bluuebunny/crossref_metadata_2025 huggingface dataset:
Theoretical Model and Control-Parameter Classification for Solid Oxide Fuel Cell System with Cooling Air Bypass into Burner
Authors: Ma Long , Lin Zijing
Published: December 2024

When using solid oxide fuel cells (SOFCs) as the auxiliary power unit (APU) of automobiles, a stringent thermal control to limit the temperature and thermal stress of all components of the SOFC system is required. Various thermal management methods have been proposed, mostly involving the use of cooling air (CA). To avoid the thermal shock associated with directly adding CA into the SOFC stack air inlet stream, directing CA into the burner is a desirable alternative. Using CA bypass into the burner is a simple and effective way to control the excessive burner temperature, which in turn limits the temperatures of other system components.

In this study, a 5 kW SOFC system fueled by diesel and with CA into the burner is examined. The system consists of an SOFC stack and a balance of plant (BOP) that includes a steam generator, an air heat exchanger, a fuel heat exchanger, a pre-reformer and a burner, a water pump and an air blower. The burner burns the unused fuel and provides heat to the pre-reformer and heat exchangers. A thermocouple is installed near the outlet of the burner, which is connected to a CA pipe. When the burner temperature exceeds its set maximum temperature, TBM, the CA valve opens to allow fresh air to enter directly to the burner through the bypass pipe to maintain the burner temperature at the set value. A comprehensive theoretical model, including detailed sub-models for all system components, is developed and verified with multiple experimental data.

The theoretical model is used in a comprehensive control-parameter classification analysis, revealing the impacts of the fuel utilization, Uf, air flow rate, Vair, and TBM = (900 ℃, 1000 ℃) on the system performance. In particular, the effects of (Uf, Vair, TBM) on the system electrical efficiency, Esys, and the characteristic temperatures of the stack and BOP components are determined quantitatively. The main findings are: 1) It is confirmed that the CA bypass into the burner can limit the operating temperatures of all system components. 2) Changing TBM from 900℃ to 1000℃ can notably increase Esys only for low Uf, but may increase the maximum stack temperature, TM. It appears that TBM = 900℃ is more favorable than TBM = 1000℃. 3) Increasing Uf increases Esys, but may also increase TM and the maximum stack temperature difference, Tdiff. 4) TM and Tdiff as well as Esys decrease with the increase of Vair. Overall, the constrains of (TM ≤ 900℃,
Tdiff

≤ 200℃) can be satisfied together with Esys > 55%, if Vair is chosen properly.

It is concluded that the examined system design is suitable as an APU. Moreover, the system model presented here can be used for the design and operation optimization of similar systems, taking factors such as the stack size and performance, the thermal constrains the stack can withstand into considerations.
Enabling Separator Modification with Sulfiphilic CoTe2 Sites on Electrospun Carbon Nanofibers for High-Performance Lithium-Sulfur Batteries
Authors: Wei Zhen , Liu Zhi , Li Xing , Fei Ling
Published: December 2024

Lithium-sulfur batteries (LSBs) have been recognized as a promising candidate for next generation electrochemical energy-storage technologies owing to their unparalleled theoretical capacity and energy density compared to conventional lithium-ion batteries. However, the sluggish redox kinetics of the electrochemistry and the formidable dissolution of polysulfides during cycling lead to poor sulfur utilization, serious polarization, cyclic instability, and hazardous Li corrosion/dendrites issues. Herein, cobalt tellurides and carbon nanofibers composites (CoTe2@CNFs) were designed, synthesized by facial electrospinning, and applied to modify the separator of Li–S batteries, providing a viable solution for these challenges. The composites feature polar CoTe2 nanoparticles embedded in each carbon nanofiber, and the carbon nanofibers intertwine with each other to form an interconnected 3D nanofiber network. The sulfiphilic CoTe2 nanoparticles exhibit dual functionality, as they both strongly interact with soluble polysulfides and dynamically facilitate polysulfide redox reactions. Moreover, the 3D nanofiber network not only provides an additional physical barrier to lithium polysulfides (LiPSs) but also enables uniform sulfur distribution, thereby significantly inhibiting LiPSs shuttling and accelerating sulfur conversion reactions. In summary, the functionally modified separator synergistically works as both redox mediators, catalyzing the sulfur conversion, and a buffer layer, regulating Li ions stripping/deposition behaviors. This work has provided a new avenue for designing nanomaterials with synergistic effect of catalytic conversion and chemisorption of polysulfides to promote high-performance Li-S batteries. Furthermore, it is expected to inspire the engineering of novel material architectures with enhanced properties for various energy-storage devices.
Zr-Based Thin Film Metallic Glasses As High-Efficiency Materials for Electrocatalysis of the Hydrogen Evolution Reaction
Authors: Howard Jerry , Carlson Krista , Chidambaram Dev
Published: December 2024

The production of hydrogen through water electrolysis is a major limiting step in the implementation of hydrogen-based energy storage. Currently used materials for catalyzing the hydrogen evolution reaction require large overpotentials, reducing the efficiency of hydrogen production. Metallic glasses are of interest for use in electrocatalysis due to their high activity and diversity of catalytic sites. However, only a small selection of metallic glass compositions can be manufactured into bulk parts, necessitating the use of metallic glass coatings. In this research, a Zr-based metallic glass was produced as a thin film using sputtering deposition. Combinatorial co-sputtering was used to produce a library of quaternary Zr-based metallic glasses to enable high-throughput characterization of the anode material and electrochemical testing. Metallic glass surfaces were characterized prior to and after electrochemical testing using a range of techniques to explore the physiochemical properties of the catalytic surface. Nano-structured metallic glass coatings are a promising material for catalysis of the hydrogen evolution reaction.

