bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of Li Metal Plating and Dissolution on Graphite Electrodes
Authors: Hein Simon , Hogrefe Christin , Waldmann Thomas , Danner Timo , Richter Karsten , Wohlfahrt-Mehrens Margret , Latz Arnulf
Published: July 2021

Li plating, meaning the deposition of metallic Lithium on the negative electrode is considered as one of the major degradation mechanisms in Li-Ion batteries. Therefore, understanding the processes which occur between metallic Lithium and state-of-the-art electrode materials, mainly Graphite, is important to improve the life-time of Li ion cells.

Lithium plating and stripping is explored using an electrochemical model, which explicitly includes the growth of plated lithium as a competing process to the direct intercalation lithium ions [1]. The model is combined with a thermodynamically consistent transport theory and implemented in the simulation framework Battery and Electrochemistry Simulation Tool (BEST). The extended framework is used to conduct a first study regarding the impact of an inhomogeneous SEI growth on the deposition of metallic lithium.

Moreover, we will present recent work on simulations of model experiments investigating the dissolution of lithium deposits on Graphite electrodes [2]. Different electrolyte formulations and configurations of a lithium metal disk on the electrode are investigated to evaluate different lithium transport pathways. In each experiment some pathways are intentionally blocked, thus yielding interesting insights into the dissolution mechanism. Post-mortem analysis on the Graphite electrodes is performed using Raman spectroscopy and glow-discharge optical emission spectroscopy (GD-OES) revealing the spatial distribution of the lithium at the end of the dissolution experiment. At the same time measurements of the open circuit voltage are performed to monitor the progress of the dissolution process. Our simulations are in very good qualitative agreement with measured OCV curves and the observed lithium distributions.

Therefore, the simulations provide additional “in-operando” insights to the plating as well as the dissolution of a metallic lithium phase. With the mechanistic insights optimization of the electrode and cell architecture can be deduced which help to improve the life-time of Li ion cells.

[1] S. Hein, T. Danner, and A. Latz, “An electrochemical model of lithium plating and stripping in lithium-ion batteries,” ACS Appl. Energy Mater., vol. 3, no. 9, p. acsaem.0c01155, Jul. 2020.

[2] C. Hogrefe et al., “Mechanistic Details of the spontaneous Intercalation of Li Metal into Graphite Electrodes,” J. Electrochem. Soc., Nov. 2020.
Application of Synchrotron Diffraction to Understand Lithium Plating Caused By Extremely Fast Charging
Authors: Charalambous Harry , Wiaderek Kamila Magdalena , Ren Yang
Published: July 2021

Lithium plating is a serious safety concern as the segregation of lithium in metal form results in accelerated capacity fade and creates sites for potential dendrite growth. Processes involving high current densities and low temperatures have been shown to cause plating. However, the characteristics and mechanisms resulting in the onset of plating are not well understood. High energy synchrotron diffraction is an effective method of locally probing lithium plating, anode, and cathode due to its high flux, high penetration depth, and minimal destructive interaction in a functioning battery. In this study, we present the results of a periodic mapping of a high loading LiNi0.5Mn0.3Co0.2O2 cathode, graphite anode pouch cell operated in extremely fast charging mode over extended cycle life. Initial nucleation of plating is correlated to heterogeneity in lithium intercalation while the spread of plating regions during cycle life is mapped and quantified.
Ex-Situ and in-Situ Electron Microscopy and Spectroscopy Diagnosis of Interfacial Process Governed Electrode Stability in Lithium Ion Batteries
Authors: Wang Chongmin
Published: July 2021

Over the last two decades or so, we have witnessed tremendous progress on the development of aberration corrected transmission electron microscopy and scanning transmission electron microscopy. As a result of this development, imaging and spectroscopy of materials at atomic scale appears to be a routine practice. The questions now come to how we extend the microscopy and spectroscopy methodologies to analyze materials at or near realistic condition, typically such as real time observation of mass transport, microstructural evolution, charge and ion transport process. In this presentation, I will focus on in-situ S/TEM techniques that developed for probing into the structural and chemical information of energy storage materials, highlighting direct observation of structural evolution, phase transformation and their correlation with mass, charge and electron transport, providing insights as how active materials failure during the cyclic charging and discharging of a battery. In particular, I will focus on recent progress on ex-situ, in-situ and operando S/TEM studies for probing into the structural and chemical evolution of interfacial process in lithium ion batteries. I will highlight several recent key observations, which appear to be well documented, while essentially are poorly understood. It would be expected that this presentation can stimulate new ideas as how to attack these bottlenecks for optimized tailoring of cathode and anode for stable cycling of batteries.
Machine Learning for the Quantification and Identification of Natural Gas from Mixed Potential Electrochemical Sensors
Authors: Tsui Lok-kun , Halley Sleight , Agi Kamil , Garzon Fernando H
Published: July 2021

Methane emissions from natural gas pipeline infrastructure contribute to over 2 billion dollars in losses in the US and 1.6 x 108 metric tons of CO2-equivalent per year.[1-2] Widely deployable sensors are needed to quickly identify and repair leaks so that their environmental and economic impact can be minimized. Mixed potential electrochemical sensors (MPES) are a low cost, highly robust system which can be deployed in the field. Mixture identification and quantification using sensor signals produced by MPES devices is challenging due to cross interference effects and complicated by the presence of interferent methane sources including wetlands and agricultural resources.

