Recycling
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2022
·Vol. 7
·期 2
·11
·
IF 0
Cesar Lubongo,Paschalis Alexandridis
Recycling plastic is an important step towards a circular economy. Attaining high-quality recycled plastics requires the separation of plastic waste by type, color, and size prior to reprocessing. Automated technology is key for sorting plastic objects in medium- to high-volume plants. The current state of the art of commercial equipment for sorting plastic as well as challenges faced by Material Recovery Facilities (MRFs) to sort post-consumer plastics are analyzed here. Equipment for sorting plastic recyclables were identified using publicly available information obtained from manufacturers’ websites, press releases, and journal articles. Currently available automated sorting equipment and artificial intelligence (AI)-based sorters are evaluated regarding their functionality, efficiency, types of plastics they can sort, throughput, and accuracy. The information compiled captures the progress made during the ten years since similar reports were published. A survey of MRFs, reclaimers, and brokers in the United States identified methods of sorting used for plastic, sorting efficiency, and current practices and challenges encountered at MRFs in sorting plastic recyclables. The commercial sorting equipment can address some of the challenges that MRFs face. However, sorting of film, multilayered, blended, or mixed-material plastics is problematic, as the equipment is typically designed to sort single-component materials. Accordingly, improvements and/or new solutions are considered necessary.Keywords:polymer;optical sorter;waste management;recycling;circular economy;sustainability
研究领域:
环境科学
·
工程技术
✓ 已验证
DOI
Cell Reports Physical Science
·
2025
·
IF 7.3
Jingyi Xiong,Jiawei Zhang,Xufan Zheng,Tianyu Hu,Huimin Xiang,Yuda Li,Biao Xiao,Xunchang Wang,Renqiang Yang
Summary Fluorescence sensing technology has been extensively used in the field of explosives monitoring for highly sensitive trace detection and early warning systems. However, these advancements have been hindered by a significant reliance on professional technicians and a low degree of automation. Here, we present a cloud-based website that encapsulates a deep-learning-assisted technique based on the PaddlePaddle You Only Look Once (PPYOLO) model and integrates a highly sensitive external fluorescence sensor. This approach, combined with a deep learning model, streamlines the detection of nitro explosives, enhancing automation levels and efficiency. The cloud-based interface and self-developed portable sampling software offer a user-friendly, interactive, and portable system. Moreover, the model boasts a target recognition accuracy (bounding box mean average precision [bbox_map]) of up to 99%, making it capable of automatically extracting six independent color signals from images and providing detection results. These results suggest that the proposed method could provide promising perspectives for the future development of efficient and portable explosives detection systems.
研究领域:
分析化学
·
爆炸物监测
·
人工智能
·
传感器技术
✓ 已验证
产品关联
DOI
高影响因子
ACS Omega
·
2020
·
IF 2.87
Yang Zhao,Yahang Xie,Qifan Zhou,Pan Wang,Ying Chang,Changxu Lin
An automatic setup for reactional wettability variation (RWV) was developed by interlinking liquid selection and transportation, object movement, and image recognition. In this way, the performance of the RWV strategy is updated to a nearly unmanned control manner with the example of methamphetamine and its aptamer. On the automatic RWV detection setup, the sensing surface acts similarly as before. The aptamer-based sensing surface resulted from the breakdown of the hydrophobic basis. The hydrophobicity is constructed on the metastable aptamer layer, which is responsive to the corresponding target. Methamphetamine interacts with its corresponding aptamer and destroys the basis of the hydrophobicity. A decrease in contact angle indicates the existence of methamphetamine. The RWV phenomenon is also affected by concentration and temperature. The development of an automatic detection ability would bring new possibilities to the surface reaction on smarter detection.
