bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Generative AI on Creativity in Software Development: A Research Agenda
Authors: Jackson Victoria , Vasilescu Bogdan , Russo Daniel , Ralph Paul , Izadi Maliheh , Prikladnicki Rafael , D’angelo Sarah , Inman Sarah , Andrade Anielle , van der Hoek André
Published: December 2024

As GenAI becomes embedded in developer toolchains and practices, and routine code is increasingly generated, human creativity will be increasingly important for generating competitive advantage. This paper uses the McLuhan tetrad alongside scenarios of how GenAI may disrupt software development more broadly, to identify potential impacts GenAI may have on creativity within software development. The impacts are discussed along with a future research agenda comprising five connected themes that consider how individual capabilities, team capabilities, the product, unintended consequences, and society. can be affected.
Predicting the Occurrence of Respiratory Diseases Based on Campus Indoor Air Quality
Authors: Li Pei-En , Ho Yao-Hua
Published: December 2024

Air quality is known to be strongly correlated with respiratory diseases. Indoor air quality considerably affects human health, especially in spaces such as classrooms, where students gather and interact for long periods. Most schools are located in relatively old buildings, where suitable ventilation systems are difficult to implement. The consequent lack of a standard ventilation rate increases the risk of cluster infections in classrooms. Accordingly, this article proposes a classroom respiratory disease occurrence prediction method based on indoor air-quality data (CROP–IAQ). Early warnings provided by CROP–IAQ will enable authorities to implement measures such as ventilation and isolation that reduce the risk of cluster infections in school campuses. Data on indoor temperature, relative humidity, particulate matter (PM) concentrations (PM1.0, PM2.5, and PM10, referring to the concentrations of particles with diameters of

\(\leq 1\)

,

\(\leq 2.5\)

, and

\(\leq 10\)

micrometer, respectively), carbon dioxide concentration, total volatile organic compound concentration, and luminosity in classrooms were collected using a MAPS V6.0 airbox. The air-quality data corresponding to potential cluster infections were identified from the aforementioned data and records of student epidemic prevention leaves in each class. Because most of the collected air-quality data did not correspond to potential cluster infections (that is, the dataset was imbalanced), synthetic data samples were generated using a synthetic minority oversampling technique. Four neural network models were constructed for predicting the possibility of disease occurrence and alerting authorities to classrooms at the risk of cluster infections: a convolutional neural network model, the inception model, a residual network model, and a residual network with external transformations model. The predictive capabilities of these models were only slightly improved after implementing a squeeze-and-excitation (SE) module. Experimental results indicated that the inception model with the SE module achieved the best results among the four models, with an F1 score and sensitivity of 0.72 and 0.76, respectively.
Detecting Misinformation on Social Media using Community Insights and Contrastive Learning
Authors: Ozcelik Oguzhan , Toraman Cagri , Can Fazli
Published: December 2024

Social media users are more likely to be exposed to similar views and tend to avoid contrasting views, especially when they are part of a community of social media users. In this study, we investigate the presence of user communities and leverage them as a tool to detect misinformation on social media, specifically on X (formerly known as Twitter). We propose a misinformation detection framework, namely Similarity-based Misinformation Detection (SiMiD) that employs microblogs and utilizes user-follower interactions within a social network. Our approach extracts important textual features of social media posts using a transformer-based language model. We use contrastive learning and pseudo-labeling to fine-tune the language model. Then, we measure the similarity for each social media post based on its relevance to each user in the communities. Finally, we train a machine learning model to identify the truthfulness of social media posts using these similarity scores. We evaluate our approach on three social media datasets, compare our method with twelve state-of-the-art approaches, and answer five research questions. The experimental results, supported by statistical tests, show that contrastive learning and user communities can enhance the detection of misinformation on social media. Our model can identify misinformation content by achieving a consistently high weighted F1 score of over 90% across all datasets, even employing only a small number of users in communities. We make our implementations publicly available and provide all details that are necessary for the reproducibility of experiments.

1
Two-Dimensional Siloxene: A Promising Silicon-Based Material with Buffered Volume Change As Anode for Lithium Ion Batteries
Authors: Zhang Xiaoxiao , Xin Le , Qiu Dantong , Qu Huainan , Liu Miao , Ding Tianyao , Zheng Dong , Qu Deyang
Published: December 2024

Silicon has emerged as a potential anode material for lithium-ion batteries due to its high theoretical capacity of 3579 mAh g−1 (Li3.75Si). However, the alloy reaction with a high lithium content presents challenges, such as significant volumetric expansion and an unstable solid electrolyte interphase layer, which are detrimental to the electrodes and lead to rapid capacity fade [1]. Siloxene, a silicon compound with a layered structure, has attracted attention in lithium-ion battery applications due to its small volume change and moderate capacity [2, 3]. This material is obtained through the topotactic deintercalation of Ca2+ from layered CaSi2 [4]. Microscopically, the layered structure of siloxene consists of Si6 rings interconnected with or without oxygen to form planes, with Si–OH/Si–H bonds on the surface of these planes [5]. Macroscopically, siloxene exhibits a morphology of stacked layered sheets. Our research explored how the layered morphology of siloxene changes during the lithiation/delithiation process. Figure 1 showed that the siloxene sheets bulge together during lithiation and revert to separate sheets after delithiation. The buffered volume change of the layered siloxene material contributed to significantly better cycling performance compared to chunky SiO and spherical Si/C materials. Additionally, the cycling performance of siloxene was further improved when it was blended with graphite materials.

