Effects of surface hydrophobization on the phase evolution behavior of iron-based catalyst during Fischer-Tropsch synthesis.

Iron-based Fischer-Tropsch synthesis (FTS) catalyst is widely used for syngas conversion, but its iron carbide active phase is easily oxidized into Fe3O4 by the water produced during reaction, leading to the deterioration of catalytic performance. Here, we show an efficient strategy for protecting the iron carbide active phase of FTS catalyst by surface hydrophobization. The hydrophobic surface can reduce the water concentration in the core vicinity of catalyst during syngas conversion, and thus inhibit the oxidation of iron species by water, which enhances the C - C coupling ability of catalyst and promotes the formation of long-chain olefins. More significantly, it is unraveled that appropriate shell thickness plays a crucial role in stabilizing the iron carbide active phase without Fe3O4 formation and achieving good catalytic performance.

Production of Jet Fuel Range Aromatics by Alkylation of Benzene with Olefins over Bifunctional Ga/ZSM-5 Catalyst.

Aromatic components of C8-C15 are playing indispensable roles in multi-functional properties of jet fuel. Here, we reported the controllable alkylation of benzene with mixed olefins of ethylene and propylene toward C8-C15 aromatic hydrocarbons for jet fuels over the bifunctional Ga/ZSM-5 catalyst. The resultant 2Ga/ZSM-5 exhibited a superior selectivity of 86.4% (yield of 55.5%) to C8-C15 range aromatics, at benzene conversion of 40.3%, ethylene and propylene conversion of 99.5% and 99.2%, respectively. The incorporation of Ga species could effectively weaken the strong acid sites of ZSM-5 and endow 2Ga/ZSM-5 catalyst with appropriate acidity, therefore facilitating the benzene alkylation process and suppressing the undesired hydrogen transfer or aromatization side reactions as well, thus improving the yield of desired C8-C15aromatics for jet fuels. This work provided insight into the development of promising bifunctional catalyst for the oriented transformation of biomass-derived chemicals to aviation fuels.

Preparation of high-affinity and high-specificity monoclonal antibody and development of ultra-sensitive immunoassay for the detection of 1-aminohydantoin, the metabolite of nitrofurantoin.

1-Aminohydantoin (AHD), the residual marker of nitrofurantoin, is usually detected after derivatisation using the derivatisation reagent 2-nitrobenzaldehyde. Avoiding the antibody recognition of the derivatisation reagent is essential for the accurate detection of AHD residues. In this paper, a novel hapten called hapten D was designed, and then, a monoclonal antibody that did not recognise 2-nitrobenzaldehyde was prepared based on this novel hapten. An ultra-sensitive indirect competitive enzyme linked-immunosorbent assay (icELISA) was established under optimal conditions. The 50% inhibition concentration and limit of detection of AHD were 0.056 and 0.0060 ng/mL, respectively, which improved the sensitivity by 9-37-fold compared with the previously reported icELISA methods. The average recovery rates were 88.1%-97.3%, and the coefficient of variation was <8.6%. The accuracy and reliability of the icELISA were verified using liquid chromatography-tandem mass spectrometry. These results demonstrated that the developed icELISA is a useful and reliable tool.

Full waveform inversion using frequency shift envelope-based global correlation norm for ultrasound computed tomography.

Many studies have been carried out on ultrasound computed tomography (USCT) for its ability to offer quantitative measurements of tissue sound speed. Full waveform inversion (FWI) is a technique for reconstructing high-resolution sound speed images by iteratively minimizing the difference between the observed ultrasound data and the synthetic data based on the waveform equation. However, FWI suffers from cycle-skipping, which usually causes FWI convergence at a local minimum. Cycle-skipping occurs when the phase difference between the observed data and the synthetic data exceeds half a cycle. The simplest way to avoid cycle-skipping is to use low-frequency information for reconstruction. Nevertheless, in imaging systems, the response bandwidth of the probe is limited, and reliable low-frequency information often exceeds the response band. Therefore, it is a challenge to perform FWI imaging and avoid cycle-skipping problems without low-frequency information. In this paper, we propose a frequency shift envelope-based global correlation norm (FSEGCN), where an artificial source wavelet with a lower frequency is adopted to calculate synthetic data. FSEGCN compared with FWI, envelope inversion (EI), global correlation norm (GCN), envelope-based global correlation norm (EGCN) through concentric circle phantom without low-frequency information. The experimental results demonstrated the capability of the proposed method to recover the sound speed close to the exact model in the absence of low-frequency information, whereas FWI, EI, GCN, and EGCN cannot. Experiments on phantoms of the human head and calf show that artificial source wavelets can reduce image artifacts and enhance reconstruction robustness, when original low-frequency information is absent.