研究领域:
分析化学
·
生物传感
✓ 已验证
产品关联
DOI
PubMed
高影响因子
IEEE Sensors Letters
·
2024
·Vol. 9
·期 1
·1-4
·
IF 2.2
Jiawei Zhai,Bin Luo,Tianyang Liu,Xiaodong Wang,Chunjiang Zhao
Ion-selective electrodes (ISEs) play an important role in the field of electrochemical sensors and have a significant impact on future ion detection. At present, to address the sensor consistency issue in the commercialization process of ISE, we emphasize that automated manufacturing has the potential to achieve calibration-free sensors. First, the design of automated manufacturing requires expert experience to help understand the ISE mechanism and its structure. Then, we introduce two automated manufacturing processes for sensors to help understand the design and manufacturing process. Finally, we propose a device for semiautomated manufacturing of ISE and verify that automated manufacturing of ISE has better consistency and potential reproducibility than manual manufacturing of ISE. The results show that for the transduction layer (conductive graphite adhesive) coated automatically in the same batch, the impedance difference is 4.8 KΩ, while that of the manual batch is 36.6 KΩ. In the performance of cyclic voltammetry, the gap of peak current is reduced from 21.5 to 4.8
μ
A.
研究领域:
传感器技术
·
电化学工程
✓ 已验证
DOI
高影响因子
ACS Nano
·
2025
·
IF 16
Mohammad Zaki,Carsten Prinz,Bastian Ruehle
The recent emergence of self-driving laboratories (SDL) and material acceleration platforms (MAPs) demonstrates the ability of these systems to change the way chemistry and material syntheses will be performed in the future. Especially in conjunction with nano- and advanced materials which are generally recognized for their great potential in solving current material science challenges, such systems can make disrupting contributions. Here, we describe in detail MINERVA, an SDL specifically built and designed for the synthesis, purification, and in line characterization of nano- and advanced materials. By fully automating these three process steps for seven different materials from five representative, completely different classes of nano- and advanced materials (metal, metal oxide, silica, metal organic framework, and core–shell particles) that follow different reaction mechanisms, we demonstrate the great versatility and flexibility of the platform. We further study the reproducibility and particle size distributions of these seven representative materials in depth and show the excellent performance of the platform when synthesizing these material classes. Lastly, we discuss the design considerations as well as the hardware and software components that went into building the platform and make all of the components publicly available.
研究领域:
材料科学
·
化学工程
·
人工智能
✓ 已验证
DOI
PubMed
高影响因子
JOURNAL OF CHROMATOGRAPHY A
·
2014
·
IF 4.258
Hangzhen Lan,Ning Gan,Daodong Pan,Futao Hu,Tianhua Li,Nengbing Long,Li Qiao
A new automated solid-phase micro extraction (SPME) sampling method was developed for quantitative enrichment of estrogens (ES) from milk powder, using magnetic molecularly imprinted polymer (MMIP) as fiber coating. The method (MMIP-SPME) was built with several electromagnetic stainless steel fibers, placed in parallel for simultaneously extraction. The MMIP was synthesized using core–shell Fe 3 O 4 @SiO 2 nanoparticles (NPs) as magnetic support. Estradiol (E2) was employed as the template molecule, acrylamide (AA) as functional monomer, and ethylene glycol dimethacrylate (EGDMA) as cross-linker. MMIP can be easily absorbed or desorbed from fibers when the current is turned on or off, creating magnetism. Compared to traditional MIP-SPME, the prepared procedure of MMIP-SPME is time-saving and organic solvent-free. The proposed device significantly improved the efficiency of separation and enrichment of estrogens from complex matrices thereby and facilitating the pretreatment steps by electromagnetically controlled extraction fibers to achieve full automation. Several experimental parameters were studied, including extraction and desorption kinetics, solution pH, desorption solution, ratio, and shuttle rate. The newly developed MMIP-SPME showed good sensitivity and high binding capacity, fast adsorption kinetics and desorption kinetics for estrone (E1), estradiol (E2), estriol (E3) and diethylstilbestrol (DES) under optimized conditions. The detection limits for the four estrogens were 1.5–5.5 ng g −1 with excellent reproducibility (RSD values less than 7.1%) when milk powder samples spiked with analytes at 20, 100 and 250 ng g −1 were studied.