This work is funded by ARPA-e under DE-AR0001697. JRH is funded as a fellow under the NSF GRFP.
Scalable Cross-Flow Multi-Tubular Electrochemical Cell for Electrochemically Mediated CO2 Capture
Authors: Lee Younghun , Massen-Hane Michael Edward , Hatton T. Alan
Published: December 2024

The global concentration of carbon dioxide (CO2) in the atmosphere has increased by approximately 23 percent over the past 50 years, reaching an all-time record of 425 parts per million in March 2024. In efforts to achieve negative carbon emissions, electrochemically mediated CO2 separations have recently garnered increasing attention as a promising pathway due to their low energy requirements, modular scalability, and straightforward integration with renewable energies. Conventionally, flow systems requiring a membrane to prevent mixing of the anolyte and catholyte in the cell have been utilized in CO2 capture systems employing electrochemical reactions. However, the pumping costs and membrane have adverse impacts on energetics and CO2 transport in electrochemical systems.

In this study, a cross-flow multi-tubular electrochemical cell based on supported liquid membranes (without a solid membrane) between two gas diffusion electrodes with porous and tubular structures is proposed. The conductive and tubular electrodes are manufactured through a facile two-step dip coating method employing Teflon AF 2400 and silver, which maximizes the stability and electrical conductivity of the electrodes. This novel cell architecture enables continuous operation through diffusion without pulsed flow or mixing, as well as a two-stage system combining activation/absorption and deactivation/release, thereby minimizing thermodynamic and operating energy consumption. Furthermore, the cylindrical diffusion profile and high surface area of the hollow fiber electrodes ensure superior CO2 fluxes compared to conventional flat plate electrodes. In particular, this proposed cross-flow system, where anodic and cathodic fiber electrodes are orthogonally arranged within the cell, can realize a compact design and ease of scaling up. Ultimately, this system not only serves as a "process-ready" separation device but also offers a cutting-edge perspective on the fabrication of electrochemical cell structures.

Figure 1
Carbon Fixation for Food Production
Authors: Almeida Simoes Andressa Juliana , Sit Chun Yat , Hong Sukhwa , Wachtveitl Josie , Moon Yewon , Kenis Paul J.A
Published: December 2024

Demand for food is ubiquitous around the globe. Different regions of the world meet their food needs in different ways, but at times the normal production and supply mechanisms are interrupted. Reasons include drought and natural disasters such as hurricanes, tornados, floods, or situations arising from conflicts. The work here pursues the vision to develop a system able to produce food from minimal resources, e.g., water, as well as N2, O2, CO2 from air, using renewable energy (wind, solar, hydro). Realization of this vision will require CO2 capture, carbon and nitrogen fixation, as well as conversion of the carbon and nitrogen substrates into biomass for subsequent processing into food formats such as shakes or puddings.

This presentation will focus on developing the carbon fixation capability to help enable the vision of generating food from minimal resources. The specific approach involves the electroreduction of CO2 to CO in a membrane electrode assembly (MEA) cell, followed by the electroreduction in bipolar cells with a porous solid electrolyte of CO to acetate. This two-step approach is expected to achieve a higher selectivity for acetate than direction reduction of CO2 to acetate. An additional advantage is that the product stream of the second step is comprised of pure water with water-soluble products (acetate, traces of ethanol, etc.) without the presence of electrolyte salts, avoiding separation steps. This presentation will focus on catalyst, electrode, and cell optimization for both CO2 to CO and CO to Acetate conversion, with a focus on scaling of single cells and enhancing durability over multi-hour runs.
Crystal Engineering of Metal-Organic Framework As a Catalyst Design for Water Splitting and Sensing
Authors: Arun Kumar Paulraj , Gayathri Sampath , Han Jong Hun
Published: December 2024

