Using Magnetically Responsive Tea Waste to Remove Lead in Waters under Environmentally Relevant Conditions

We report the use of a simple yet highly effective magnetite-waste tea composite to remove lead(II) (Pb[superscript 2+]) ions from water. Magnetite-waste tea composites were dispersed in four different types of water–deionized (DI), artificial rainwater, artificial groundwater and artificial freshwater–that mimic actual environmental conditions. The water samples had varying initial concentrations (0.16–5.55 ppm) of Pb[superscript 2+] ions and were mixed with the magnetite-waste tea composite for at least 24 hours to allow adsorption of the Pb[superscript 2+] ions to reach equilibrium. The magnetite-waste tea composites were stable in all the water samples for at least 3 months and could be easily removed from the aqueous media via the use of permanent magnets. We detected no significant leaching of iron (Fe) ions into the water from the magnetite-waste tea composites. The percentage of Pb adsorbed onto the magnetite-waste tea composite ranged from ~70% to 100%; the composites were as effective as activated carbon (AC) in removing the Pb[superscript 2+] ions from water, depending on the initial Pb concentration. Our prepared magnetite-waste tea composites show promise as a green, inexpensive and highly effective sorbent for removal of Pb in water under environmentally realistic conditions.SUTD-MIT International Design Center (Research Grant IDG11200105/IDD11200109)Singapore-MIT Allianc

Microfluidic engineering of water purification

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, 2017.Cataloged from PDF version of thesis.Includes bibliographical references.The demand for clean water has been increasing for several reasons, such as rapid industrialization of developing countries, environmental pollution and climate change, and development of biofuels and the resulting irrigation growth. To meet the needs for this growing demand for clean water, desalination has become an appealing solution as saline water (brackish water, seawater and brine) are the most abundant water source for most of the world. However, desalination is energy and capital intensive compared to other water treatment processes, and oftentimes it is not economically feasible. Current desalination technologies require further engineering and development to become more sustainable in the long term. My Ph.D thesis is focused on engineering of electromembrane desalination, which is a set of electrically driven desalination technologies that utilize ion transport through ion exchange membranes. We employed microfluidic platforms and numerical modeling tools for the study, for they help reveal novel insights regarding the micro-scale details that are difficult to be discovered from the conventional large-scale systems. In this thesis, we consider three topics: i) engineering of structures that enhance mass transport in electrodialyis (ED), ii) techno-economic analysis of ion concentration polarization (ICP) desalination for high salinity brine treatment, and iii) development of electrocoagulation (EC) - ion concentration polarization (ICP) desalination hybrid that removes dissolved ions and non-ionic contaminants from water in a single device. First, we employed an electrodialysis (ED) system as a model to investigate the mass transport effects of embedded microstructures, also known as spacers, in electromembrane desalination systems. The spacer engineering is especially critical for low salinity (i.e., brackish water) desalination, where the mass transport in the solution is a dominant contributor to the electrical energy consumption in the system. Parametric studies of the spacer design revealed that small cylindrical structures effectively re-distribute the local flow velocity and enhance mass transport in the system. Furthermore, we found that relative diffusivities of cation and anion in the solution should be considered in designing the spacer and that the optimal design should maximize the mass transport while keeping the effect on the hydrodynamic resistance small. Next, we built an empirical model to estimate an electrical energy consumption of ICP desalination and utilized it to obtain the water cost and optimal operating parameters for high salinity applications. We performed cost analyses on two specific cases (i.e., partial desalination of high salinity brine to the seawater level, and brine concentration for salt production) and compared the performance with mainstream desalination technologies for each application. Lastly, we combined two electrical water treatment technologies and created an EC-ICP hybrid for total water treatment, which removes dissolved ions and non-ionic contaminants from the feed solution. We demonstrated a continuous EC-ICP operation that successfully removed salt and suspended solids. Our system is flexible in terms of the system size, and the type and concentration of contaminants it can handle, and thus it can find applications as a portable water treatment system.by Siwon Choi.Ph. D

Towards a Rigorous Evaluation of Time-Series Anomaly Detection

In recent years, proposed studies on time-series anomaly detection (TAD) report high F1 scores on benchmark TAD datasets, giving the impression of clear improvements in TAD. However, most studies apply a peculiar evaluation protocol called point adjustment (PA) before scoring. In this paper, we theoretically and experimentally reveal that the PA protocol has a great possibility of overestimating the detection performance; even a random anomaly score can easily turn into a state-of-the-art TAD method. Therefore, the comparison of TAD methods after applying the PA protocol can lead to misguided rankings. Furthermore, we question the potential of existing TAD methods by showing that an untrained model obtains comparable detection performance to the existing methods even when PA is forbidden. Based on our findings, we propose a new baseline and an evaluation protocol. We expect that our study will help a rigorous evaluation of TAD and lead to further improvement in future researches

Imbalanced Data Classification via Cooperative Interaction Between Classifier and Generator

© 2012 IEEE.Learning classifiers with imbalanced data can be strongly biased toward the majority class. To address this issue, several methods have been proposed using generative adversarial networks (GANs). Existing GAN-based methods, however, do not effectively utilize the relationship between a classifier and a generator. This article proposes a novel three-player structure consisting of a discriminator, a generator, and a classifier, along with decision boundary regularization. Our method is distinctive in which the generator is trained in cooperation with the classifier to provide minority samples that gradually expand the minority decision region, improving performance for imbalanced data classification. The proposed method outperforms the existing methods on real data sets as well as synthetic imbalanced data sets.Y