Dimethyl Carbonate Synthesis from CO2 over CeO2 with Electron-Enriched Lattice Oxygen Species.

Direct synthesis of dimethyl carbonate (DMC) from CO2 plays an important role in carbon neutrality, but its efficiency is still far from the practical application, due to the limited understanding of the reaction mechanism and rational design of efficient catalyst. Herein, abundant electron-enriched lattice oxygen species were introduced into CeO2 catalyst by constructing the point defects and crystal-terminated phases in the crystal reconstruction process. Benefitting from the acid-base properties modulated by the electron-enriched lattice oxygen, the optimized CeO2 catalyst exhibited a much higher DMC yield of 22.2 mmol g-1 than the reported metal-oxide-based catalysts at the similar conditions. Mechanistic investigations illustrated that the electron-enriched lattice oxygen can provide abundant sites for CO2 adsorption and activation, and was advantageous of the formation of the weakly adsorbed active methoxy species. These were facilitating to the coupling of methoxy and CO2 for the key *CH3OCOO intermediate formation. More importantly, the weakened adsorption of *CH3OCOO on the electron-enriched lattice oxygen can switch the rate-determining-step (RDS) of DMC synthesis from *CH3OCOO formation to *CH3OCOO dissociation, and lower the corresponding activation barriers, thus giving rise to a high performance. This work provides insights into the underlying reaction mechanism for DMC synthesis from CO2 and methanol and the design of highly efficient catalysts.

Normalized Spatial Autocorrelation in Ultrasound B-Mode Imaging for Point-Scatterer Detection.

OBJECTIVE: Point-scatterer detection plays a key role in medical ultrasound B-mode imaging. Speckle noise and insufficient spatial resolution are important factors affecting point-scatterer detection. To address this issue, normalized spatial autocorrelation in ultrasound B-mode imaging (NSACB) is proposed. METHODS: First, the acquired data are pre-processed by adding Gaussian white noise (GWN) with a certain signal-to-Gaussian white noise ratio (SGWNR). Next, normalized spatial autocorrelation is applied to the pre-processed data, and the data are divided into several new signals with different spatial lags. Then, the new signals are performed unsigned delay multiply and sum. Finally, the NSACB beamformed data are bandpass filtered by extracting the frequency component around twice the center frequency. Simulated and in vitro experiments were designed for validation. RESULTS: Simulations revealed that the lateral resolution of NSACB measured by the -6-dB mainlobe width can reach as high as 11.11% of delay and sum (DAS), 25.01% of filtered delay multiply and sum (F-DMAS) and 50% of LAG-FDMAS-SCF. The sidelobe level of the NSACB can be reduced at most by 28 dB. Experimental results of simple and complex scatterer phantoms indicate the image resolution of the proposed NSACB can even reach up to 18.76% of DAS, 27.28% of F-DMAS and 14.29% of LAG-FDMAS-SCF. Compared with these methods, the proposed NSACB can reduce the sidelobe level at least by 18 dB. CONCLUSION: Although the proposed method causes loss of the ability to observe hypo-echoic structures, these results suggest future work to determine the ability to detect breast microcalcifications, kidney stones, biopsy needle tracking and other scenarios requiring scatterer detection.

Robust Semi-Supervised 3D Medical Image Segmentation With Diverse Joint-Task Learning and Decoupled Inter-Student Learning.