We have developed a machine learning system with artificial neural networks using MPES devices as inputs and either concentration or mixture label as outputs. We have previously demonstrated using this approach to automatically decode sensor signals associated with automotive emissions gas mixtures [3-4]. Artificial neural networks created using the Google Tensorflow library for the Python programming language were trained on MPES sensor signals to identify and quantify mixtures as natural gas, CH4 only, and a CH4+NH3 mix as a simulant for bovine emissions. The results we have collected showed >99% test accuracy in identification of these gas mixtures as shown in the confusion matrix in Figure 1 in the concentration range of 1000-4000 PPM CH4 and 75-255 PPM NH3. Optimization of the ANN architecture to minimize processing time and facilitate deployment of machine learning onto portable hardware will also be presented. We will also compare the performance of ANNs to alternate ML techniques.

This work was supported by the US Department of Energy under award DE-FOA-0031864.

[1] A.J. Marchese, T. L. Vaugh, D. J. Zimmerle, D. M. Martinez, L. L. Williams, A. L. Robinson, A. L. Mitchell, R. Subramanian, D. S. Tkacik, J. R. Roscioli, S. C. Herndon. Science. 7204 (2018).

[2] Kort, E. A.; Frankenberg, C. Costigan, K.R.; Lindenmaier, R.; Dubey, M. K; Wunch, D. Geophys. Res. Lett, 2014, 41, 19, 6898

[3] L. Tsui, A. Benavidez, P. Palanisamy, L. Evans, F. Garzon, Electrochim. Acta 283 (2018) 141–148.

[4] L. Tsui, A. Benavidez, P. Palanisamy, L. Evans, F. Garzon, Sens. Act. B: Chem. 249 (2017), 673-684

Figure 1. Confusion matrix for (a) natural gas simulant, (b) CH4, (c) NH3, and (d) CH4+NH3. Mixtures (b) and (d) serve as surrogates for wetlands and agricultural bovine emissions respectively.

Figure 1
Novel Data Science Driven Chemical Agent Sensors: Towards Better Discrimination in Complex Environments
Authors: Uzarski Joshua R , Wiederoder Michael S. , Weiss Matthew , Moore Alexander , Paffenroth Randy
Published: July 2021

Chemical agents remain a persistent threat to both Warfighters and civilian personnel in both combat and non-combat environments. While many useful detection technologies exist to provide early warning, many of them suffer from similar drawbacks. Most common are unacceptable false positive response rates and inability to discriminate target analytes in complex or obscurant-laden environments. A typical approach to this problem is to develop material solutions for more specific and sensitive sensors. While useful, these solutions are often too expensive, not practical, or non-deployable. Our approach fuses both material and data science to extend the power of multiplexed sensor arrays towards more accurate and faster detection and discrimination.

This presentation will discuss our approach towards vapor analyte detection using multiplex array systems combined with novel data science approaches. For vapor phase detection, sorptive and conductive graphene-based nanocomposite polymer films as well as select 2D conductive materials are used for semi-selective affinity towards chemical agent simulants in binary mixtures with common obscurants. Response data are pre-processed using a novel algorithm called the Variational Autoencoder Kalman Filter and the entire response dataset is used to train neural networks for analyte discrimination. To inform the neural networks to facilitate accurate and fast analyte discrimination, datasets far exceeding the capability of laboratory measurements are needed. Here too we describe our approach to generate simulated data to supplement and augment the classification algorithm machine learning process. We lastly demonstrate this approach to discriminate binary and tertiary mixtures of analytes with both similar and different chemical similarity both in and out of the precise of common environmental interferents.
Estimation of Soil Moisture and Earth Resistivity Using Wenner’s Method and Machine Learning
Authors: Cussei Valdimiro Cassule
Published: July 2021

The research presented in this dissertation discusses a novel approach to address the corrosion of underground metallic structures. The system consists of using Wenner’s four electrodes method to measure the electrical resistivity of the soil (e.g., clayey silt and clay), applying two machine-learning algorithms (k Nearest Neighbor (Knn) and Supervised Vector Machine (SVM)) to predict the type of soil, and help engineers to leverage the extracted parameters to select the best material that withstands corrosion in that specific environment. A dataset of 162 sample points was obtained from different kinds of literature (142 training, and 20 testing points). The results show that given the electrical resistivity of soil and its moisture, the k nearest neighbor model is capable of predicting the type of soil with accuracy, error rate, sensitivity, specificity, and precision of 70%, 30%, 64%, 83%, and 90% respectively. In contrast, the support vector machine model was not able to perform soil prediction, presenting an error rate and accuracy of 44.1% and 55.9 % respectively. This dissertation also provides suggestions such as increasing the number of sample points to improve the performance of the machine learning algorithms.
(Invited) Nanoscale Engineering of Plasmonic Materials for Biosensing and Bioimaging
Authors: Xie Fang
Published: July 2021

