Electron-deficient Fe3O4@AC-NH2@Cu-MOF nanoparticles for enhanced degradation of electron-rich benzene derivatives via synergistic adsorption and catalytic oxidation.

Benzene derivatives in wastewater have negative impacts on ecosystems and human health, making their removal prior to discharge imperative. In this study, Fe3O4@AC-NH2@Cu-opa (AC-NH2 = aminoclay, Cu-opa = [Cu(opa)(bipy)0.5(H2O)]n (H2opa = 3-(4-oxypyridinium-1-yl) phthalic acid)) nanoparticles (NPs) were synthesized as adsorbent and catalyst for phenolic compound removal from wastewater. Fe3O4@AC-NH2@Cu-opa NPs demonstrated outstanding performance in the adsorption of phenol, exhibiting a remarkable adsorption capacity of up to 166.39 mg g-1 according to the Langmuir model. The composite also exhibited higher Fenton activity toward the degradation of electron-rich organic phenolic pollutants, with a rate approximately 3.4 times higher than that of Fe3O4 alone. The high catalytic activity of the composite was attributed to the large surface area and abundant active sites of the 2D charge-separated Cu-MOF. Meanwhile, the superparamagnetism of the Fe3O4 core enabled magnetic recollection and reuse without any significant loss of activity. Therefore, use of Fe3O4@AC-NH2@Cu-opa/H2O2 shows potential in an efficient method for the removal of phenolic compounds from wastewater.

A Multimodal Sensing CMOS Imager Based on Dual-Focus Imaging.

Advanced machine intelligence is empowered not only by the ever-increasing computational capability for information processing but also by sensors for collecting multimodal information from complex environments. However, simply assembling different sensors can result in bulky systems and complex data processing. Herein, it is shown that a complementary metal-oxide-semiconductor (CMOS) imager can be transformed into a compact multimodal sensing platform through dual-focus imaging. By combining lens-based and lensless imaging, visual information, chemicals, temperature, and humidity can be detected with the same chip and output as a single image. As a proof of concept, the sensor is equipped on a micro-vehicle, and multimodal environmental sensing and mapping is demonstrated. A multimodal endoscope is also developed, and simultaneous imaging and chemical profiling along a porcine digestive tract is achieved. The multimodal CMOS imager is compact, versatile, and extensible and can be widely applied in microrobots, in vivo medical apparatuses, and other microdevices.

Visual-Olfactory Synergistic Perception Based on Dual-Focus Imaging and a Bionic Learning Architecture.

The synergistic interaction of vision and olfaction is critical for both natural and artificial intelligence systems to recognize and adapt to complex environments. However, current bioinspired systems with visual and olfactory sensations are mostly assembled with separate and heterogeneous sensors, inevitably leading to bulky systems and incompatible datasets. Here, we demonstrate on-chip integration of visual and olfactory sensations through a dual-focus imaging approach. By combining lens-based visual imaging and lensless colorimetric imaging, a target object and its odor fingerprint can be captured with a single complementary metal-oxide-semiconductor imager, and the obtained multimodal images are analyzed with a bionic learning architecture for information fusion and perception. To demonstrate the capability of this system, we adapted it to food detection and achieved 100% accuracy in identifying meat freshness and category with a 10 s sampling time. In addition to the highly integrated sensor design, our approach exhibits superior accuracy and efficiency in object recognition, providing a promising approach for robotic sensing and perception.

Multiplexed Chemical Sensing CMOS Imager.

A miniaturized and multiplexed chemical sensing technology is urgently needed to empower mobile devices and robots for various new applications such as mobile health and Internet of Things. Here, we show that a complementary metal-oxide-semiconductor (CMOS) imager can be turned into a multiplexed colorimetric sensing chip by coating micron-scale sensing spots on the CMOS imager surface. Each sensing spot contains nanocomposites of colorimetric sensing probes and silica nanoparticles that enhance sensing signals by several orders of magnitude. The sensitivity is spot-size-invariant, and high-performance gas sensing can be achieved on sensing spots as small as ∼10 µm. This great scalability combined with millions of pixels of a CMOS imager offers a promising platform for highly integrated chemical sensors. To prove its compatibility with mobile electronics, we have built a smartphone accessory based on this chemical CMOS sensor and demonstrated that personal health management can be achieved through the detection of gaseous biomarkers and pollutants. We anticipate that this new platform will pave the way for the widespread application of chemical sensing in mobile electronics and wearable devices.

Online Accurate Detection of Breath Acetone Using Metal Oxide Semiconductor Gas Sensor and Diffusive Gas Separation.

Breath acetone (BrAce) level is an indicator of lipid oxidation rate, which is crucial for evaluating the status of ketoacidosis, ketogenic diet, and fat burning during exercise. Despite its usefulness, detecting BrAce accurately is challenging because exhaled breath contains an enormous variety of compounds. Although many sensors and devices have been developed for BrAce measurement, most of them were tested with only synthetic or spiked breath samples, and few can detect low concentration BrAce in an online manner, which is critical for extending application areas and the wide acceptance of the technology. Here, we show that online detection of BrAce can be achieved using a metal oxide semiconductor acetone sensor. The high accuracy measurement of low concentration BrAce was enabled by separating major interference gases utilizing their large diffusion coefficients, and the accuracy is further improved by the correction of humidity effect. We anticipate that the approach can push BrAce measurement closer to being useful for various applications.