Semi-supervised segmentation is highly significant in 3D medical image segmentation. The typical solutions adopt a teacher-student dual-model architecture, and they constrain the two models' decision consistency on the same segmentation task. However, the scarcity of medical samples can lower the diversity of tasks, reducing the effectiveness of consistency constraint. The issue can further worsen as the weights of the models gradually become synchronized. In this work, we have proposed to construct diverse joint-tasks using masked image modelling for enhancing the reliability of the consistency constraint, and develop a novel architecture consisting of a single teacher but multiple students to enjoy the additional knowledge decoupled from the synchronized weights. Specifically, the teacher and student models 'see' varied randomly-masked versions of an input, and are trained to segment the same targets but reconstruct different missing regions concurrently. Such joint-task of segmentation and reconstruction can have the two learners capture related but complementary features to derive instructive knowledge when constraining their consistency. Moreover, two extra students join the original one to perform an inter-student learning. The three students share the same encoding but different decoding designs, and learn decoupled knowledge by constraining their mutual consistencies, preventing themselves from suboptimally converging to the biased predictions of the dictatorial teacher. Experimental on four medical datasets show that our approach performs better than six mainstream semi-supervised methods. Particularly, our approach achieves at least 0.61% and 0.36% higher Dice and Jaccard values, respectively, than the most competitive approach on our in-house dataset. The code will be released at https://github.com/zxmboshi/DDL.

Quantitative Determination of Aflatoxin B1 in Maize and Feed by ELISA and Time-Resolved Fluorescent Immunoassay Based on Monoclonal Antibodies.

In this study, a highly sensitive monoclonal antibody (mAb) was developed for the detection of aflatoxin B1 (AFB1) in maize and feed. Additionally, indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) and time-resolved fluorescence immunoassay assay (TRFICA) were established. Firstly, the hapten AFB1-CMO was synthesized and conjugated with carrier proteins to prepare the immunogen for mouse immunization. Subsequently, mAb was generated using the classical hybridoma technique. The lowest half-maximal inhibitory concentration (IC50) of ic-ELISA was 38.6 ng/kg with a linear range of 6.25-100 ng/kg. The limits of detections (LODs) were 6.58 ng/kg and 5.54 ng/kg in maize and feed, respectively, with the recoveries ranging from 72% to 94%. The TRFICA was developed with a significantly reduced detection time of only 21 min, from sample processing to reading. Additionally, the limits of detection (LODs) for maize and feed were determined to be 62.7 ng/kg and 121 ng/kg, respectively. The linear ranges were 100-4000 ng/kg, with the recoveries ranging from 90% to 98%. In conclusion, the development of AFB1 mAb and the establishment of ic-ELISA for high-throughput sample detection, as well as TRFICA for rapid detection presented robust tools for versatile AFB1 detection in different scenarios.

Monospecific and ultrasensitive detection of ofloxacin: A computational chemistry-assisted hapten screening strategy and analysis of molecular recognition mechanism.

Contamination in food and the environment with fluoroquinolones (FQs) has become a serious threat to the global ecological balance and public health safety. Ofloxacin (OFL) is one of the most widely utilized sterilization agents in FQs. In the process of monitoring OFL, broad-spectrum monoclonal antibodies (mAb) cannot meet the demand for monospecific detection. Here, a computational chemistry-assisted hapten screening strategy was proposed in this study. Differences in the properties of antigenic epitopes were precisely extracted through a comprehensive comparative study of 16 common FQs molecules and a monospecific and ultrasensitive mAb-3B4 for OFL was successfully prepared. The screened fleroxacin (FLE) hapten was applied in a heterologous competition strategy resulting in a 20-fold improvement in the half inhibitory concentration (IC50) of mAb-3B4 to 0.0375 µg L-1 and cross-reacted only with marbofloxacin (MAR) in regulated FQs. In addition, a single-chain variable fragment (scFv) for OFL was constructed for the first time with an IC50 of 0.378 µg L-1. Molecular recognition mechanism studies validated the reliability of this strategy and revealed the key amino acid sites responsible for OFL specificity and sensitivity. Finally, ic-ELISA and GICA were established for OFL in real samples. This work provides new ideas for the preparation of monospecific mAb and improves the monitoring system of FQs.