Early diagnosis plays an increasingly significant role in current clinical drive. Detection, identification, and quantification of low abundance biomarker proteins form a promising basis for early clinical diagnosis and offer a range of important medical benefits. Amplification of light from NIR fluorophores by coupling to metal nanostructures, i.e. Metal Induced Fluorescence Enhancement (MIFE), represents a promising strategy for dramatically improving the detection and quantification of low abundance biomarker proteins, and potentially increase already sensitive fluorescence-based detection by up to three orders of magnitude. The amplification of the fluorescence system is based on interaction of the excited fluorophores with the surface plasmon resonance in metallic nanostructures. The enhanced fluorescence intensity due to the existence of metal nanostructures makes it possible to detect much lower levers of biomarkers tagged with fluorescence molecules either in sensing format or for tissue imaging. The first part of my talk will focus on some recent developments of plasmonic metal nanostructures by both "top-down" and "bottom up" methods. I will then discuss the prepared plasmonic nanostructures in the applications of biosensing and bioimaging, with the emphasis on plasmonic enhancement towards NIR I and NIR II regions.
Electrochemical Immuno-Biosensors on Nanostructured Electrodes for Rapid Sensitive Detection of Disease Biomarkers
Authors: Mahshid Sahar Sadat
Published: July 2021

Development of rapid tests for quantitative detection of analytes in complex matrices, plays an important role in medical diagnostics, prognostics and therapeutics. Current methods for molecular diagnostics are time-consuming and multiple-step reliant on well-trained technicians and fully-equipped laboratories to provide quantitative detection of biomarkers. In this case, the challenges to overcome the sensitivity and selectivity of working directly in biological fluids in a timely manner have always been the main step for the development of such rapid tests.

Electrochemical sensors, analogous to glucometer, are known to be rapid with the ability to provide direct electronic signal without any interference from the biological phenomena. When functionalized with specific biological substances, they intend to provide the required specificity in addition to signal selectivity in biological fluids. Inspired by nature, we design biorecognition probes that are combined with newest advancement in the engineering for the development of electrochemical immune-biosensors. These molecular recognition probes are designed using the ability of antibodies to bind antigens, and DNA construct to hybridize to the complementary construct, to create specificity for direct detection in complex media. On the other hand, we rely on the innovative approaches in nanomaterials, surface sciences, and self-assembly techniques to improve the conductivity and sensitivity of electrode surface. This includes the incorporation of high-curvature nanostructured microelectrodes that helps with the efficiency of molecular interactions at the surface and the transfer of electrons for the ease of signal transduction.

In this regard, we fabricate small-scale nanostructured electrodes and engineer the surface for the immobilization of the biomolecular monolayer at the interface to provide the desired specificity for biomarkers in real biological samples, e.g. whole blood. We adapted our nano-bio-sensors for translational applications such as (1) at-line monitoring of signaling proteins in hematopoietic stem cell expansion, (2) rapid diagnosis of pathogenic infections through quantitative detection of antibodies directly in patient samples, and (3) rapid diagnosis of inner ear disorders based on the detection of blood biomarkers. We showed that our electrochemical immune-biosensors are capable of detecting at therapeutic concentrations with tunable ranges while performing in a 10 µL sample within less than 30 minutes.
Aptamer-Modified Electrode Biosensors for Npy Detection Using Methylene Blue Redox Probe
Authors: Martinez Lyza , Lopez Luis F. , Cunci Lisandro
Published: July 2021

A biosensor is a device that can determine the concentration or presence of chemicals, such as neurotransmitters and neuropeptides. Certain excitatory neurotransmitters and neuropeptides can be measured by Methylene blue (MB), a synthetic dye that stains to negatively charged cell components. For the modification process in this work, aptamers are used because they possess the advantage of binding to any given target molecule and, when they bind, they undergo conformational changes, which is where MB comes into play. This research focuses on the modification of the surface of Gold (Au) and Highly Oriented Pyrolytic Graphite (HOPG) electrodes using MB as a redox label probe for the detection of neurotransmitters and neuropeptides in aptamer-modified electrodes. Electrochemical Impedance Spectroscopy (EIS) was used to understand the adsorption properties of molecules that stick to the surface of the electrode and Atomic Force Microscopy (AFM) was used to measure the topography of the electrodes before and after the aptamer modification. As results, we were able to prove that AFM cannot monitor the changes on the surface of the Au electrodes with the different modifications due to the roughness of the surface, and that, electrochemically, the capacitance of the gold electrode decreases at higher concentrations of NPY. Different NPY measurements were made, ranging from femtograms to picograms, and different molecules such as dopamine, epinephrine, and PYY were also tested to determine if the sensor system has the same affinity with different types of molecules. These results give us a better understanding of the use of these techniques for the monitoring of biomolecules.
(Keynote) Artificial Intelligence Biosensors: Challenges and Prospects
Authors: Xu Tailin , Zhang Xueji
Published: July 2021

Artificial intelligence (AI) and wearable sensors are two fields that are instrumental in realizing the goal of precision medicine—tailoring the best treatment for individual patients. Recent development between these two fields is enabling better patient data acquisition and improved design of wearable sensors for monitoring the wearers’ health, ﬁtness, and their surroundings. The growing field of wearable sensors aims to tackle the limitations of centralized, reactive healthcare by giving individuals insight into the metrics of their own physiology. However, assessing the effectiveness of a therapeutic platforms on disease is extremely complex, due to the massive quantities of data generated by biomedical devices. Integration of AI approaches can bridge this gap, using pattern analysis and classification algorithms for improvement of diagnostic and therapeutic accuracy. The future AI-biosensors (AI wearable sweat biosensor, AI- eatable biosensor, AI-glass biosensor, AI-implantable biosensor et al.) mainly have the function of AI-diagnosis (Diagnostic algorithms in the microprocessor can verify the output of the sensor and present the diagnostic information), Big data processing (Use of self-contained space for historical data and various necessary parameters of data storage to greatly improve the performance of the controller.) and Self-learning/adaptive (Embedded microprocessor with advanced programming function. In the working process, the AI-biosensor can reconstruct the structure and parameters according to certain behavioral criteria, and has adaptive functions)
(Invited) Skin-Interfaced Wearable Sweat Biosensors
Authors: Gao Wei
Published: July 2021