Loop-mediated Isothermal Amplification Assay to Rapidly Detect Wheat Streak Mosaic Virus in Quarantined Plants

We developed a loop-mediated isothermal amplification (LAMP) method to rapidly diagnose Wheat streak mosaic virus (WSMV) during quarantine inspections of imported wheat, corn, oats, and millet. The LAMP method was developed as a plant quarantine inspection method for the first time, and its simplicity, quickness, specificity and sensitivity were verified compared to current reverse transcription-polymerase chain reaction (RT-PCR) and nested PCR quarantine methods. We were able to quickly screen for WSMV at quarantine sites with many test samples; thus, this method is expected to contribute to plant quarantine inspections

Application of computerized 3D-CT texture analysis of pancreas for the assessment of patients with diabetes.

OBJECTIVE:To evaluate the role of computerized 3D CT texture analysis of the pancreas as quantitative parameters for assessing diabetes. METHODS:Among 2,493 patients with diabetes, 39 with type 2 diabetes (T2D) and 12 with type 1 diabetes (T1D) who underwent CT using two selected CT scanners, were enrolled. We compared these patients with age-, body mass index- (BMI), and CT scanner-matched normal subjects. Computerized texture analysis for entire pancreas was performed by extracting 17 variable features. A multivariate logistic regression analysis was performed to identify the predictive factors for diabetes. A receiver operator characteristic (ROC) curve was constructed to determine the optimal cut off values for statistically significant variables. RESULTS:In diabetes, mean attenuation, standard deviation, variance, entropy, homogeneity, surface area, sphericity, discrete compactness, gray-level co-occurrence matrix (GLCM) contrast, and GLCM entropy showed significant differences (P < .05). Multivariate analysis revealed that a higher variance (adjusted OR, 1.002; P = .005), sphericity (adjusted OR, 1.649×104; P = .048), GLCM entropy (adjusted OR, 1.057×105; P = .032), and lower GLCM contrast (adjusted OR, 0.997; P < .001) were significant variables. The mean AUCs for each feature were 0.654, 0.689, 0.620, and 0.613, respectively (P < .05). In subgroup analysis, only larger surface area (adjusted OR, 1.000; P = .025) was a significant predictor for T2D. CONCLUSIONS:Computerized 3D CT texture analysis of the pancreas could be helpful for predicting diabetes. A higher variance, sphericity, GLCM entropy, and a lower GLCM contrast were the significant predictors for diabetes

Deciphering the critical degradation factors of solid composite electrodes with halide electrolytes: Interfacial reaction versus ionic transport

Recently, halide-type Li+ conductors have been revisited for their use in all-solid-state batteries (ASSBs) owing to their stability at high potentials. However, the realization of ASSBs is hindered by the fast performance decay of composite cathodes. From a comparative study using halide and sulfide solid electrolytes (SEs), herein, we reveal the critical degradation factors of halide-SE-based cathodes, which are different from the conventional findings of sulfide-SE-based cathodes. By using impedance decoupling combined with scanning spreading resistance microscopy and force spectroscopy, we elucidate the mechanisms behind the SE-dependent degradation of single-particle LiNi0.8Co0.1Mn0.1O2 (NCM) composite cathodes. Impedance analyses show that NCM-Li6PS5Cl (LPSCl) and NCM-Li3InCl6 (LIC) exhibit considerable increase in interfacial impedance and Li+-transport impedance, respectively, upon cycling. Based on the combined experimental and computational study of microscopic interfacial and mechanical properties, we demontrate that the degradation of NCM-LPSCl originates primarily from the formation of resistive interphases, while the crucial degradation factor of NCM-LIC is the cracking-induced mechanical deformation of the LIC under pressure. Finite element analysis results further reveal how the deformation behavior of the SE materials influences the formation and propagation of cracks in composite cathodes during cycling. This study provides insights into the design of materials and electrodes for ASSBs with high power capabilities and long cycle lifetimes. © 2023FALS

Unravelling inherent electrocatalysis of mixed-conducting oxide activated by metal nanoparticle for fuel cell electrodes

Highly active metal nanoparticles are desired to serve in high-temperature electrocatalysis, for example, in solid oxide electrochemical cells. Unfortunately, the low thermal stability of nanosized particles and the sophisticated interface requirement for electrode structures to support concurrent ionic and electronic transport make it hard to identify the exact catalytic role of nanoparticles embedded within complex electrode architectures. Here we present an accurate analysis of the reactivity of oxide electrodes boosted by metal nanoparticles, where all particles participate in the reaction. Monodisperse particles (Pt, Pd, Au and Co), 10 nm in size and stable at high temperature (more than 600 °C), are uniformly distributed onto mixed-conducting oxide electrodes as a model electrochemical cell via self-assembled nanopatterning. We identify how the metal catalysts activate hydrogen electrooxidation on the ceria-based electrode surface and quantify how rapidly the reaction rate increases with proper choice of metal. These results suggest an ideal electrode design for high-temperature electrochemical applications. © 2019, The Author(s), under exclusive licence to Springer Nature Limite