Metal-organic frameworks (MOFs) offer a versatile platform for heterogeneous catalysis due to high porosity and structure tunability, where a rational choice of metal and ligand nodes can effectively control the reactivity of catalytic metal centers in MOFs and MOF-derived materials. This work reports the influence of heterometal inclusion on the crystal engineering of MOFs on their catalytic performance of derived and pristine material towards sensing and water splitting applications. Firstly, a high-performance MOF-based glucose sensor was designed, by integrating trivalent Fe into Ni (II)-based benzene-dicarboxylate (BDC-NH2) MOF, resulting in increased valency of nickel with high-valent Ni3+ formation and enhanced pore sizes by utilizing dissimilar bond stabilities between the Fe3+ dopant and the host Ni2+ ion, and the coordinating ligand. Secondly, a Ni-doped Co-based zeolitic imidazole framework (ZIF-67) precursor was employed to design mesoporous bimetallic (Ni/Co–P) phosphide electrocatalyst for hydrogen evolution reaction (HER). Ni-inclusion altered the pore structure and surface chemistry of ZIF-67, facilitating effective phosphidation, and forming a high-performing Ni-doped Co2P/CoP catalyst due to synergistic activity, porosity, and conductive N-doped carbon. This study highlights the versatility of MOF-derived catalysts with tailored properties for diverse electrochemical applications, offering insights into advanced catalyst design strategies.
Manufacturing Scale-up of ALD Onto Synthetic Graphite Powder in a Continuous Vibrating Reactor for Battery Applications
Authors: Castro Brandon , Broerman Andrew , Gump Christopher , Dameron Arrelaine A
Published: December 2024

As the demand for improved performance in battery material increases, development of large-scale, high-throughput ALD processes and equipment is necessary to meet production demands. Forge Nano has previously demonstrated ALD deposition onto natural and synthetic graphite over a range of scales (50 g – 50 kg) in both rotary bed and fluidized bed reactors. This process has now been successfully scaled-up to the highest throughput system (ton scale) with a continuous vibrating reactor (CVR). The CVR (and associated product Circe) is a spatial ALD system where the substrate powder travels down a porous deck, driven by vibration. Process gases flow at atmospheric pressure perpendicularly to the powder flow, up through the porous deck, and fluidize the moving powder bed and mixing the particles with the gases top to bottom in the process. The substrate travels through zones of the precursors and purge gases of an ALD cycle (Figure 1).

Reproducibility per batch and relative to successful graphite deposition criteria from smaller ALD batch systems was explored in a CVR system configured to perform 4 TMA/H2O ALD cycles. Commercial synthetic graphite was coated at a rate of 33 kg/h, in 45-50 kg batches, at 180°C. Precursor flow was controlled based on the calculated stoichiometry required to achieve 100% titration of available surface sites, as determined in experiments performed in small scale fluidized bed reactors. Samples of coated product were taken from the reactor effluent every 10 minutes. Effluent samples of replicate runs were analyzed using ICP to determine the Al loading, and to characterize the reproducibility of the coating process. An average of 84 ± 13 ppm Al was deposited for all replicate runs (each totaling 4 ALD cycles). The 1-2 initial samples for a given run comprised lower Al mass loadings, likely due to the system approaching steady state in terms of substrate and precursor flow. Additional tests with 150% of the calculated stoichiometric TMA flow rate showed the deposition to be self-limiting. Finally, the coated material was homogenized and then recycled through the CVR to demonstrate reproducibility at higher deposition levels. This material was recycled multiple times to achieve 20 TMA/H2O ALD cycles and establish an average and linear growth rate per ALD cycle. Additionally, bed height and speed conditions were explored to achieve higher material processing rates. Coated materials were tested in coin cells as anode powders for lithium-ion batteries, with performance being compared to coated graphite prepared via more traditional deposition in fluidized bed reactors under vacuum conditions. Coated materials demonstrated that increasing coating levels increased first cycle coulombic efficiency (FCE), reversible capacity, and cycle life.

Figure 1. Schematic and photo of the spatial CVR ALD system

Figure 1
Addition of Iodine Compounds in H3PO4 Solution for the Increase in Si3N4 Etching Rate
Authors: Han Jongwon , Lim Sangwoo
Published: December 2024

Highly selective etching of silicon nitride (Si3N4) layers in the Si3N4/SiO2 multi-stack structure is crucial for the fabrication of 3D NAND flash memory devices. A high-temperature 85 wt% phosphoric acid (H3PO4) solution is commonly used for this process. With the increasing demand for higher-density memory devices, the number of stacked Si3N4-SiO2 pair-layers in 3D NAND devices continues to increase. This increase in the number of stacks produces various challenges in the selective Si3N4 etching process. For example, the Si3N4 etch byproduct cannot be effectively diffused out of the 3D NAND structure due to the high viscosity of the 85 wt% phosphoric acid solution. Additionally, the accumulated Si3N4 etch byproduct suppresses the etching reaction of Si3N4 by Le Chatelier’s principle. Moreover, in the high temperature 85 wt% phosphoric acid solution, the SiO2 layers in Si3N4/SiO2 multi-stack structures can be etched and become thin. The thinning of SiO2 layers can hinder post etching process such as metal deposition. Although some additives were introduced to suppress SiO2 thinning, they also disrupted the Si3N4 etching reaction, leading to lower throughput in the selective Si3N4 etching process. However, given the economic importance in the industry, increasing the etching rate of Si3N4 is crucial for improving throughput in the selective Si3N4 etching process.