The rising research interest in personalized medicine promises to revolutionize traditional medical practices. This presents a tremendous opportunity for developing wearable devices toward predictive analytics and treatment. In this talk, I will introduce our recent advances in developing fully-integrated skin-interfaced flexible biosensors for non-invasive molecular analysis. Such wearable biosensors can continuously, selectively, and accurately measure a wide spectrum of sweat analytes including metabolites, electrolytes, hormones, drugs, and other small molecules. These devices also allow us to gain real-time insight into the sweat secretion and gland physiology. The clinical value of our wearable sensing platforms is evaluated through multiple human studies involving both healthy and patient populations toward physiological monitoring, disease diagnosis, and drug monitoring. This talk will also feature our very recent works on laser-engraved lab on the skin and biofuel powered battery-free electronic skin toward metabolic/nutritional management as well as dynamic stress monitoring. These wearable and flexible devices could open the door to a wide range of personalized monitoring, diagnostic, and therapeutic applications.
Development of an Improved Immunosensor for Fast Electrochemical Determination of Progesterone
Authors: Disha Disha , Kumari Poonam , Nayak Manoj Kumar , Kumar Parveen
Published: July 2021

Monitoring the endocrine disrupting lipid-compounds such as progesterone (a gonadal steroid hormone) is becoming vital in environmental as well as clinical samples because of the deleterious effects of its excessive consumption. Herein, our present work illustrates a label free electrochemical detecting approach employing Magnetic Graphene Oxide as electrode casting nanomaterials which offered the characteristics of enlarged surface area and plenty of sites for bio receptor immobilization. Further we also characterized the synthesized nanomaterials via FT-IR, HR-TEM, XRD and RAMAN. Implementing the electrochemical techniques such as Cyclic Voltammetry and electrochemical impedance spectroscopy along with the nanomaterials generated a simplified, fast and sensitive determination of the target. With optimized parameters, this developed bio sensing platform demonstrates a wide linearity ranging from 10-6 M to 10-14 M with 0.173 pM as detection limit, excellent selectivity, sensitivity and a high recovery in real water samples. The stated work successfully signified the potential of developed immunosensor in real applications by giving good recovery for detecting progesterone in tap water samples.

Figure 1
Catechol-O-Methyl Transferase (COMT) Activity Detection Using Metal Oxide Electrodes
Authors: Lisdat Fred , Göbel Gero
Published: July 2021

Parkinson’s disease is one of the most frequent diseases of the central nervous system with rather severe consequences for patients. Since the disorder can not be cured, the dopamine level in the brain needs to adjusted. Here several key enzymes of the dopamine metabolism [e. g. catechol-O-methyl transferase (COMT)] are targets for administered drugs. However, the efficiency of the treatment is decreasing with time. Consequently a monitoring of the actual activity of these enezmyes and an adjustment of the pharmaceutical treatment would be beneficial to prolong the treatment effects.

In this study, an electrochemical approach is introduced for activity determination of the COMT enzyme. As detection method differential pulse voltammetry (DPV) has been used exploiting an improved signal to noise ratio. Activity determination is based on the selective detection of one substance in the reaction scheme of the enzyme – here dopamine. As electrode material fluorine doped tin oxide (FTO) has been elucidated since it is characterized by a clear discrimination between the substrate and the product of the COMT [1]. This can be achieved without additional layers on top of the electrode. The response is characterized by a rather high stability of the dopamine signal during consecutive measurements and a linear dependency of the peak currents on the dopamine concentration in the range of the maximum reaction rate of COMT [2]. Furthermore it has been detected that redox active interferences such as ascorbic acid do not disturb the analysis.

Despite these advantageous results, it has been found that the electrochemical dopamine oxidation in the complete activity assay is influenced by each of the added essential assay components, even though none of the added components reveal a current signal at the FTO electrode itself. After adjusting the potential range of the electrochemical analysis and the solution composition, these effects can be circumvented.

Consequently, by following the dopamine concentrations during COMT action, it can be shown that the

activity of the enzyme can be detected by using DPV at a FTO electrode. Experiments with different amounts of the enzyme further demonstrate that activity quantification is feasible.

References

[1] G. Göbel, A. Talke, F. Lisdat, Electroanalysis, 2018, Vol. 30 (2), p. 225-229

[2] G. Göbel, A. Talke, U. Ahnert, F. Lisdat, ChemElectroChem, 2019, Vol. 6 (17)
Synergistic Effects of Au and SnO2 Nanoparticles Decorated on WS2 Nanosheets for Flexible, Room-Temperature CO Gas Sensing
Authors: Kim Jae-Hun , Kim Sang Sub , Saito Noriko
Published: July 2021

Two-dimensional (2D) materials such as graphene and graphene oxide are desirable for sensing applications owing to their high surface-to-volume ratio. Recently another class of 2D materials namely transition metal dichalcogenides (TMDs) with semiconducting properties have gained extensive attention for gas sensing studies due to their high surface area and excellent electronic and catalytic properties. TMDs form layered structures, where adjacent layers are held together by weak van der Waals forces. Accordingly, they can be easily exfoliated into individual 2D layers with high surface area which is a merit for sensing applications.

