultrasound-triggered nanodroplets for revitalizing fatigued RBCs, contributing to long-term health and well-being.