研究领域:
分析化学
·
环境科学
·
食品科学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
ANALYTICA CHIMICA ACTA
·
2025
·
IF 6
Lin Cheng,Yitong Li,Weiwei Ji,Jing Yan
Rapid and sensitive protein detection methods are of benefit to clinical diagnosis, pathological mechanism research, and infection prevention. However, routine protein detection technologies, such as enzyme-linked immunosorbent assay and western blot, suffer from low sensitivity, poor quantification and labourious operation. Herein, we developed a fully automated protein analysis system to conduct fast protein quantification at the single molecular level. It streamlines antibody-coated beads-based protein capture, fluorescent labelling with fluorophore-conjugated antibodies, and flow-cytometric optical detection in a microfluidic chip, achieving sample-in quantitative result-out protein detection within 60 min. This platform employs a combination of spiral and ultrasonic mixing, and realizes highly efficient protein capture and immunolabelling. Leveraging non-Newtonian fluids, the beads can be well-aligned at the focus of the optical module, yielding robust protein quantification results with a low coefficient of variation of 0.4%. As a proof of concept, interleukin 6 was determined using the integrated instrument. The results showed good linear correlation (R 2 =0.9938) with that obtained from Roche Electrochemiluminescence Immunoassay Analyzer (ECLIA). Moreover, the single molecule immunoanalyzer achieved a lower limit of detection (LOD) of 16 fg/mL and exhibited an 8-fold increase in sensitivity compared to ECLIA. With short turnaround time and less human intervention, the developed protein quantification system could become a valuable tool for detection of disease markers and precision medicine.
研究领域:
生物医学工程
·
临床诊断
·
分子生物学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
TALANTA
·
2023
·
IF 6.1
Xuejia Chen,Min Zhang,Xuejun Li,Jin Xu,Ying Liang
This paper discusses the first-time study of a naphthalene-based fluorescent probe—naphthalene-2,3-dicarboxaldehyde (NDA), in combination with merging-zone flow injection analysis for the automated fluorescence determination of ammonium. The determination was contingent on detecting the fluorescent product of NDA-SO 3 2- -NH 4 + , which has maximum excitation and emission wavelengths of 508 nm and 564 nm, respectively. And the possible sensing mechanism of NDA-NH 4 + was proposed. The effects of the reaction parameters, including reagent concentrations, reaction flow rate , coil length, reaction temperature, and pH were optimized. Under optimal conditions, this method afforded a sampling rate of 8 h −1 , a limit of detection of 0.045 μmol L −1 , and RSD of 3.68% (n = 14) with 1.50 μmol L −1 ammonium, and the calibration range was 0.045–6.00 μmol L −1 . Examination of the organic nitrogen interference confirmed that the method attracts minimal interference from organic nitrogen, and the stability of the NDA reagent facilitates its field application. Other exhibited advantages include low reagent consumption and high automation; the method has been utilized in the successful determination of ammonium in freshwater and rainwater. The development of NDA applications for ammonium determination also provides more options for fluorometric determination of ammonium.
研究领域:
环境科学
·
分析化学
✓ 已验证
DOI
PubMed
高影响因子
Reaction Chemistry & Engineering
·
2020
·Vol. 5
·期 9
·1751-1758
·
IF 3.441
Xiaonan Duan,Jiacheng Tu,Andrew R. Teixeira,Le Sang,Klavs F. Jensen,Jisong Zhang
An automated flow platform based on a tube-in-tube contactor and micro-packed bed reactor is developed to measure the kinetics of gas–liquid–solid hydrogenation reactions. The liquid flowing in the inner tube of the tube-in-tube contactor is rapidly saturated to ensure a constant H2 concentration before entering the micro-packed bed, which transforms the gas–liquid–solid system into a liquid–solid system. A ramping strategy is adopted in which the continuously varied residence time and the corresponding conversion data are obtained in a single experiment. Two reactions including hydrogenation of α-methylstyrene and nitrobenzene are chosen to demonstrate the accuracy and efficiency of this automated platform. Varying the flow rate ramping shows that accurate kinetic determination requires a specific range of flow rate ramps. A kinetic curve of conversion versus residence time (more than ten thousand data points) can be obtained in a single experiment within 50 min. The kinetic parameters obtained with this strategy agree well with literature values. The automated flow platform with flow rate ramping enables accurate determination of gas–liquid–solid reaction kinetics with higher efficiency and lower reagent cost compared with other methods.