WS2 is a promising 2D TMD for sensing applications thanks to high surface area and excellent electrical properties. However, for sufficient sensing applications its sensitivity needs to be improved more. A good strategy for that purpose is to functionalize with noble metal and metal oxide nanoparticles (NPs). NPs can make additional charge depletion zone in WS2 nanosheets, thereby amplifying their resistance modulation during interaction with gas molecules. Furthermore, NPs can provide a spillover effect; facilitating adsorption, dissociation, and transfer of target gases to WS2 nanosheets surface. This can lead to improved sensitivity towards a specific gas.

In this study, WS2 nanosheets that are bare or decorated with Au, SnO2, or a combination of Au and SnO2 were realized on flexible polyamide substrates. The fabricated sensors were operated for CO gas sensing in applied-voltage-induced self-heating mode at room temperature (24 ºC). Not only optimal applied voltage was varied for the sensing of different gases, but also that the sensors behaved uniquely in response to CO gas. Therefore, the optimized applied voltage for the fabricated sensors and their room temperature sensing characteristics were investigated. Furthermore, we investigated that tilting, bending and stretching conditions to the optimized gas sensor. Also, we suggested that the enhanced response was related to the formation of Au-WS2 and Au-SnO2 Schottky junctions, n-SnO2-n-WS2 heterojunctions, and the catalytic performance of Au NPs towards CO gas. The results obtained in this study provide new avenues towards fabrication of flexible, low power gas sensors using metal chalcogenides.
Membrane-Based Electrochemical Sensors for Detecting Internal Corrosion Risk of Natural Gas Pipelines
Authors: Ziomek-Moroz Malgorzata , Duffy Timothy , Hall Derek M , Lvov Serguei
Published: July 2021

Internal corrosion monitoring programs are essential for the safe management of natural gas transmission pipelines. Electrochemical technologies can provide reliable, real-time monitoring of key risk factors, such as solution conductivity, corrosion rates, and localized corrosion risk. A novel, membrane-based sensor is being developed to perform electrochemical tests in both aqueous and gaseous environments, allowing for continuous operation and data collection within a pipeline environment. This sensor can be used to determine water content in the presence of a number of gases (CH4, H2S, CO2), to monitor the pipeline’s corrosion rate with and without a condensed phase, and to provide localized corrosion data in the presence of a pitting agent. Here, we explore the sensor’s design, validation through finite-element analysis, and performance data for general and localized forms of corrosion.
SO2 Gas Sensor Based on LATP Solid Electrolyte
Authors: Fung Kuan-Zong , Tsai Shu-Yi
Published: July 2021

The emission of SO2 mainly comes from the burning of fossil fuels such coal and sulfur-containing oil. Thus, the source of SO2 emission may be contributed from power plants or steel making factories.

Exposures to SO2 can harm the human respiratory system and make breathing difficult. People suffered by asthma are sensitive to these effects of SO2. To improve air quality, the concentration of SO2 is typically limited by national and/or regional standards to reduce emissions of SO2. Therefore, the accurate detection of SO2 is important. Electrochemical solid state sensors are known to provide reliable and stable signals based on the use of solid electrolytes. Oxygen sensors based on oxygen-conducting yittria-stabilized zirconia have shown their wide applications. In this study, a solid state SO2 sensor are developed using Li-conducting Li1.3Al0.3Ti1.7(PO4)3 (LATP). Li2SO4 is used as electrode. With the application of adequate voltage, Li2SO4 may be formed at the surface exposed to SO2-containing atmosphere. Thus, the current measured from the sensors is expected to be proportional to the concentration of SO2. The dependence of SO2 concentration, temperature, and electrode microstructure will be analyzed and discussed.
pH Micro-Sensor from IrOx SECM Microelectrode for Local pH Measurement While Chromium Electrodeposition
Authors: Dasque Ariane , Gressier Marie , Taberna Pierre-Louis , Menu Marie-Joelle
Published: July 2021

In this work, it will be presented the chromium electrodeposition mechanisms with the use of a Scanning ElectroChemical Microscopy (SECM) micro-electrode. Among several factors, the pH is key to achieve even a metallic deposit. pH buffers and complexing agents are often used for this purpose [1] but in the vicinity of the electrode, at the electrode/electrolyte interface, strong variations are highly likely to occur. To this respect, since pH is a key parameter, a pH micro-electrode is intended to be developed to scan the pH gradient upon the electrodeposition of chromium. The first part of this work is so devoted to the pH micro-electrode realization from microelectrode on which iridium oxide is deposited. Iridium oxide has been reported to be suitable for local pH sensing [2-4]. Different parameters have been studied such as IrOx thickness and thermal treatment. The addition of Nafion has been assessed as well to achieve a tradeoff between fast response time, good selectivity and good stability [5]. An optimized IrOx micro-electrode has been obtained and used as SECM micro-electrode to get the evolution of the pH at the electrode/electrolyte interface upon electrodeposition. Different micro-electrode diameters have been used to improve the resolution. These results are promising and will allow going further to the development of chromium electrodeposition electrolyte helping to select the different complexing agents.