In this study, iodine compounds which were expected to increase the Si3N4 etching rate by participating in the Si3N4 etching reaction, were introduced to the 85 wt% phosphoric acid solution. The effects of each additive on the etching rate were examined in Si3N4 and SiO2 films and Si3N4/SiO2 multi-stack structures which were prepared by depositing Si3N4 or SiO2 films using plasma-enhanced chemical vapor deposition. These films and Si3N4/SiO2 multi-stack structures were etched using an 85 wt% phosphoric acid solution with iodine compounds at 160 ºC for 15 min. It was observed the addition of iodine compounds to the phosphoric acid solution increased the etching rate of Si3N4 up to 21% on film and 17% on multi-stack structure compared to the condition of bare 85 wt% phosphoric acid solution. It is thought that iodine compounds can provide lone pair electrons to the Si atom in the Si3N4 layer, which has been conducted by water molecule of bare phosphoric acid solution. When this nucleophilic substitution occurs on the Si atom, the broken of Si-N bond which is the rate determining step of Si3N4 etching reaction will be followed. Since the addition of iodine compounds in addition to H2O in 85 wt% H3PO4 solution increases total concentration of species participating rate determining step, the etching rate of Si3N4 is accelerated. These results suggest that addition of iodine compounds can enhance throughput in selective Si3N4 etching processes. This is attributed to the participation of iodine compounds in the nucleophilic substitution of the Si3N4 etching process.
(Invited) High-Performance Ge/Si Electro-Absorption Optical Modulator and Its Highly-Efficient Photodetector Operation
Authors: Fujikata Junichi , Ishikawa Yasuhiko
Published: December 2024

We studied a high-speed Ge/Si EAM evanescently coupled with a Si waveguide of a p–n junction for a high-bandwidth optical interconnect over a wide range of temperatures from 25 °C to 85 °C.

Figure 1 (a) -(c) show schematic diagrams of a Ge/Si EAM on a Si rib waveguide with a lateral pn junction and cross-sectional TEM image of a Ge/Si EAM. The Ge/Si EAM consists of an evanescently coupled structure with a Si rib waveguide. The stack Ge/Si layer width was changed from 0.3 mm to 1.0 mm, and the Ge height was about 300 nm.

Figure 2 (a) and (b) show output waveforms of 112 Gbps PAM-4 with 2^7-1 PRBS and 100 Gbps NRZ with 2^7-1 PRBS at 1550 nm wavelength, measured at room temperature.

We demonstrated 56 Gbps high-speed operation at high temperatures up to 85 °C. From the photoluminescence spectra, we confirmed that the bandgap energy dependence on temperature is relatively small, which is consistent with that of the operation wavelengths with increasing temperature for a Ge/Si EAM. We also demonstrate a high-speed and high-efficiency Ge photodetector. The photoresponsivity was enhanced by the F-K effect and avalanche-multiplication effect in the C+L band wavelengths. These results demonstrate that the Ge/Si stacked structure is promising for both high-performance optical modulators and photodetectors integrated on Si platforms.

Reference:

J. Fujikata et al., Opt. Express 31(6), 10732 (2023).

J. Fujikata et al., Opt. Express 28(22), 33123 (2020).

Figure 1
Development of Data-Driven Feature Value Map Toward High-Performance Material Exploration
Authors: Yamada Tetsuya , Kitada Riku , Hayashi Fumitaka , Teshima Katsuya
Published: December 2024

Currently, over 100,000 data on inorganic compounds was reported in the Inorganic Crystal Structure Database (ICSD). Until now, exploration of functional materials has been experimentally carried out using intuition and experience from such huge amount of materials. This approach needs several trials and errors, resulting in consuming times. To overcome this issue, we introduce data-driven exploration system that is guided by crystal structure, composition, and their properties. Since functional performances are strongly dependent of material's properties, this approach should potentially lead to novel discoveries beyond the subjective perception of the researcher. Our research goal is development of a data-driven feature value map that is strongly correlated with a functional performance. To achieve this, we aimed to find contribution factor of material performance in X-ray diffraction (XRD) profiles and structural properties. We also aimed to understand the material exploration efficiency using the feature value map that was composed of these descriptors.

Approximately 100 kinds of crystalline materials were grown and their functional performance was measured. The feature value map was depicted using XRD profiles of over 60,000 reference data and this experimental data. The feature values extracted from XRD profiles (XRD feature values) and structural properties (structural feature values) were used as the explanatory variable to depict the map using t-SNE. The contribution factors for material performance were analyzed by multivariate regression analysis.

The generated feature value map only using XRD feature values exhibits that similar materials in crystal structure make clusters in the map, indicating good explanatory power for crystal structures. However, its regressive prediction accuracy for material performance show low coefficient of determination (COD) at 0.18. By adding some structural feature values, the COD improved up to 0.7. This result clearly indicates the XRD feature values are not major contributing factor and other factors are necessary for high predictive map construction. Under the updated map, we succeeded to find novel material with high functional performance. The detail will be reported in the presentation.

