bluuebunny/crossref_metadata_2025 huggingface dataset:
A power law solution for FLRW universe with observational constraints
Authors: Sharma Lokesh Kumar , Parekh Suresh , Maurya Sanjay , Singh Kuldeep , Ray Saibal , Mehta Kalyani C. K. , Trivedi Vaibhav
Published: December 2024

This work analyzes a power law solution under [Formula: see text] gravity for an isotropic and homogeneous universe. To construct [Formula: see text] gravity model, we consider the functional form of [Formula: see text] as the sum of two independent functions of the Ricci scalar R and the trace of the energy–momentum tensor T, i.e. [Formula: see text], with [Formula: see text] being a positive constant where we study the cosmological model under the following two cases: (i) [Formula: see text] and (ii) [Formula: see text]. In the framework of [Formula: see text] gravity with homogeneous and isotropic spacetime, the constructed model yields several features on application of the scale factor [Formula: see text]. We employed the Markov Chain Monte Carlo (MCMC) approach to get model parameters [Formula: see text], [Formula: see text] and [Formula: see text] over a redshift range of [Formula: see text]. The model parameter’s restricted values are listed below: [Formula: see text] km [Formula: see text][Formula: see text]Mpc[Formula: see text], [Formula: see text][Formula: see text]km[Formula: see text] Mpc[Formula: see text], [Formula: see text][Formula: see text]km[Formula: see text]s[Formula: see text] Mpc[Formula: see text], [Formula: see text][Formula: see text]km[Formula: see text]s[Formula: see text][Formula: see text]Mpc[Formula: see text], [Formula: see text][Formula: see text]km[Formula: see text]s[Formula: see text][Formula: see text]Mpc[Formula: see text]. The model was constrained using the Hubble parameter ([Formula: see text]) dataset, Baryon Acoustic Oscillations (BAO) dataset, Pantheon dataset, joint [Formula: see text] + Pantheon dataset and collective [Formula: see text] + BAO + Pantheon dataset. The results from the Planck collaboration group are consistent with these calculated Ho observed values. In order to study and analyze the model, we first look at how the energy circumstances affected our power law assumption. The validity of the model has also been evaluated using the [Formula: see text] diagnostic and the jerk parameter, which are state finding diagnostic tools. We find that the model under investigation agrees with the observed fingerprints within a certain range of constraints.
Investigating Domain Knowledge Graph Knowledge Reasoning and Assessing Quality Using Knowledge Representation Learning and Knowledge Reasoning Algorithms
Authors: Cao Ying
Published: December 2024

Domain Knowledge Graphs are becoming increasingly significant in a multitude of sectors, as they collate distinctive data from a plethora of disciplines. However, in some domains, generic knowledge representation is limited, resulting in problems like duplication and knowledge loss. To solve the above issues, the study first builds a Knowledge Representation Learning model for training and then constructs a Domain Knowledge Graph inference algorithm based on Knowledge Representation Learning for knowledge inference and quality evaluation. The results indicated that the effectiveness of the knowledge-inference-raised method was the best in datasets of different sizes, with the average accuracy, Hits@1, Hits@3 and Hits@10 of 0.906, 0.914, 0.942 and 0.948, respectively. In the results of the link prediction task, the study method had a poor performance for only one relation, with an average accuracy rate of 0.675. In the application results of knowledge graph quality assessment, the interpretability and data fusion ability of both Domain Knowledge Graphs were strong, with the accuracy indexes exceeding 0.95, and the various indexes of simplicity and completeness exceeding 0.88. The above results indicate that our research method is effective in filling in the missing knowledge through knowledge reasoning and ensures data reliability.
Edge-integrated image denosing using a dual branch convolutional neural network
Authors: Huang Yongdong , Liu Qiang , Li Qiufu , Su Weijian , Pei Xiao , Zhu Fengjuan
Published: December 2024