[1] D. Del Pianta et al. Determination of the chromium(III) reduction mechanism during chromium electroplating. Electrochimica Acta (2018) 234-241.

[2] H. A. Elsen et al. Effects of electrodeposition conditions and protocol on the properties of iridium oxide pH sensors electrodes. J. Electrochem Soc. 156 (2009).

[3] C. S. Santos et al. Fabrication and use od dual-function iridium oxide coated gold SECM tips. An application to pH monitoring above copper electrode surface during nitrate reduction. Electroanalysis 28 (2016) 1441-1447.

[4] Z. Zhu et al. A fabrication of iridium oxide film pH micro-sensor on Pt ultramicroelectrode and its application on in-situ pH distribution of 316 stainless steel corrosion at open circuit potential. Sensors and Actuators B 25 (2018) 1974-1982.
Controlled Synthesis of Multi-Shelled SnO2 Hollow Microspheres for High-Sensitive MEMS Formaldehyde Sensors
Authors: Cai Haijie , Xu Jiaqiang
Published: July 2021

Multi-shelled hollow micro/nanostructures materials preferentially possessing high surface area demand attention due to their expectable sensing performances. However, controlled synthesis of multi-shelled hollow micro/nanostructures remains quite challenging. In this work, multi-shelled hollow SnO2 microspheres with tunable interior structure were successfully prepared by using alkali-treated carbonaceous microspheres as the templates following with a calcination process. The single-, double-, and multi-shelled SnO2 hollow nanospheres were selectively tailored by the simple regulation of Tin precursors concentration, and used as sensing material in high-performance MEMS sensors. The gas sensitivity test results indicated that the multi-shelled architecture displayed significantly enhancing formaldehyde detection properties due to large specific surface area, abundant interfaces, thin shells, and high proportion porous structure, which acts synergistically to the gas adsorption quantity and transport rate.

Figure 1
Hydrogen Sulfide Gas Sensor Based on a V2O3/NiO Composite
Authors: Qiu Tiantian , Xu Jiaqiang , Cheng Zhixuan
Published: July 2021

Hydrogen sulfide（H2S）is a colorless and odorous gas. Abnormal H2S concentration may be related to Alzheimer's disease, ischemia, Down syndrome, bad breath and other diseases. Therefore, rapid、sensitive and highly selective detection of H2S is essential for the early diagnosis of these diseases. In the research, a two-dimensional nanosheet self-assembly structure based on NiO-V2O3 was developed to construct a high-performance H2S gas sensor. Morphological and structural characterization proved that the NiO-V2O3 composite is a three-dimensional flower-like porous microspheres self-assembled from two-dimensional nanosheets with high surface area and rich active sites. The sensor can quantitatively detect H2S gas at ppb level. When exposed to 500 ppb H2S gas at the optimal working temperature of 200°C, the highest response of the sensor is 65, and the response time and recovery time are 8 s and 25 s, respectively. The sensor also has excellent stability, moisture resistance and selectivity, and has a low detection limit (20 ppb). Considering these advantages, the NiO-V2O3 sensor is expected to be used for the detection of H2S in the early diagnosis of certain diseases.

Figure 1
NO2 Gas Sensing Characters of Polycrystaline ZnO Nanorods
Authors: Ren Xiaowei , Tang Zilong
Published: July 2021

ZnO has attracted much attention as an important semiconductor material, since it has a wide band gap (3.4eV), and excellent stability. It has been extensively researched to detect many gases, such as H2, C2H5OH, NH3 and VOC(volatile organic compounds). Herein, we developed a MOF derived ZIF-8 coated ZnO nanorods(ZnO@ZIF) as a precursor by solvethermal route, then calcined at 500 ºC in air, during the process, the exposure facets of ZnO nanorods have changed. The polycrystaline ZnO nanorods shows higher response to 1-5 ppm NO2 at 140ºC compared with single crystal ZnO nanorods. This provides a new etching way to change the surface facets by using ZIF coated and calcined in air.
Electrochemical Detection of Biomolecules for Agriculture and Farming Applications
Authors: Durairaj Sharmila , Chen Aicheng
Published: July 2021

There is an increasing interest in developing efficient techniques to detect agri-based biomolecules and biomarkers to improve food production and quality. Electrochemical sensors and biosensors are desirable over conventional analytical techniques due to the advantages of instrumental simplicity, rapid response, high sensitivity, cost-effectiveness, and portability [1-4]. The development of nanomaterials has paved the way for their applicability in designing high-performance electrochemical sensing devices for agriculture and environmental applications. Hydroxyproline (Hyp) is a significant amino acid present in connective tissues and extracellular matrix in all animal cells. Hyp's quantitative analysis plays a vital role in the quality testing of chicken, swine, and beef meat in farming. In the animal farming industry, sodium metabisulfite (SMBS) is used as a feed additive to control the effect of deoxynivalenol (DON), a mycotoxin from Fusarium Species. The monitoring of SMBS is essential as its over-dosage may cause significant side effects like stomach upset or heaviness. In this presentation, the synthesis of gold nanoparticles and graphene-based nanocomposites, and their applications for the detection of Hyp and SMBS are highlighted. Our study has shown that gold nanoparticles exhibit high sensitivity (8.5 μA/μM cm-2), a low limit of detection (2.6 μM), and a wide linear range for the detection of Hyp. The fabricated gold and fluorine-doped reduced graphene oxide nanocomposites show high-performance for detecting SMBS in different digestive fluids such as stimulated salivary fluid and simulated gastric fluid. The roles of nanomaterials in the electrochemical sensing applications are also discussed.