Acknowledgement

This work was partly supported by Priority Project in Aichi Knowledge Hub Aichi, JST Green Technologies of Excellence, the Strategic Innovation Program (SIP) of the Cabinet Office, and joint research with a company.
Dielectric Response Using Long-Range Neural Network Potential
Authors: Dhattarwal Harender , Gao Ang , Remsing Richard C.
Published: December 2024

Machine learning-based neural network potentials are revolutionizing molecular dynamics simulations enabling large system sizes and longer time scales with ab initio-level accuracy. Conventional neural network potentials, however, rely on a local description of atomic interactions but can not predict system properties where long-range interactions become important. Several methodologies have been developed to embed the long-range interactions in the neural network potentials. Here, we explore the transferability of a recently developed long-range self-consistent field neural network (SCFNN) by modeling the dielectric saturation in water. The SCFNN model was trained only in the linear response region but correctly predicts the dielectric response and saturation of the dielectric constant of water at higher field strengths. We also examine classic theories and quantify the structural underpinnings of dielectric saturation, including electronic polarization effects. Our results highlight that the focus of SCFNN to learn the physics associated with long-range response makes it transferable. We expect that the transferability of the current SCFNN model can be extended further to aqueous electrolytes by including additional local interactions, such as those between water and ions.
A Novel Approach to State-of-Health Estimation for Lithium-Ion Batteries Using User Profile Data
Authors: Song Young Chan , Jang Il-Chan , Woo Jung-Je , Seo Joon Kyo
Published: December 2024

The State-of-Health (SOH) of lithium-ion batteries is a crucial indicator for assessing battery life and safety. Traditional methods for estimating SOH, which rely on battery capacity measurement or electrochemical impedance spectroscopy, are often costly and time-consuming. This study proposes a novel approach utilizing user profile data, which includes time-dependent charging and discharging patterns that can be collected easily and inexpensively. The developed SOH descriptor demonstrated a high correlation with capacity-based SOH assessments. Our findings confirm that user profile data provides a viable, efficient means to estimate the SOH of lithium-ion batteries, offering significant implications for optimizing battery management systems and enhancing battery safety and lifespan predictions.
(Invited) Design Insights into Solid Electrolytes with Machine Learning Interatomic Potentials
Authors: Ong Shyue Ping , Mishra Adesh , Qi Ji , Yu Zihan
Published: December 2024

Machine learning interatomic potentials (MLPs) have had a transformative impact in the computational modeling of materials by enabling accurate simulations at length and time scales beyond that accessible by ab initio methods. In this talk, I will share new insights into the design of solid electrolytes (SEs) for all-solid-state rechargeable alkali-ion batteries from MLP-based MD simulations. I will demonstrate how the cation chemistry can influence grain boundary lithium concentration in perovskite SEs, providing a means to enhance overall conductivity. I will also discuss the effect of anion chemistry on alkali conductivity in crystalline and amorphous SEs. These new insights can guide the rational design of high conductivity SEs through compositional tuning as well as processing conditions.
Optimization of 3D Battery Geometries Using a Combination of Accurate Energy Prediction Models and Automatic Geometry Generator
Authors: Miyamoto Kaito
Published: December 2024

In order to enlarge the IoT ecosystem, there is a growing need for microbatteries with high areal energy density. A promising approach to improve areal energy density includes using three-dimensional (3D) electrodes, which allow for the holding of more active materials without increasing the internal resistance. Nonetheless, pinpointing the optimal 3D geometry is a challenging task, reliant on the printable materials, the resolution of the production machinery, and the usage of the battery. This constitutes a multiobjective optimization problem, introducing substantial difficulties even when computer simulations are employed because of their high computational cost.

To overcome this challenge, we propose a novel approach for the automated identification of optimal 3D battery geometries, which combines quick and accurate energy prediction models with an automatic geometry generator (AGG). [1-4] The energy prediction models employ simple principal component regression, which results in a significantly reduced computational cost. [2] AGG constructs a 3D geometry by filling the empty cell space with cuboid-shaped electrodes (electrode elements). The placement of each electrode element is determined automatically through the Monte Carlo tree search (MCTS) algorithm, leading to the designation of this method as AGG-MCTS. Given that the dimensions of the electrode elements are determined following the resolution of using fabrication equipment, such as 3D printers, our method ensures the generation of only manufacturable geometries. The combination of the energy prediction models and AGG-MCTS enables the rapid identification of optimal 3D battery geometries, without using human intuition and experience.

In this study, we demonstrate the efficacy of our approach through its application to two standard electrode pairs: LiFePO4/Li4Ti5O12 (LFP/LTO) and LiNi0.5Mn0.3Co0.2O2/graphite (NMC/Graphite). Despite the distinct discharging behaviors of these systems, our regression models accurately predict the discharge-current-dependent energies of both systems.[4] By integrating these models with the AGG-MCTS, we successfully identify frontier solutions and obtain optimal geometries that display 30% - 40% greater energy than the current state of the art. Notably, optimal geometries vary in response to the discharge current and the specific electrode combination. Our approach uniquely facilitates the discovery of material- and discharge-current-dependent optimal geometries for the first time. This advancement underscores the significance of custom-designed batteries for a variety of IoT applications and highlights our method’s potential to enable such designs.

[1] Miyamoto, et al., iScience, 23, 101317 (2020).

[2] Miyamoto, et al., Cell. Rep. Phys. Sci., 2, 100504 (2021).