[1] Kim, N., Kim, Y., Sung, J., & Cho, J. (2023). Issues impeding the commercialization of laboratory innovations for energy-dense Si-containing lithium-ion batteries. Nature Energy, 8(9), 921-933.

[2] Loaiza, L. C., Monconduit, L., & Seznec, V. (2020). Si and Ge‐based anode materials for Li‐, Na‐, and K‐ion batteries: a perspective from structure to electrochemical mechanism. Small, 16(5), 1905260.

[3] Loaiza, L. C., Dupré, N., Davoisne, C., Madec, L., Monconduit, L., & Seznec, V. (2021). Complex lithiation mechanism of siloxene and germanane: two promising battery electrode materials. Journal of The Electrochemical Society, 168(1), 010510.

[4] Yamanaka, S., Matsuura, H., & Ishikawa, M. (1996). New deintercalation reaction of calcium from calcium disilicide. Synthesis of layered polysilane. Materials Research Bulletin, 31(3), 307-316.

[5] Weiss, A., Beil, G. & Meyer, H. (1980). The Topochemical Reaction of CaSi2 to a Two-Dimensional Subsiliceous Acid Si6H3(OH)3 (= Kautskys’ Siloxene). Zeitschrift für Naturforschung B, 35(1), 25-30.

Figure 1
Flexible and Stretchable Li Ion Battery Using Origami Scale Structure for Untethered Soft Robot
Authors: Hyun Seungmin , Oh Minsub , Jang Bongkyun
Published: December 2024

In recent years, technology of soft robotics has emerged as an important issue for the robot industry. Compared to conventional industrial metallic robots in controlled environments, soft robots are highly expandable in responding to non-standardized environments. Due to these characteristics, it is expected to be used not only in daily life, but also in specific applications such as treatment of disease and disaster relief. The development of a structure that is free to deformation with energy source is also essential to improve the technology. Among several energy sources, Lithium ion batteries (LIBs) are the prime choices for these applications due to light weight, high energy density and long cycle life. The integration of flexible structure and LIBs is very important to reduce the waste of space and weight of soft robots for versatility and portability. However, there are many difficulties due to the absence of batteries with high reliability under deformation. LIBs usually have little flexibility due to the high stack cells and stiff nature of cell components. It is required to have a new design of LIBs. Geometrically designed structures incorporating bioinspiration are promising solutions for integrating components of soft robots. In this study, we propose a novel geometric structure for stretchable devices, created by folding well-defined two-dimensional patterns with cutouts to produce an extremely stretchable structure with superior reliability and bi-axial deformability. The structure is designed to mimic the hinge of a snakeskin so that its unit cells do not interfere with each mutual movement enabling stable deformations without mechanical damage. In addition, to maximize areal density and stretchability, the optimal shape of unit is determined. The unit-based geometric structure is applied to a stretchable Li-ion battery and constructed of hexagonal pouch cells and parallelogram interconnections. In situ electrochemical characterization confirms that the performance of the battery is maintained under dynamic deformation with a stretching ratio of 90% and a 10-mm-radius bending curvature, guaranteeing a long-lasting cycle life. To confirm the mechanical reliability of the scale battery, the strain distribution at the flexible hinge is obtained by FEA(Finite element analysis). The strain is mainly localized in the folding parts of the interconnection, and it is found that the unit cell experiences on deformation during the unfolding process. This is the main reason that the electrochemical performance is maintained during the mechanical deformation of the scale battery. Finally, the geometrically designed structure-based battery is applied to movable robots, crawling and slithering, with dynamic bi-axial deformations and can be pivotal role in the development of flexible electronics including human-friendly wearable electronics and soft robots.
Tailoring Ni-Rich Cathode Properties with Mo Doping for Next-Generation Li-Ion Batteries
Authors: Kim Jae-Ho , Sun Yang-Kook
Published: December 2024

Among battery components, cathode chemistry is a defining feature because it primarily determines both cost and performance. Enhancing the long-term cycling stability of Ni-rich layered cathode materials is crucial for high-energy-density applications in electric vehicles. However, the intrinsic instability of these Ni-rich layered cathode materials, which increases with increasing Ni content, limits their commercial use.1 Doping is a promising strategy to improve stability and performance. However, improving cycling performance through cathode material doping is challenging and requires the careful tuning of the doping parameters and conditions.2 Among the various dopants, Mo is highly effective in refining cathode morphology across a broad range of lithiation temperatures, enhancing the resistance of cathode particles to mechanical damage and improving their stability during repeated cycling.