In image denoising, preserving the object edges and fine texture details is crucial for restoring high-quality images. However, most image denoising methods fail to integrate edge information, resulting in excessive smoothing of the denoised images. In this paper, we propose a lightweight edge-integrated image denoising convolutional neural network (EIID), which comprises two parallel branches, namely image branch and the edge branch, to separately handle the input noisy image and its object edge layer. First, EIID obtains the object edge layer of an input noisy image using Laplacian operator. Second, the noisy image is input into the image branch to extract global and local features, while the object edge layer is input into the edge branch, to extract edge features. Finally, a mask fusion strategy is adopted to dynamically fuse the global and local features of the input image and its edge detail features. The fused features are then processed through convolutional operations to recovery the denoised image. Experimental results demonstrate the outstanding performance of EIID on synthetic and real noise datasets. EIID achieves a PSNR/SSIM improvement of 0.13[Formula: see text]dB/0.003 on the grayscale dataset Urban100 and 0.22[Formula: see text]dB/0.001 on the color dataset BSD68 with noise intensity of 25. Moreover, on the real noise dataset PolyU, it achieves a PSNR/SSIM improvement of 0.17[Formula: see text]dB/0.001. Additionally, the parameter count of EIID is one-sixteenth that of Restomer, and its number of floating-point operations is one-fourth.
Accelerating cosmological models in Hoyle–Narlikar gravity with observational constraints
Authors: Maurya Dinesh Chandra
Published: December 2024

In this paper, we explore the cosmic acceleration and the physical aspects of the dark energy nature in Hoyle–Narlikar’s creation-field theory, taking into account observational constraints. We find analytical solutions to the modified field equations for a specific choice of creation field [Formula: see text] with certain background fluid sources as a barotropic fluid and a radiation fluid in a flat Friedmann–Lemaître–Robertson–Walker (FLRW) spacetime universe. From there, we use observational constraints with data from the cosmic chronometer (CC) Hubble data and the apparent magnitude from the Pantheon SNe sample to get the model parameters’ constrained values with [Formula: see text] and [Formula: see text] confidence levels. We look at the physical properties of the models we’ve made using these estimated values of model parameters. To do this, we look at the deceleration parameter [Formula: see text], the effective equation of state parameter [Formula: see text], the jerk parameter [Formula: see text], the snap parameter [Formula: see text], and the energy conditions. We also examine the cosmic behavior of square sound speed [Formula: see text] for the test of causality and viability of the models. We measure the present age of the universe and transition redshift [Formula: see text] for the signature-flipping point. We obtain two transit-phase accelerating universe models with [Formula: see text] Km/s/Mpc, [Formula: see text], [Formula: see text], and [Formula: see text], respectively, with barotropic and radiation fluid sources.
Klein–Gordon oscillators in traversable wormhole rainbow gravity spacetime: Conditional exact solvability via a throat radius and oscillator frequency correlation
Authors: Mustafa Omar , Guvendi Abdullah
Published: December 2024

In this study, we discuss an analytical solution for a set of the Klein–Gordon (KG) oscillators’ energies through a correlation between the frequency of the KG-oscillators and the traversable wormhole (TWH) throat radius. Under such restricted parametric correlation (hence the notion of conditionally exact solvability is unavoidable in the process), we report the effects of throat radius, rainbow parameter, disclination parameter and oscillator frequency on the spectroscopic structure of a vast number of [Formula: see text]-states (the radial and magnetic quantum numbers, respectively). In the process, we only use two loop quantum gravity motivated rainbow functions pairs. Only rainbow functions clearly and reliably fully adhere to the rainbow gravity model and secure Planck energy [Formula: see text] as the maximum possible energy for particles and anti-particles alike. Near the asymptotically flat upper and lower universes connected by the TWH, i.e. for the throat radius [Formula: see text], the energies tend to cluster around the rest mass energies, i.e. [Formula: see text]. Whereas, for [Formula: see text], the energies tend to approach [Formula: see text].
Construction of complexity-free fuzzy Dark Matter wormholes
Authors: Yousaf Z. , Adeel A. , Rizwan M. , Mustafa G. , Ali Akbar
Published: December 2024