[3] Miyamoto, et al., J. Power. Sources, 536, 231473 (2022).

[4] Miyamoto, in preparation (2024).
Electric Vehicle Battery Lifespan Diagnosis Technology Based on Resistance Trends Under Real-World Operating Conditions
Authors: Park Sang Jun , Kang ByoengSu , Kim Woojoong , Kang Minjun , Lim Chae ho , Hong Youngsun
Published: December 2024

As part of global efforts towards low-carbon green growth for a sustainable future, the rapid adoption of electric vehicles is underway worldwide. Consequently, the importance of battery-related technology is increasing, and research on battery lifespan and fault diagnosis has emerged as a crucial topic. However, due to environmental and temporal constraints, lifespan diagnosis technology based on accelerated laboratory tests and equivalent circuit modeling faces challenges in accurately reflecting the diverse environmental factors such as degradation under actual driving conditions. Therefore, this study monitors data from electric vehicles in actual operation to analyze the driving patterns of users. Based on these patterns, charging and discharging experiments were conducted on 18650 cylindrical batteries to investigate their characteristics under real-world conditions. The degradation characteristics under actual operating conditions were then trained in an AI model and scaled up to electric vehicle batteries to analyze the accuracy of the AI model. This approach aims to provide insights into electric vehicle battery pack lifespan diagnosis technology.
(Invited) Sparking Autonomous Full Cycle Battery Research
Authors: Stein Helge Sören , Zhang Bojing , Rahmanian Fuzhan , Nuss Leah , Yuan Jun , Heaney Dannika , Ke Qiamin , Vogler Monika , Bhowmik Arghya
Published: December 2024

Materials optimization typically focuses on fine-tuning selected properties of a material for targeted applications. However, optimizing a single material property or component does not necessarily lead to optimized system performance. This talk demonstrates how to design, run, and debug a Materials Acceleration Platform (MAP) that integrates computational and experimental capabilities from dozenz of institutions across Europe to autonomously optimize both material-level properties, like ionic conductivity of electrolytes, and system-level performance, like the end-of-life (EOL) of lithium-ion coin cells, by varying electrolyte formulations.

The MAP leverages automation, robotics, and machine learning to enable high-throughput experimentation, inverse design, and intelligent orchestration of research across the entire battery value chain – from lab benches to manufacturing and back. This holistic, intention-agnostic approach aims to elucidate how materials influence interfaces, components, and full battery packs, and vice versa. By integrating robotic experimentation, intelligent manufacturing, and machine learning models like the Attention-based Recurrent Algorithm for Neural Analysis (ARCANA) of battery lifetime, the MAP seeks to achieve 10-100x acceleration in battery research and development, reducing the current 20-30 year proliferation time to just a few months.

The results demonstrate the MAP's capability to rediscover known trends, like ionic conductivity variation with salt concentration, while also enabling complex multi-scale optimizations spanning materials, components, and full systems. This paradigm shift in research orchestration highlights the power of autonomously linking models, theory, and experiments across domains to spark revolutionary advances in battery technology development.

The talk will conclude with a demo of the Kilofactory, the worlds first fully automated pouch cell factory that starts from active materials precursors and is capable of providing a fully parameterized cell every 15 minutes.
(Invited) Advances in Oxide Thin-Film Transistor Based Inverter Technology
Authors: Nomura Kenji
Published: December 2024

Several advantages in oxide device processing, including low-temperature processability and exceptional uniformity on a large scale, render oxide device technology essential for a wide range of next-generation electronics. Advancing oxide thin-film transistor-based circuits marks a crucial milestone in developing the next generation of cost-effective ubiquitous electronics. This moves forward oxide-TFT to the forefront of transistor technology, marking the commencement of a new era characterized by low-cost mass-production and high-performance. Extensive efforts have been devoted to developing oxide inverters, including NMOS, and CMOS inverters, and excellent characteristics, such as high-speed separation, low-power dissipation, and sufficient noise marge, have been already demonstrated. Nevertheless, persistent open issues, such as the absence of high-performance p-channel oxide-TFT and the lack of doping control, in oxide semiconductors impede the progress of oxide inverter technology development to the next levels.

This presentation reviews recent advances in oxide-TFT inverter technology and delves into open issues that should be addressed for oxide-TFT-based circuit applications. First, I will present the advancements in oxide-TFT inverter technology, encompassing NMOS, PMOS, and CMOS, primarily drawing from our research activities. Subsequently, we will elucidate and discuss strategies for addressing open issues for the development of high-performance oxide-TFT-based circuit applications.
(Invited) High Performance Metal Oxide Thin Film Transistor Using ALD Technology
Authors: Takahashi Takanori , Uraoka Yukiharu
Published: December 2024

Field-effect transistors (FETs) based on oxide semiconductors, mainly In2O3 and ZnO, have been commercialized as channel materials for thin-film transistors due to their features such as electron mobility exceeding 10-50 cm2/Vs, extremely low leakage current, and low process temperature. Recently, FETs that can be applied to ferroelectric memory and back end of line have been demonstrated for implementation in ultra-integrated circuits and semiconductor memory. In order to realize various integrated devices using oxide semiconductors, it is necessary to uniformly deposit ultra-thin films of about 5 nm on a three-dimensional structure from the viewpoint of device integration and suppression of short-channel effects. This research group has shown that amorphous In-Ga-O (IGO) is a promising oxide semiconductor material that can be applied to three-dimensional integrated devices. However, it was shown that IGO-FETs have reliability issues because their threshold voltage (Vth) easily fluctuates in response to voltage stress . The purpose of this study was to examine the factors that contribute to Vth instability and to suppress it by evaluating the relationship between FET reliability and IGO composition ratio and annealing temperature, as well as the effect of crystallization.