Hearin, we investigate the impact of molybdenum (Mo) doping on Ni-rich NCMA cathodes, examining how varing Mo content and lithiation temperatures affect material properties. To evaluate the effect of Mo as a dopant, we focused on the morphological properties and crystallinity of Mo-doped Ni-rich NCMA94 cathode materials. The results show that optimal Mo doping improves cathode morphology and crystallinity, leading to better electrochemical performance.3 Mo-doped NCMA94 cathodes with refined primary particle size and high crystallinity demonstrate superior capacity and cycling stability. This study provides insights into optimizing doping parameters for advanced Ni-rich cathode materials, supporting long cycle life in next-generation Li-ion batteries.

References:

[1] H.-H. Ryu, K.-J. Parl, C.-S. Yoon, Y.-K. Sun, Chemistry of materials, 2018, 30(3), 1155.

[2] Z. Peng, K. Mu, Y. Cao, L. Xu, G. Hu, Ceramics International, 2019, 45(4), 4184.

[3] H.-H. Ryu, H.-W. Lim, S.-G. Lee, Y.-K. Sun, Energy Storage Materials, 2023, 59, 102771.
Physics-Informed Neural Networks for State and Parameter Estimation of Li-Ion Batteries
Authors: Kajiura Yuichi , Espin Jorge , Zhang Dong
Published: December 2024

Combining machine learning with physics is a trending approach for discovering unknown dynamics, and one of the most intensively studied frameworks is the physics-informed neural network (PINN). However, PINN often fails to optimize the network due to its difficulty in concurrently minimizing multiple losses originating from the system’s governing equations. This problem can be more serious when the system’s states are unmeasurable, like lithium-ion batteries. In this work, we introduce a robust method for training PINN that uses fewer loss terms and thus constructs a less complex landscape for optimization. In particular, instead of having loss terms from each differential equation, this method embeds the dynamics into a loss function that quantifies the error between observed and predicted system outputs. This is accomplished by numerically integrating the predicted states from the neural network(NN) using known dynamics and transforming them to obtain a sequence of predicted outputs. Minimizing such a loss optimizes the NN to predict states consistent with observations given the physics. Further, the system’s parameters can be added to the optimization targets. To demonstrate the ability of this method to perform various modeling and control tasks, we apply it to an electrochemical battery model to concurrently estimate its states and parameters.

Figure 1
Hydrodynamic Jet Cavitation to Process Natural Graphite for Ultra-Fast Charging Lfp // Graphite Pouch Cells
Authors: Robinson Benjamin , Low John
Published: December 2024

Graphite has proven to be the most dominant anode material for Li-ion batteries (LIBs) due to its relatively high gravimetric capacity (372 mAh g-1), high Li-ion diffusion coefficient (~10-11 cm2 s-1) and

low delithiation potential (0.1V vs. Li/Li+). (1) Current methods of producing battery-grade graphite are both energy and greenhouse gas intensive. (2) New methods of processing graphite with far lower carbon footprints are becoming available using hydrodynamic jet cavitation. (3) This work tests the Li ion battery anode performance of three different jet cavitation processed graphite powders that have been processed by the above-mentioned method. The materials both matched the performance of commercial synthetic graphite anodes in low C-rate cycling and showed an improved capacity of >100 mAhg-1
LFP in full cells at 10C. Additional testing was also performed on single layer pouch cells. It was found that the rougher surface morphology of the jet cavitation processed graphite causes a slightly poorer initial coulombic efficiency but a far greater capacity at high C-rates.
Sn-Gradient Sulfide Solid Electrolytes with Superior Air-Stability for Practical All-Solid-State Batteries
Authors: Ko Sumin , Ko Sumin
Published: December 2024

Sulfide solid electrolytes (SSEs) with high ionic conductivity and mechanical flexibility are considered promising Li+ transport media for all-solid-state batteries (ASSBs). However, susceptibility to moisture originating from their crystal structures degrades their inherent superior properties. In this study, we synthesized core-shell structured SSEs by inducing the growth of compounds with moisture-stable SnS44- units on the surface of Li6PS5Cl (LPSC). This Li10SnP2S12 (LSPS)@LPSC showed > 30 times higher Li+ conductivity than LPSC after exposure to dry room environment for 2 h. Additionally, the hydrolysis reaction was effectively inhibited in LSPS@LPSC, resulting in not only significant reduction of hydrogen sulfide (H2S) gas release, but the onset of its generation was also more delayed than in LPSC. Also, in LSPS@LPSC, the inhibition of P-O bond formation after moisture exposure contributes to retention of mechanical properties, as demonstrated by nano-indentation measurements: hardness changes from 1.42 GPa to 1.50 GPa for LSPS@LPSC versus from 1.21 GPa to 1.62 GPa for LPSC (dew point of -7.5 °C, 5 min). Furthermore, the symmetric cell with LSPS@LPSC exhibited excellent cycling stability comparable to that of LPSC under typical external pressure (30 MPa). And more remarkably, the Li(Ni0.8Co0.1Mn0.1)O2 half cell showed superior cycle retention than LPSC cell under ultra-low external pressure (~0.3 MPa).
Investigating the Redox Dynamics of Rare-Earth Phosphate-Coated Li-Rich Layered Oxides
Authors: Jenkins Tristram H. M. , Cowie Bruce C , Alarco Jose A , Mackinnon Ian D.R.
Published: December 2024

Li-rich, Mn-rich layered oxides (LMOs) are promising cathode materials for next-generation Li-ion batteries, offering high energy densities (>250 mAhg⁻¹) and an average voltage of ~3.6V. However, LMOs suffer from capacity and voltage decay due to O 2p redox activity, leading to structural degradation, microcracking, lattice destabilization, and O₂ release[1]. This material degradation is driven by both surface and bulk structural transformations, though surface modification has emerged as a key strategy to mitigate these effects by stabilizing surface oxygen bonding and restraining spinel transformation[2].