This work aims to explore the possibility of wormholes (WHs) fenced by fuzzy Dark Matter (FDM) haloes relying on the Einasto density profile (EDP). The research explains how combining the EDP with an anisotropic stress-energy momentum tensor leads to the formation of WH solutions corresponding to different Einasto index values. We have investigated the existence of fuzzy WHs and developed the shape function for them. An analysis is conducted on the active gravitational mass and the lodging diagrams for a certain form of the shape function. Additionally, we have also examined the exotic matter’s breach of the null energy conditions, the equilibrium conditions, and the complexity factor associated with the fuzzy WHs.
Local existence of a classical solution to the Einstein–Maxwell–Klein–Gordon system in higher dimensions
Authors: Wijayanto Mirda Prisma , Akbar Fiki Taufik , Kosasih Jusak Sali , Triyanta  , Gunara Bobby Eka
Published: December 2024

In this paper, we study the local existence of a classical solution to the coupled Einstein and Maxwell–Klein–Gordon system in higher dimensions. This system provides a toy model to study the dynamics of the complex scalar fields under the influence of the interaction of the gravitational and electromagnetic fields. In the starting point, we introduce the metric of the space-time in the Bondi coordinate. Then, we construct the evolution equation in the form of a single first-order nonlinear integro-differential equation. Furthermore, we show that there exists a unique fixed point that is the solution of the main problem based on the contraction mapping arguments. Finally, for a given initial data, we prove the existence of a local classical solution.
Traveling waves for the closed hypersurfaces in central force fields
Authors: Yan Weiping , Guo Huiru , He Jiawei
Published: December 2024

We consider the front propagation problems for the hyperbolic mean curvature motion in central force fields. Problems of this type describe the long time behavior for the electrically charged membrane with a constant charge per area and a radially symmetric potential moving with the mean curvature motion law. In this paper, we establish the existence of generalized periodic traveling waves with a large speed of propagation under appropriate assumptions on the central periodic force fields.
Planarity of the bipartite graph associated to squares of elements and subgroups of a group
Authors: Pramanik Munna , Pal Pavel , Sardar Sujit Kumar
Published: December 2024

A new kind of bipartite graph is defined in this paper. The work is motivated mainly from a graph introduced by Al-Kaseasbeh and Erfanian [A bipartite graph associated to elements and cosets of subgroups of a finite group, AIMS Math. 6(10) (2021) 10395–10404] and partially from the undirected power graph of a group and from the inclusion graph. For a nontrivial group [Formula: see text], we define a simple undirected bipartite graph [Formula: see text] with the vertex set [Formula: see text], where [Formula: see text] is the set of all elements of the group [Formula: see text] and [Formula: see text] is the set of all subgroups [Formula: see text] of [Formula: see text] such that [Formula: see text] and two vertices [Formula: see text] and [Formula: see text] are adjacent if and only if [Formula: see text]. Here, we classify all the finite groups [Formula: see text] whose bipartite graphs [Formula: see text] are planar. In addition, we also classify the finite groups [Formula: see text] such that [Formula: see text] is outerplanar, maximal planar, maximal outerplanar, star, tree, claw graph, respectively. The planarity of the graph [Formula: see text] corresponding to an infinite group [Formula: see text] has also been investigated here. It is also observed that [Formula: see text] satisfies Vizing’s conjecture.
Autonomous Vehicle Motion Control and Energy Optimization Based on Q-Learning for a 4-Wheel Independently Driven Electric Vehicle
Authors: Hou Shengyan , Chen Hong , Liu Jinfa , Wang Yilin , Liu Xuan , Lin Runzi , Gao Jinwu
Published: December 2024