[1] V.S. Manikandan, B.R. Adhikari, A. Chen, Analyst,
143, 4537-4554 (2018).

[2] Z. Liu, V.S. Manikandan, A. Chen,Curr. Opin. Electrochem., 16, 127-133 (2019).

[3] S. Durairaj, B. Sidhureddy, A. Chen, J. Electrochem. Soc.,
167, 167511 (2020).

[4] J. van der Zalm, S. Chen, W. Huang, A. Chen, J. Electrochem. Soc.,
167
, 037532 (2020).
(IMCS Second Place Best Paper Winner) Investigation of Room Temperature Ionic-Liquid (RTIL) Modified Electrode for Decoupling Soil Electrochemistry
Authors: Dhamu Vikram Narayanan , Paul Anirban , Muthukumar Sriram , Prasad Shalini
Published: July 2021

Room temperature ionic liquid (RTIL) is a unique zwitter-ionic compound, that possesses excellent physical and chemical properties, which enables electrochemical applications such as to be utilized as a transducer for probing a complex matrix such as soil. The wide electrochemical window and elevated double layer capacitance of RTIL helps to gauge soil parameters which is helpful to understand soil state. In this work we investigate the utility of RTIL modified electrodes as viable sensors for decoupling soil electrochemistry. Soil plays the key role in plant and crop production and is a vital parameter in the ecological structure of the planet and indispensable in the food ecosystem cycle. Soil health monitoring in the near past has been highly qualitative and speculative with more recent advancements still trying to fill the void of a holistic soil profile. In fields and crop-circles, testing methods to perform in-situ profiling however from one lab is likely to vary with another and hence results are not universally compatible. Additionally, these normalized techniques ideally involve empirical approaches, extensive sample preparation which adds on to a temporal factor along with equipment for extraction and subsequently-analysis. This therefore-stimulates the need for a testing methodology that is capable of rapid analysis in an in-situ environment that can be applicable universally.

In this paper, we focus on: a rapid electrochemical point probing mechanism that acts as a soil state evaluation platform via a 3-electrode sensor modified by a widely characterized-RTIL [BMIM] [BF4] interfacial transducer medium. The proposed quantitative model –‘DENSE’ probes the soil diffuse double layer (DDL) dielectric to evaluate a thorough chemical profile of the soil matrix. The experimental design was implemented to capture the effect of electroactive species in the soil matrix altered by adding nutritional amendments. Non-faradaic probing was then performed in this design to gauge the inherent capacitive modulations of the soil system as a function its compositional changes. Therefore, by looking at the rate of electrochemical activity and inherent soil dielectric changes driven by an RTIL interfacial layer, it is possible to decouple information on nutrient availability in soils with potential for application towards temporal soil analysis.

Figure: (A) Equivalent-circuit (DENSE) model of the soil-water matrix and a schematic representation of the model with respect to the electrode-electrolyte interface (B) Impedance nyquist plot and (C) Bode-phase to denote the pseudo-capacitive dominant nature of the soil matrix (1:1, 1:2) and the comparatively resistive behavior of the baseline and 2:1 mixture

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(Invited) 4D Printed Soft-Matter Robotics: Materials, Fabrication and Applications
Authors: Furukawa Hidemitsu , Khosla Ajit
Published: July 2021

Soft robotics is a relatively new and rapidly emerging field of research that encompasses development of soft functional materials i.e. soft matter, fabrication techniques, and artificial intelligence. 3D printing facilitates fabrication of complex shapes and structures, placement of multiple soft matter, and customization of soft robots which is not possible conventional subtractive manufacturing technologies. 4D printing relates to the evolution in the shape, property, and functionality of a 3D printed structure with time when exposed to the stimuli. 4D printing can replicate natural physio-mechanical changes over time leading the transition from static to dynamic.

This talk will focus on 4D printed soft robotics by employing various types gel materials [1], fabrication of embedded gel sensors (physical and chemical) [2], actuation methodologies and sensing mechanisms [3], development of custom build 3D printer for gel materials [4], applications and examples of prototypes leading towards commercialization [5].