In this work, we investigate the influence of rare earth phosphate (REP) coatings (YPO₄ and CePO₄) on the electronic structure and electrochemical performance of Li₁.₂Mn₀.₅₄Ni₀.₁₃Co₀.₁₃O₂. Using soft X-ray absorption spectroscopy (sXAS), we observe reduced O 2p-TM 3d hole formation, improved reversibility of transition metal redox and dynamic changes in P-O coordination in REP-coated LMOs. Additionally, band alignment at the REP-LMO interface is discovered, correlating with lower observed charge transfer resistance and generally enhanced electrochemical performance during initial and long cycling. This study further demonstrates the importance of electronic compatibility in surface modifications for Li-ion battery cathodes.
Integrated Energy Generation and Water Desalination Platform
Authors: Choi Byeongwook , Son Moon , Park Sanghun
Published: December 2024

The transpiration-driven electrokinetic power generator (TEPG) system, utilizing substrates such as cotton fabric, generates electricity through a pseudo-streaming mechanism between water and the substrate. Extensive research efforts are underway to store the generated electricity in devices such as watches, light bulbs, and supercapacitors. However, there are still limitations of low current (µA levels), low power density, and short duration (< 300s). Furthermore, there is an increasing necessity for environmentally sustainable applications beyond simply supplying power to small devices. Therefore, more research efforts are necessary to increase both the current and duration to effectively operate TEPG in various applications.

In this study, we have developed a carbonous water-driven power generator (CWPG) to address this low-energy generation issue. The CWPG differs from TEPG in utilizing carbonous porous material, maximizing the efficacy of the electricity generation mechanism. The CWPG, composed of a carbon-structured substrate, has overcome the limitations of previous designs by achieving currents at the milliampere (mA) level and ensuring high durability with duration times exceeding two hours. The power generation capability of CWPG was applied to an electrochemical water desalination system, capacitive deionization (CDI), which utilizes the principle of electric double-layer formation to adsorb ions in salty water (i.e., brackish water). Thus, in this presentation, for the first time, an integrated energy generation and water desalination platform based on CWPG and CDI will be introduced.
Direct Conversion from Poly- to Single-Crystal Cathode By Oxygen-Storage Additive
Authors: Kim Jongmin , Lee Seongwoo , Kim Kookhan , Eom Ji-Yong
Published: December 2024

As demand for electric vehicles increases, interest in cathode materials with high energy density continues to increase. Ni-rich layered NCM811 is a cathode material attracting attention because it can realize high energy density. However, currently available NCM cathode materials use secondary particles. In the case of commercial NCM811, which has a secondary particle shape, the cycle-life characteristics rapidly decrease due to the cracks of the primary particles constituting the secondary particles. Single crystallization of NCM cathode materials is used to minimize these particle cracks. Single-crystal cathodes without intergranular cracks have been shown to improve cycling and thermal stability by minimizing surface degradation.

In this study, A high-performance single crystal cathode material was synthesized by directly converting commercial NCM811 polycrystal using a crystal growth promoter (Ce0.5Zr0.5O2) during heat treatment. The CeZrO2 additive used in the synthesis was able to grow primary particles significantly at the same temperature compared to when no additive was used or when CeO2 or ZrO2 was used. The performance of single crystal particles synthesized using this method was further improved through cobalt coating. Single crystals synthesized using additives showed very excellent cycle-life performance compared to existing commercial secondary particles or active materials that were heat-treated without additives at the same temperature. The enhanced electrochemical performance is attributed to decreased crack generation, reduced surface reactivity by cobalt coating, which was confirmed through various electrochemical analyses and electrode observations.
The Redox Activity of Fe-C and M-Fe-C Species to Improve an Overall Water Electrolysis and Alkaline Zinc-Air Batteries
Authors: Jin Yoo
Published: December 2024

The creation of energy storage and conversion devices, including electrolytic water splitting and metal-air batteries, depends on multifunctional electrocatalysts based on elements that are readily available on Earth. In this case, copper paper is used to create hierarchical Fe-Se-C nanorod arrays, which enrich numerous active species on the catalytic scaffolds and result in exceptional trifunctional activities of OER, HER, and ORR that are comparable to those of IrO2 and Pt/C. While an elevated current density of 500 mA cm−2 can be achieved for total water splitting with a cell voltage of just 1.57 V, Zn-air batteries (ZABs) require a highly stable round-trip efficiency. Demonstrating a clever use of materials to maximize energy efficiency and achieve multifunctionality at the same time. Density functional theory calculations were used to further examine the electronic structure and HER, OER, and ORR reaction mechanism of the catalysts Fe-Se-C and Sc@Fe-Se-C. Lastly, a method for creating, setting up, and assembling air electrodes is proposed for the advancement of high-performance Zn-air batteries in the future.
Sensitivity Improvement of Electrochemical Virus Detection through Morphology Control of CNT Electrodes
Authors: Suzuki Daichi , Takemura Kenshin , Terasaki Nao
Published: December 2024