Top-contact/bottom-gate FETs with AlOx protective films were fabricated by depositing 10-11 nm-thick IGO channels on SiO2 (85 nm)/n++-Si substrates using ALD method Triethylindium and Trimethylgallium The composition ratio of In:Ga in the IGO film was controlled by adjusting the ratio of growth cycles of the InOx and GaOx layers. positive bias stress (PBS), in which a positive voltage is applied to the gate electrode.

The reliability of amorphous IGO against PBS was found to depend on the composition ratio of In:Ga and annealing temperature. It is known that the formation energy of O-O bonds corresponding to excess oxygen is lower in amorphous oxide semiconductors than in single-crystal and polycrystal structures due to their higher structural degrees of freedom. It was experimentally clarified that electron capture occurs more easily in IGO systems than in other oxide semiconductors (Ex. In-Zn-O), which is consistent with theoretical calculations in previous studies. In addition, we focused on crystalline Ga-doped In2O3 to improve the reliability of the IGO system and developed a deposition process using ALD method. We demonstrated that FETs with polycrystalline IGOs as channels have superior mobility and reliability compared to amorphous IGOs. The present study clarified that excess oxygen must be reduced during deposition of oxide semiconductors using the ALD method, and that polycrystalline oxide semiconductors are effective in improving reliability.
(Invited) Mesoscale Ordered Two-Dimensional Semiconductor Polymers with Tunable Dirac Cones and Flat Bands
Authors: Contini Giorghio
Published: December 2024

Dirac cones, present in the band structure of graphene, are responsible of its remarkable charge-transport properties. However, they are not exclusive to graphene but require that the material presents specific symmetry and delocalized electrons. Efforts have been devoted to identifying 2D materials beyond graphene that offer a greater degree of tunability and a non-zero band gap while retaining high carrier mobility [1].

On-surface synthesis represents an opportunity to manipulate the electronic band structure of the material by varying the molecular building blocks (e.g. by the change of constituent atoms and symmetry). By using a class of heteroatom substituted triangulene monomers we synthesized mesoscale ordered 2D π-conjugated polymers on Au(111) with semiconducting properties arranged in a kagome lattice showing Dirac cone structures and flat bands, theoretically predicted [2-3]. We demonstrate that it is possible to tune the Dirac cone structures and flat bands energy positions by changing the bridging atoms in the triangulene monomers [4]. These results overcome the major barriers to the application of 2D π-conjugated polymers due small domain size and high defect density attained so far.

Although the 2D polymers have been obtained on a metal surface, they can be detached and transferred to other substrates to be used in devices.

References

[1] K. Asano and C. Hotta, Phys. Rev. B 83, 245125 (2011); J.Wang, S. Deng, Z. Liu and Z. Liu, Natl Sci. Rev. 2, 22 (2015).

[2] Y. Jing and T. Heine, J. Am. Chem. Soc. 141, 743 (2019).

[3] G. Galeotti, F. De Marchi, E. Hamzehpoor, O. MacLean, R. M. Rao, Y. Chen, L. V. Besteiro,

Dettmann, L. Ferrari, F. Frezza, P. M. Sheverdyaeva, R. Lui, A. K. Kundu, P. Moras, M. Ebrahimi, M.C. Gallagher, F. Rosei, D.F. Perepichka, G. Contini, Nature Materials, 19, 874 (2020).

[4] D. Dettmann, P. M. Sheverdyaeva, S. Franchi, G. Galeotti, P. Moras, C. Ceccarelli, D.F. Perepichka, F. Rosei, G. Contini, ACS Nano, 18, 849 (2024).
(Invited) Low-Dimensional Hybrid Perovskite Materials: Discoveries and Properties
Authors: Wu Tom
Published: December 2024

As an emerging class of light-responsive semiconductors, hybrid perovskites seamlessly marry the characteristics of organic and inorganic materials, offering a new fertile playground to explore light-matter interaction and advance optoelectronic technologies. In comparison to three-dimensional perovskites, low-dimensional counterparts have been less investigated, but they offer a vast chemical and functional space to navigate. Here, I will discuss our recent effort to use high-throughput calculations to generate large datasets containing structural and property information for 2D hybrid perovskite materials, which is further used to train and validate machine learning models to establish accurate structure-property relationships. The result helps shed light on the impact of various conjugated organic spacers on the electronic structures of 2D Dion-Jacobson perovskites. In addition, I will talk about the exceptional physical properties of a series of zero-dimensional copper-halide perovskites demonstrating efficient self-trapped exciton and single-mode lasing.
A Comprehensive Study of Ferroelectric Properties of Fluorite-Structured Hf1-XZrxO2 Thin Films Grown on Mo Electrode with Various Thicknesses and Compositions
Authors: Park Ju Yong , Kim Se Hyun , Lee Dong Hyun , Yang Kun , Park Geun Hyeong , Park Min Hyuk
Published: December 2024