References:

Kumkum Ahmed, MD Nahin Islam Shiblee, Ajit Khosla, Larry Aiko Nagahara, Thomas Thundat, Hidemitsu Furukawa (2020) “Recent Progresses in 4D Printing of Gel Materials- A Review.” J. Electrochem. Soc. 167 037563. https://doi.org/10.1149/1945-7111/ab6e60

Hara, Yuta, Kazunari Yoshida, Ajit Khosla, Masaru Kawakami, Koh Hosoda, and Hidemitsu Furukawa. "Very Wide Sensing Range and Hysteresis Behaviors of Tactile Sensor Developed by Embedding Soft Ionic Gels in Soft Silicone Elastomers." ECS Journal of Solid State Science and Technology9, no. 6 (2020): 061024. https://doi.org/10.1149/2162-8777/aba913

MD Nahin Islam Shiblee, Kumkum Ahmed, Ajit Khosla, Masaru Kawakami, and Hidemitsu Furukawa (2018). "3D Printing of Shape Memory Hydrogels with Tunable Mechanical Properties." Soft matter, 2018,14, 7809-7817. https://doi.org/10.1039/C8SM01156G

Yosuke Sato, Azusa Saito, Yosuke Watanabe, MD Nahin Islam Shiblee, Jun Ogawa, Ajit Khosla, Masaru Kawakami, and Hidemitsu Furukawa. "Material Development and Equipment Improvement for 3D Gel Printing Using a Commercially-Available Stereolithography Printer." ECS Transactions98, no. 13 (2020): 93. https://doi.org/10.1149/09813.0093ecst

Jun Ogawa, Naoya Yamada, Yosuke Watanabe, Ajit Khosla, Masaru Kawakami, and Hidemitsu Furukawa. "Design of Hydrogel Material and 3D-Printed Molding for Imitating the Tactile Textured Properties of Moon Jellyfish." ECS Transactions 98, no. 13 (2020): 39. https://doi.org/10.1149/09813.0039ecst
Preparation of Efficient Memristive Films (2D materials) for Flexible Devices and Their Electrical Characterisation
Authors: Osayemwenre Gilbert
Published: July 2021

2D materials have various properties which make them potential candidates for better applications in electronic, chemical and biosensing devices. It is certain that so much work have previously been done on 2D materials. However, the aim of this study is to fabricate a material with a better quality that could create room for greater opportunities in electronic, chemical and biosensing devices. This fabrication was performed through exfoliation, and wet chemical means or PVD layer deposition technique. Furthermore, the current state of the electronics industry has necessitated the need for a novel and suitable memory for low cost and large scale flexible electronics materials. These materials should be non-volatile and low-power consuming devices because energy is of global concern. The non-volatility nature and the energy consuming ability of the finally fabrication was investigated from the current vs time curve in order to obtain the energy retention time. After the fabrication of the electronics material, various characterisations were performed on the devices; stability and endurance level was tested from the current vs cycle numbers of the curves. The rationale for these experiments is to take advantage of the Van der Waals multilayer force present in-between the layers of the two-dimensional (2D) materials to form a material with a desirable atomic and accurate quality. The outcome shows improve 2D memeristive material required to address most challenges experienced by electronic devices, particularly in the multilayer thin film. The result shows performance improvement of the memristors by raising the switching endurance at an elevated temperature of 300 oC and above. Finally, the mechanical flexibility and stability together with its endurance level were tested.
Micromechanical Resonators for Ultrasound-Based Sensors
Authors: Farhoudi Navid , Laurentius Lars B , Magda Jules , Reiche Christopher F , Solzbacher Florian
Published: July 2021

The current field of biomedical sensor platforms is substantial, and ever more creative approaches are envisioned and realized. Herein, we showcase a new platform technology for continuous biomedical analyte sensing that relies on the resonance absorption of ultrasound waves in microfabricated smart hydrogel structures (see Figure 1). Smart hydrogels can be tailored to be biocompatible and respond to many different analytes to undergo a volume-phase transition in response to changing levels of these biomarkers. [1,2] In addition, smart hydrogels can be designed to be biodegradable by basing them on compositions that include poly(ethylene glycol), poly(methyl methacrylate), or hyaluronic acid.

Employing smart hydrogel structures as mechanical resonators and probing them using ultrasound [3,4] can provide an implantable sensor platform that is minimally invasive and free of transcutaneous wires. This approach makes use of the fact that hydrogel structures exhibit a resonant oscillation at certain ultrasound frequencies by strongly absorbing mechanical energy. As they swell or contract in response to the presence or absence of the target analyte, their resonance frequencies change, leading to a modification of their ultrasound absorption spectrum. Measuring this allows for the reconstruction of analyte concentration changes. In addition to that, tailoring the resonance frequency of the hydrogel resonator structures to different frequency ranges allows for multiplexing. We successfully demonstrate the use of this platform technology using glucose as a target metabolic marker in vitro and in a rat model (see Figure 2).

Florian Solzbacher declares financial interest in Blackrock Microsystems LLC and Sentiomed, Inc. Jules Magda declares financial interest in Applied Biosensors LLC.

[1] Buenger, F. Topuz, and J. Groll, “Hydrogels in sensing applications,” Prog. Polym. Sci., vol. 37, no. 12, pp. 1678–1719, 2012.

[2] A. Peppas, J. Z. Hilt, A. Khademhosseini, and R. Langer, “Hydrogels in biology and medicine: From molecular principles to bionanotechnology,” Adv. Mater., vol. 18, no. 11, pp. 1345–1360, Jun. 2006.

[3] Carovac, F. Smajlovic, and D. Junuzovic, “Application of Ultrasound in Medicine,” Acta Inform. Medica, vol. 19, no. 3, p. 168, 2011.

[4] Troïani, J. R. Dion, and D. H. Burns, “Ultrasonic quantification using smart hydrogel sensors,” Talanta, vol. 83, no. 5, pp. 1371–1375, 2011.

Figure 1