The global pandemic of influenza virus (IFV) and Covid-19 has created a strong need for the technology to measure viruses quickly and sensitively. Currently, PCR-based detection technology is used to accurately detect these viruses, however they lack immediacy as it takes several days for the viruses to grow to detectable amounts. A complementary method that allows immediate detection is an antigen testing that uses complementary substances (aptamers and antibodies) that specifically bind to target virus. Among them, electrochemical detection via cyclic voltammetry is being researched as a method that can measure target virus in solutions with high sensitivity and high speed. Since these utilize chemical reactions on the electrode surface, the material and surface morphology of the electrode are important factors that govern sensitivity. Previous research has reported that highly sensitive and robust virus testing can be performed by using carbon nanotube (CNT) films, which are chemically stable and have a large surface area, as chemical electrodes. However, the effect of the surface morphology of CNT films such as structures and defects has not been sufficiently studied.

In this study, we attempted to increase the sensitivity of electrochemical virus testing by controlling the surface morphology of CNT films and increasing the amount of aptamer adsorption. The morphology of the CNT film was controlled through heat and non-heat laser processing by using 532 nm nano-second and/or pico-second pulsed lasers. The fabricated morphology was evaluated by SEM and polarized Raman spectroscopy. In addition to measuring the amount of aptamer adsorption for each morphology using ultraviolet spectroscopy, we also evaluated the detection sensitivity of IFV when using the CNT films as an electrochemical electrode. As a result, we achieved the high sensitivity and reliability IFV detection with fg/ml of the limit of detection. In the presentation, we will introduce the developed CNT morphology control technology and discuss the relationship between morphology and aptamer adsorption amount.

Figure 1
Highly Conductive Deformation-Free Reduced Graphene Oxide Fibers : Towards High-Performance Wearable Supercapacitors
Authors: Lee Hye Jung , Jeong Seung Yol , Yang Sunhye , Jeong Sooyeon , Hong DongGyun , Ryu Jihyeon , Kim Ick-Jun
Published: December 2024

Solution-processed graphene fiber has been introduced by a wet spinning process of liquid crystal (LC) graphene oxide because of its strong hydrogen bonding and self-assembled layered structures with nematic phases. Substantially, graphene oxide (GO) solidified with layered structures in a coagulation bath. The LC-spun GO fibers generally have highly stacked and layered structures and are uneven along the fiber axis. However, due to the insulating properties of GO fiber, a reduction process should be introduced for a practical approach. Following the chemical reduction process, the LC-spun GO fiber has abundant and irregular structural deformation on the core and shell in fiber due to significant volume shrinkage. It has poor electrical conductivity, low specific surface area, and weak mechanical properties for applying high-performance supercapacitors.

Herein, we introduce deformation-free graphene fiber by extruding reduced graphene oxide (rGO) and GO hybridization. This is also used in the conventional wet spinning processes. The rGO-GO hybrid dope is a possible candidate for applying porous graphene fiber with high electrical conductivity, effective surface area, and proper mechanical strength. In addition, the rGO has high electrical conductivity with low defect sites. The fabrication method is based on modified Brodie method which generates quasi-defect-free reduced graphene oxide as introduced previous work. In particular, against LC-spun GO spinning, high-quality rGO-GO dope reveals that the rGO minimizes the self-assembly of GO and adjusts the imbibition ratio simultaneously for rapid dope solvent-coagulation exchange on extruding the graphene fiber. In addition, chemically stable rGO plays a role in a frame for supporting the fiber structure after the reduction process without the deformation of core and shell structures. Despite porous rGO-GO fiber, the significantly high circularity and effective porosity could enhance electrical conductivity (~654 S/cm, after drawing) and capacitance of supercapacitors. The graphene fiber can be applicable for wearable energy storage devices with high performance.
Enhanced Electrochemical Properties of Silicon and Quasi-Defect-Free Reduced Graphene Oxide for High Performance Anode Materials
Authors: Jeong Sooyeon , Kim Byeong Guk , Ryu Jihyeon , Lee Hye Jung , Hong DongGyun , Nam Ki-Hun , Kim Ick-Jun , Yang Sunhye , Jeong Seung Yol
Published: December 2024

