Probe bismuth sulfide modified with Pluronic F127 (Bi2S3-PF127), which has high biocompatibility and dispersibility, is synthesized using triblock copolymer Pluronic F127 to modify hydrophobic Bi2S3 nanoparticles that are prepared by a hot injection method. TEM results show that most of the probe has a length of about 14.85 ± 1.70 nm and a breadth of about 4.79 ± 0.63 nm. After injected into the tail vein of a mouse, the probe has obvious CT contrast enhancement capability from x-ray CT imaging results. Meanwhile, the probe's in vivo toxicity is also studied. It is found that hematoxylin and eosin stains of major organs have no change. A biochemical analysis (alanine aminotransferase and aspartate aminotransferase) prove the probe has no adverse effects. The results of a blood analysis (white blood cell count, red blood cell count, hemoglobin, and platelet count) are also normal. The biological distribution of Bi by ICP-AES shows that most of nanoparticles are cleaned out after injection 48 h, and the circulation half-life of the probe is 5.0 h, suggesting that Bi2S3-PF127 has a long circulation and indicating that the Bi2S3-PF127 probe has good biocompatibility and safety.

Active magnetic detection is an effective method for detecting metal targets. Its practical application is confirmed in many previous studies, and its advantages over passive detection have been widely recognized. Most importantly, it can detect weak magnetic or nonmagnetic metal targets, unlike traditional magnetic detection. However, the secondary magnetic field generated by the eddy current on the target excited by the active emission primary magnetic field is always weak, and it has a fast attenuation in space. The target signal measured by the sensor is typically several orders of magnitude smaller than the background interference, which makes it challenging to extract the target signal during detection. This study mitigates these challenges by constructing the secondary magnetic field characteristic of the target from the perspective of signal energy. A set of 13 orthonormal basis functions (OBFs) are further derived to linearly describe this characteristic, which improves the signal-to-noise ratio (SNR) of the signal. The main contribution of this study is the proposal of an eddy current magnetic field OBF (ECMF-OBF) method to effectively characterize the secondary magnetic field of magnetic targets in active magnetic detection. The SNR is considerably improved by the proposed method, and this is independent of the target magnetic moment orientation. Our experiment is performed in different environments, including indoors, lake, and sea, to verify the method’s performance. Therefore, it has excellent value in the practical application of active magnetic detection.

Target detection technology based on magnetic anomalies, due to its wide detection range, high localization accuracy, all weather conditions and other characteristics, plays an important role in geological prospecting, medical monitoring, disaster rescue and other fields. Some nonmagnetic or weakly magnetic metal targets are difficult to observe with passive magnetic anomaly detection (MAD) methods. The active MAD method based on the eddy current magnetic effect can locate nonmagnetic metal targets. However, traditional detection methods based on magnetic dipoles require knowledge of the target magnetic moment in advance and are not suitable for near-field detection. To solve these problems, this paper establishes a detection model based on a nonmagnetic metal shell target and derives the eddy current magnetic field (ECMF) expression of the nonmagnetic metal shell target. An ECMF extraction method that separates the ECMF from the excitation magnetic field and background interference from the perspective of the signal phase is further proposed. Then, the particle swarm optimization (PSO) algorithm is used to locate the nonmagnetic metal target. When the metal target is located within the range of 1.2 m*1.2 m, the localization error is approximately 2.5%. This method is important and valuable in the fields of medical pill tracking, drug dose conversion monitoring, trapped miner locating, indoor autonomous robot navigation, unexploded object detection and other fields.

To achieve high-precision vector measurement values in a geomagnetic field, it is necessary to develop methods for overcoming alternating magnetic interference (AMI), which is generated by electrical equipment. This paper proposes the adaptive alternating magnetic interference suppression (AAIS) algorithm. In this algorithm, first, only a triaxial fluxgate sensor measures the magnetic field data. The time–frequency diagram of the total magnetic field is obtained quickly through short-time Fourier transform and wavelet transform. Additionally, the time and frequency of AMI appearance are analyzed. Then, the triaxial adaptive notch filter suppresses the three-component related magnetic interference. Herein, simulation and actual experiments are performed to verify the effectiveness of AAIS. The results indicate that the algorithm can quickly detect the frequencies of AMI from the total magnetic field and adaptively fit their amplitude and phase on the vector magnetic field. Finally, AAIS can suppress the interference effectively. The AAIS algorithm realizes error compensation for the vector measurement values by the total magnetic field, which effectively improves the vector measurement accuracy of the geomagnetic field. We highlight that the AAIS algorithm is effective for AMIs of different frequencies, numbers, and intensities without reference sensors. Our work has practical implications in airborne, vehicle-mounted, and shipborne geomagnetic vector detection.