研究领域:
化学工程
·
反应动力学
✓ 已验证
DOI
高影响因子
FOOD CONTROL
·
2021
·
IF 5.548
Le Song,Wenbo Zeng,An Li,Canping Pan,Ligang Pan
An automated multi-plug filtration cleanup (m-PFC) method, based on QuEChERS extraction was developed for the analysis of 48 pesticides in green tea. The carboxyl functionalized multi-walled carbon nanotubes (MWCNTs-COOH) were firstly packed in m-PFC columns and functioned as promising sorbents with better clean-up capability. The different parameters of automated m-PFC equipment and extraction conditions were optimized. The automated method integrated cleanup and filtration (through filter membrane) procedure into a single run before injected to the detection instrument. Comparison to d-SPE and manual m-PFC method, the automated method could handle a batch of samples simultaneously with better purification effect. Acceptable recoveries at three concentration levels from 71% to 114% were obtained (except carbendazim and bifenazate) with relative standard deviations lower than 18%. The proposed automated m-PFC method offered a great compromise between rapidity, convenience and efficiency. It was successfully applied for market monitoring of pesticide residues with robust analyze data.
研究领域:
食品科学
·
分析化学
✓ 已验证
产品关联
DOI
高影响因子
Advanced Intelligent Systems
·
2020
·Vol. 2
·期 4
·1900191
·
IF 0
Xinlong Pang,Haoran Zhao,Shaohua Ma
A multicomponent reaction is established toward quinazolimine derivatives, but it requires intensive human interventions in conventional reaction systems to suppress the side reactions. Herein, an automated microfluidics-based reaction system that uses a program to command the fluid conductance to perform a cascade of reactions and separation in a defined sequence is innovated. The system is composed of chained reaction modules. Within the individual reaction module, side reactions are suppressed by creating an extremely high concentration bias between the reagents via selective reagent diffusion through the porous channel wall. The reaction sequence is commanded by transporting reagents from one module to the following ones, obtaining quinazolimine derivatives with high yield and purity. The system is low cost, easy to compose, program commanded, and requires minimal human intervention once the reaction modules are assembled and reagents are loaded.
研究领域:
化学工程
·
药物合成
✓ 已验证
DOI
Microsystems & Nanoengineering
·
2025
·Vol. 11
·期 1
·1-13
·
IF 9.9
Zheng Lixiang,Li Gong,Du Henan,Li Zonghao,Xu Bingrui,Yang Fan,Mao Yanan,Wei Jing,Xie Hainan,Xie Wei,Fu Rongxin,Liu Na,Zhang Shuailong,Liu Lianqing,Li Wen Jung,Sun Yu
Automated parallel manipulation of multiple micro-objects with optoelectronic tweezers (OET) has brought significant research interests recently. However, the parallel manipulation of multiple objects in complex obstacle-dense microenvironment using OET technology based on negative dielectrophoresis (nDEP) remain a big technical challenge. In this work, we proposed an adaptive light pattern design strategy to achieve automated parallel OET manipulation of multiple micro-objects and navigate them through obstacles to target positions with high precision and no collision. We first developed a multi-micro-object parallel manipulation OET system, capable of simultaneous image processing and microparticles path planning. To overcome microparticle collisions caused by overlapping light patterns, we employed a novel adaptive light pattern design that can dynamically adjust the layout of overlapping light patterns according to surrounding environment, ensuring enough space for each microparticle and preventing unintended escapes from the OET trap. The efficacy of this approach has been verified through systematic simulations and experiments. Utilizing this strategy, multiple polystyrene microparticles were autonomously navigated through obstacles and microchannels to their intended destinations, demonstrating the strategy’s effectiveness and potential for automated parallel micromanipulation of multiple microparticles in complex and confined microenvironments.
研究领域:
微纳米技术
·
生物医学工程
·
光学工程
✓ 已验证
产品关联
DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）