Silicon suboxide is one of possible candidate as anode materials for high performance lithium ion battery. However, it has several significant drawbacks such as volume expansion and unstable surface electrolyte interfaces. Therefore, carbon layer should be necessary as protecting layer with high electrical conductivity and crystal structure. Graphene has significant potential as a passivation layer with respect to silicon-based anode materials. However, the conventional method of coating graphene oxide on silicon surfaces, followed by reduction processes, can lead to issues such as graphene layer pop-up and contamination, resulting in degraded electrochemical properties. To overcome these limitations and realize the practical use of silicon anode materials, we introduce silicon suboxide and reduced graphene oxide(rGO) composite anode material with high electrical conductivity and aqueous suspension simultaneously. The composite anode materials prepared simple and straightforward one-step method by spray drying technique with water-dispersed rGO solution. In particular, the cation-π interacted rGO enhances the surface interaction between the graphene and the carbon layer on the conventional silicon suboxide surface, leading to improved overall performance. We evaluated the electrochemical properties of the composite anode material, which consisted of approximately 3% graphene content added to silicon with a content of 20wt%. The results demonstrated that the silicon suboxide/C@rGO composite anode materials revealed significant superior electrochemical properties compared to the conventional silicon suboxide/C composite. This result overcomes the current limitation of silicon content almost 5%, enabling the practical utilization of anode materials and offering higher energy density and cyclic stability in battery applications.
Bioinspired Molecular Electrets: Structure-Function Relationships When Dipoles Appear Everywhere
Authors: Vullev Valentine I.
Published: December 2024

The importance of charge transfer (CT) and charge transport cannot be overstated (Phys. Chem. Chem. Phys.
2020, 22, 21583-21629). The shift to low-dielectric-constant carbon materials and devices, however, leads to the emergence of dominating electrostatic effects from localized dipole-generated fields. Resorting to molecular electrets allows examining the multifaceted nature of such effects. We develop bioinspired molecular electrets with enhanced CT capabilities that comprise anthranilamide residues. Even a single electret amino-acid residue can rectify CT (Angew. Chem. Int. Ed.
2018, 57, 12365-12369; J. Am. Chem. Soc.
2014, 136, 12966-12973). The molecular macrodipoles and the CT properties of these electrets strongly depend on their structure and conformational flexibility. Recently, we discovered an emergence of picosecond dipole transients (two-to-three times larger than the average dipole values) that originate from the solvent dynamics (J. Am. Chem. Soc.
2024, 146, 5162-5172). Further investigation reveals that these dipole transients appear universal and are not limited to large polar macromolecular structures. Such unexpectedly large dipole jumps provide underlying indication for the gating trends observed in picosecond and sub-picosecond CT kinetics (J. Am. Chem. Soc.
2016, 138, 12826-12832; Proc. Natl. Acad. Sci. USA
2021, 118, e2026462118). These unprecedented insights about the enormous picosecond dipole dynamics underlines new structure-function relationships essential for organic electronics and photonics, as well as for energy science and engineering.
Pillared Graphene Nanostructures for Electrochemical Energy Storage
Authors: Ozkan Cengiz Sinan
Published: December 2024

The global electrochemical energy storage market ranging from electric vehicles and personal electronics to physical grid storage and defense applications demands the development of new classes of materials for fabricating high performance batteries and supercapacitors. I will begin by describing innovative approaches for the design and synthesis of nanostructured carbon materials towards enhanced reversible capacity; superior rate performance and cycling stability; and superior gravimetric capacitance. A novel 3D architecture called a pillared graphene nanostructure (PGN) is a combination of two allotropes of carbon, including graphene and carbon nanotubes possessing ultra large surface area, tunability, mechanical durability and high conductivity can be grown on a variety of substrates, which are appealing to diverse energy storage systems. Another type of 3D superporous carbonaceous architecture called chrysanthemum nanofibers can be grown in roll-to-roll form on commercial nickel foams. Integration of nanostructured pseudocapacitive metal oxides to such 3D templates can provide superior electrochemical performance in supercapacitor applications. PGN templates can also be transformed into cone-shaped clusters decorated with amorphous silicon for advanced lithium ion (Li-ion) battery anodes. Single and multilayer stacked 3D carbonaceous architectures could also be envisioned for further future applications in hydrogen storage. I will also describe recent advancements in upcycling polyethylene terephthalate (PET) waste into active nano-carbon electrode materials for energy storage. For PET plastic-waste, materials are dissolved in a mixture of trifluoroacetic acid and dichloromethane, followed by carbonization under an argon/hydrogen atmosphere. Electrodes derived from PET are employed in supercapacitors and Li-ion battery anodes. Our studies pave the way for scaled up manufacturing of energy storage devices with enhanced energy density and power density.
A CNT-FET Electronic Nose for the Detection of VOCs Associated with Agriculturally Relevant Pests
Authors: Avnon Asaf , Klain Hagai , Kaspi Roy , Levi-Zada Anat , Shafir Sharoni , Mechrez Guy , Vernick Sefi
Published: December 2024

Insect infection of post-harvest agricultural yield is detrimental where even a single fruit might spoil the whole batch causing significant economic loss and shortages in the food supply chain. Given this immense loss and the looming food shortages, early detection of spoiled fruits is essential.

Upon Infection, fruits emit distinct volatile gases, conveyed even from unblemished waxed fruits. This is especially important as infected fruits may look unblemished and cannot be detected via optical sensors.

Therefore, we developed an olfactory biomimetic nanometric electronic field-effect-transistors based on single-walled carbon nanotubes covalently functionalized with polyaniline oligomers doped with silver or copper ions. The volatiles were measured via a dedicated microfluidic system.

As a proof of concept, we chose citrus fruits infected by the false codling moth Thaumatotibia leucotreta which attacks various fruits year-round but leaves the fruits unblemished from the outside, and is a common pest throughout the world.