Since ferroelectricity in Si-doped HfO2 was first reported in 2011,[1] HfO2-based thin films have attracted significant attention as an emerging material for ferroelectric devices due to their advantages such as scalability and compatibility with Complementary Metal-Oxide-Semiconductor (CMOS) processes. Generally, TiN has been used as electrode material in semiconductor processes. However, other electrode materials such as W and Mo have attracted increasing interest for HfO2-based ferroelectric thin films due to their higher remanent polarization (Pr) than the TiN electrode.[2
,3
] Recently, it has been reported that Mo electrodes can be easily oxidized even at low temperatures such as atomic layer deposition (ALD) processes, and the formed MoOx layer can sufficiently act as the oxygen supplier, resulting in the larger orthorhombic phase fraction and higher remanent polarization compared with TiN electrodes.[3] Nevertheless, the effect of the film thickness and composition on the ferroelectric properties of HZO thin films grown on Mo electrodes is yet to be elucidated. Therefore, in this study, the electrical, physical, and chemical properties of HZO films with various thicknesses (6 – 11 nm) and Zr/(Hf+Zr) ratios (0.5 – 0.7) are examined.

In the case of the HZO films grown on the TiN electrode, when the film thickness decreases or the Zr/(Hf+Zr) ratio increases, the switchable polarization (2Pr) decreases with a distortion of polarization-electric field (P-E) curves owing to the increased fraction of the antiferroelectric tetragonal phase. However, 2Pr as high as 57.5 µC/cm2 on the Mo electrode could be achieved even in the 7.6 nm-thick Hf0.4Zr0.
6O2 thin film with a little distortion of the P-E curve. The highest 2Pr of 68.3 µC/cm2 was observed in the 10.9 nm thick Hf0.4Zr0.
6O2 film, which is 31.3 % higher than the highest 2Pr (52.0 µC/cm2) of the HZO thin film on TiN reported so far.[
4] Additionally, in the (Grazing Incidence X-ray Diffraction) results of all samples, it can be observed that the m-phase which deteriorates the Pr values is sufficiently suppressed. These results are consistent with the tendency of previously reported results.[3] Therefore, It is believed that the Mo electrode would induce a higher orthorhombic phase fraction in HZO thin films compared to the TiN electrode resulting in higher 2Pr values. This enables ferroelectricity to be achievable within a wider range of film thicknesses and Zr/(Hf+Zr) ratios.

References

[1] Boescke et al., Appl. Phys. Lett., 99, 102903 (2011)

[2] K. Yang et al., Mater. Sci. Semicond. Process., 164, 107565 (2023)

[3] Y. Lee et al., Appl. Surf. Sci., 648, 158948 (2024)

[4] S. J. Kim et al., Appl. Phys. Lett., 111, 242901 (2017)

Figure 1
Tuning Selectivity of Two-Dimensional Based Gas Sensors Via Monolayer Hexagonal Boron Nitride Encapsulation
Authors: Cyu Ruei-Hong , Chueh Yu-Lun
Published: December 2024

Hexagonal boron nitride (h-BN) serves as an excellent encapsulation material in two-dimensional (2D) materials owing to its insulating nature, high thermal stability, chemical inertness, and impermeability. The surface of h-BN without dangling bonds enables effective shielding of surface charge traps and dangling bond effects on the substrate. Moreover, the defects in h-BN can serve as mediators for charge transfer. In this study, monolayer h-BN grown by CVD is utilized to encapsulate 2D semiconductor gas sensors. We demonstrate that the encapsulated gas sensors exhibit superior stability, and most importantly, significant enhancements in gas selectivity, especially for NO2 and NO, addressing a longstanding issue in gas sensing technology.

Figure 1
(Invited) Novel Materials Chemistry for Applications in Energy Storage and Conversion
Authors: Pinna Nicola
Published: December 2024

The current trend in various energy applications, ranging from batteries to electrolizers, lays in the control of structural, physicochemical and morphological properties of materials and their interfaces. During this presentation, recent scalable strategies for nanostructured materials synthesis, targeting energy and environmental applications will be discussed. Especially, we will focus on one-pot strategies for the fabrication of hybrid and complex nanomaterials focusing on the importance of the organic-inorganic and inorganic-inorganic interfaces. Among the examples presented, we will discuss the synthesis of complex nanostructures and the stabilization of metastable phases for applications in energy, catalysis and environmental remediation. We will see that nowadays the available strategies allow a control in terms of composition, crystalline structure, morphology and nanostructuration that would have been unimaginable just few years ago. Finally, the open challenges the field is currently facing and possible further developments which are needed to meet the always growing demand for high performing materials will be also discussed