We identified specific volatile gases excreted from infected fruits using honey-bees as a biological sensor through Pavlovian conditioning and matched them with the synthetic equivalents.

With our devices we were successful in identifying these volatile gases through repeated distinct shift of the transconductance gate response upon exposure to volatile gases. Washing of the device brought about a return to the initial state.

Thus, our electronic-nose device can be used as a practical and beneficial tool to detect early infection on fruit batches.
(Invited) NIR-II Instrumentation - from in Vitro Spectroscopy to Translational Fluorescence Imaging
Authors: Blais-Ouellette Sebastien , Dancer Pierre-Alix , Rioux David , Dorval Paul , Chung Wendy
Published: December 2024

Biological and medical applications harnessing carbon nanotube (CNT) fluorescence have created a need for a new breed of analytical instrumentation. Unlike traditional contrast agents and fluorophores primarily operating within the visible or near-infrared spectral range, CNTs often emit beyond 1 µm, referred to as SWIR or NIR-II, where silicon-based detectors are ineffective. Since the emergence of commercially available spectrometric systems in the early 2000s to the ongoing development of intraoperative imaging systems, researchers now have access to a diverse array of instruments. This presentation will provide an overview of the current landscape of in-vitro and in-vivo instruments while highlighting the latest advancements from various research groups and companies.
(Invited) AI-Driven Surface Enhanced Raman Spectroscopy for Rapid Diagnosis of Metabolic Disorders
Authors: Hu Tony
Published: December 2024

The utilization of artificial intelligence (AI) in material selection is rapidly advancing, yet the integration of AI into the design and optimization of sensing materials tailored for disease-related molecules and material interfaces remains nascent. In this study, we propose a data-driven approach for the design of materials, considering composition and morphology to enhance localized electric fields and molecular affinity, thereby facilitating improved Raman analysis of urine organic acids associated with metabolic diseases. Our AI-designed copper nanoplasmonic substrate exhibits a remarkable 15-fold increase in

Raman enhancement compared to commonly utilized gold nanomaterials (3 times greater enhancement than silver nanomaterials). Combining Raman spectroscopic analysis of clinical urine samples with machine learning techniques, we identify urinary markers indicative of inborn errors of metabolism (IEM), a spectrum of nutrient processing deficiencies affecting approximately 0.04% of the population. Notably, the non-targeted nature and operational simplicity of Raman spectroscopy enable rapid acquisition of spectral data within 10 minutes. Leveraging a modest dataset of 60 clinical samples, our decision model achieves a sensitivity of 95.4% and specificity of 80.5% in distinguishing between normal and abnormal samples, with an overall accuracy of 85% for categorizing

abnormal subtypes. Subsequent blinded sample tests validate the effectiveness of the pretrained model, demonstrating an accuracy of 87.5%. This study introduces a novel approach combining surface enhanced Raman spectroscopy with AI-driven machine learning, offering a streamlined and timely identification of IEMs such as ornithine transcarbamylase (OTC) deficiency and maple syrup urine disease (MSUD). Our findings highlight the potential of this approach to enhance patient care, address diagnostic challenges in IEM, and facilitate broader screening initiatives.
Advancement of Ionic Complexes Based on Multivalent Carbon Dot Polyanions for Applications in Electrochemical Systems
Authors: Lim Hong Chul , Kim Tae Hyun
Published: December 2024

Carbon dots, also known as carbon quantum dots or graphene quantum dots (C-dots), have garnered significant attention due to their promising applications in various fields such as energy, catalysis, bioimaging, and nanomedicine. Typically, C-dots exhibit zero-dimensional characteristics with hybridized carbon structures at the core and functional groups like hydroxyl and carboxyl at the edges.

In this talk, I will highlight our recent advancements in utilizing ionic complexes based on C-dots for electrochemical applications, serving as supporting electrolytes and anionic dopants. We've developed nano-sized multivalent C-dot polyanions through a hydrothermal oxidation process of carbon nanofibers, forming complexes with alkali cations such as Li+, Na+, and K+. Consequently, we investigated the potential applications of ionic complexes based on C-dot as electrolytes for lithium-ion batteries and electrochromic devices. The ionic complexes demonstrate low Coulombic energy, exceptional thermal/electrochemical stability, and good ionic conductivity when dissolved in both aqueous and organic solvents. Molecular dynamics simulation with the electrochemical characterization reveals that the ionic complexes provide highly abundant free metal cations with highly stable C-dot polyanions and negligible ion pairs in solution. Furthermore, we have successfully implemented a novel approach to fabricate nanoarchitectures based on C-dots as an electrode-active material with outstanding electrochemical catalytic activity which is suitable for electrochemical biosensors and H2O2 reduction.

Figure 1
(Invited) Conductometric Biosensors: Semiconductor Technology for Precise Measurements of Molecules
Authors: Sriram Sharath
Published: December 2024

Semiconducting substrates are chemically and environmentally stable, especially silicon. Here, high resistivity float zone silicon is used as a semiconducting substrate for the design and implementation of novel biosensors. With an electrode pair arrangement at the micro-scale, surface silanisation to create binding sites, and target-specific functionalisation a new category of precise conductometric biosensors is demonstrated.

With high sensitivity down to picomolar concentrations and high specificity in complex mixtures, the sensors are demonstrated for targets that encompass biomarkers (inflammatory, heart failure, fertility, and neurological), viral targets (SARS-CoV-2), and DNA fragments (cancer gene sequences for melanoma, liver, stomach, and oral cancers).

Integration of the micro-scale sensors with wireless electronics, to allow real-time data acquisition is demonstrated. The technology results in a semiconductor-based remote point-of-care diagnostic platform for early screening of diseases, improving healthcare accessibility and personalised medicine.
(Invited) Lubricin-Powered Biosensors for Multiplex Biomarker Detection
Authors: Moraes Silva Saimon , Coimbra Pimenta Thiago , Greene Wren
Published: December 2024

The conception of reagentless protein-based electrochemical biosensors that can detect multiple molecular analytes simultaneously directly in complex biofluids has the potential to transform our understanding of biology and personalized health monitoring. Previously, we have introduced an innovative protein-based electrochemical sensing strategy for the detection of glycans directly in unprocessed complex biofluids.[1] This innovative sensing technology uses redox reporter-engineered lectins as recognition elements. Lectins are glycan-binding proteins that can selectively interact with glycan molecules.[2] These engineered lectins are anchored to an electrode surface via a self-assembled monolayer of lubricin (LUB).[1] LUB is a glycoprotein with demonstrated antifouling properties, and it has proved its usefulness in sensors and biosensors as it allows electrochemical measurements to be performed directly in unprocessed biofluids.[2,3,4,5] In this sensing configuration, electrochemical signal generation (measured using voltammetric techniques) occurs when the target glycan binds to the lectin recognition element, diminishing the efficacy with which the attached redox reporter, methylene blue, transfers electrons to the electrode surface.[1] Thus, this is an on-off switch sensing mechanism. So far, our published work has only focused on the detection of single glycans such as Tn antigen. In this presentation, I will share our latest findings on how to provide a multiplexed capability to such a sensing technology and how it can be useful for in-situ monitoring of multiple protein biomarkers directly in biofluids, creating hence a new tool for biodiscovery and bioanalysis.

References

[1] Silva, S. M.; Langley, D.; Cossins, L.; Samudra, A.; Quigley, A. F.; Kapsa, R. M. I.; Tothill, R. W.; Greene, G. W.; Moulton, S. E. ACS Sensors, v. 7, 11, 3379–3388, 2022.

[2] Li, M.; Abeyrathne, C.; Langley, D. P.; Cossins, L. R.; Samudra, A. N.; Greene, G. W.; Moulton, S. M.; Silva, S. M. Electrochimica Acta, v. 457, 142508, 2023.

[3] Russo, M. J.; Quigley, A. F.; Kapsa, R. M. I.; Moulton, S. E.; Guijt, R.; Silva, S. M.; Greene, G. W. ChemElectroChem, v.7, 2851, 2020.

[4] Russo, M. J.; Han, M.; Quigley, A. F.; Kapsa, R. M. I.; Moulton, S. E.; Doeven, E.; Guijt, R.; Silva, S. M.; Greene, G. W. Electrochimica Acta, v. 333, 135574, 2020.

[5] Silva, S. M.; Quigley, A. F.; Kapsa, R. M.; Greene, G. W.; Moulton, S. E. ChemElectroChem, v. 15, p. 1939-1943, 2019.
Effect of Short-Chain Polymer Binders on Mechanical and Electrochemical Performance of Silicon Anodes
Authors: Sun Fei , Zurita Lizbeth , Wheeler Dean
Published: December 2024

Polymer binders are crucial components in providing both mechanical support and chemical stability to the structure of porous Li-ion electrodes. Particularly in silicon anodes, active material undergoes substantial volume expansion of up to 280%. As is shown in Figure 1, due to the restriction of the current collector, these silicon materials tend to expand vertically and so this requires substantial rearrangement of particles and plastic deformation.

However, conventional binders such as polyacrylic acid (PAA) and polyimide (PI), while providing satisfactory initial capacity, suffer from mechanical rigidity due to their long polymer chains, leading to diminished long-term performance.

Our research attempts to address this limitation by exploring the use of short-chain polymer binders, which may offer improved flexibility to accommodate the substantial volume changes of silicon particles. Although our previous work indicated that shorter polymer chains might compromise the adhesion to the copper current collector, we have developed a multilayer anode (MLA) structure featuring an adhesion layer to mitigate this issue. As is shown in Figure 2, this adhesion layer, placed between the silicon-containing bulk layer and the copper current collector, is designed to enhance the interface stability without sacrificing the mechanical compliance provided by short-chain polymers.

Our experiments demonstrate that cells combining both long and short-chain PAA binders outperformed those with conventional PAA alone, delivering initial capacity of 2200 mAh/g at a 0.1C rate, compared to 1700 mAh/g for pristine PAA cells. At the early stages of development of the MLA-style anode with an adhesion layer, there was not an observed increase in performance, though experiments are ongoing, and we will report on latest results.

We believe that the introduction of a strategic blend of different molecular weight binders can offer a promising solution to some of the challenges faced by silicon-based anodes.

Figure 1