Motion control and energy-saving optimization are the research hotspots in the field of autonomous vehicles. This study takes four-wheel independent drive (4WID) electric vehicles (EVs) in CDC 2023 Challenge. Aiming to address the issues of desired speed tracking, vehicle body motion control, and energy consumption minimization posed by the challenge, the vehicle driving resistance was analyzed, and a vehicle longitudinal dynamics model was established. The extended state observer (ESO) is utilized to estimate the model error, thereby making the dynamic model approximate the real system. A controller combining a linear quadratic regulator (LQR) and Q-learning is designed. The total torque of the vehicle is obtained by LQR method, and then the torque is distributed to the four wheels by Q-learning, so as to realize the tracking of speed and course, and ensure the smooth operation and energy-saving control of the autonomous vehicles. Simulation results indicate that the proposed control strategy can achieve precise speed tracking control and outperforms both the PID and fuzzy rule controllers in reducing vehicle body motion and energy consumption.
Siamese Network-Based Detection of Deepfake Impersonation Attacks with a Person of Interest Approach
Authors: Samrouth Khouloud , El Housseini Pia , Deforges Olivier
Published: December 2024

Deepfake technology presents critical cybersecurity challenges that have become more popular since easily accessible applications have become more widely available. The proliferation of fake portrait videos constitutes a serious risk to the legal system, society, and personal privacy. The publication of fraudulent explicit content starring celebrities, the circulation of fake political videos, and the use of faked impersonated videos as proof in court of law are all examples of the effects of deepfakes in the real world. In reaction to this growing threat, we propose a
simple
yet
efficient
Person of Interest (PoI) Siamese network-based model to detect deepfake synthetic content in portrait images, providing a preventative measure against the growing danger of deepfakes. On one side and unlike traditional neural networks, which process inputs independently, our approach leverages a Siamese network that processes two inputs simultaneously using identical sub-networks with shared weights and parameters. This twin structure is particularly effective for our adopted PoI methodology, where one input is a reference image of a specific individual, and the other is an image that needs to be verified as either real or fake. By ensuring that both the reference and the suspect image are processed in the same way, the network can accurately learn and detect subtle differences, enabling it to determine whether the second image is a genuine representation of the individual or a deepfake. This makes our method particularly relevant for targeted forensic investigations or security applications where an individual’s media integrity is paramount. On the other side, our proposed method does not require any additional complex biological feature extraction. Despite this simplification, our method achieves comparable accuracy to more complex models that rely on biological feature extraction. This efficiency makes our approach practical for implementation on resource-constrained devices, such as mobile phones and Internet of Things (IoT) systems.
Mixed-Level Modeling and Evaluation of a Cache-less Grid of Processing Cells
Authors: Govindasamy Vivek , Doemer Rainer
Published: December 2024

Modern processors experience memory contention when the speed of their computational units exceeds the rate at which new data is available to be processed. This phenomenon is well known as the memory wall and is a great challenge in computer engineering. The reason for this phenomenon is the unequal growth rate in memory access speeds compared to processor clock rates. In order to mitigate the memory bottleneck in classic computer architectures, a scalable parallel computing platform called the Grid of Processing Cells (GPC) has been proposed. To evaluate its effectiveness, the GPC is modeled at the instruction-level and functional-level using SystemC TLM-2.0, with a focus on memory contention. Individual GPC cells can be switched between the two abstraction levels. Our mixed-level system model enables fast and accurate simulations. We test multiple streaming applications on the GPC, analyze software-based optimization methods and their effects on the GPC, at both abstraction levels. The performance is then compared against the traditional shared memory processor (SMP) architecture. Experimental results show improved execution times on the GPC primarily due to a large decrease in main memory contention.
Heterogeneous Hyperbolic Hypergraph Neural Network for Friend Recommendation in Location-based Social Networks
Authors: Li Yongkang , Fan Zipei , Song Xuan
Published: December 2024

Friend recommendation is an important real-world application in Location-based Social Networks (LBSN), helping users discover potential friends and enhance their overall happiness. LBSN mainly comprises two distinct data structures: spatio-temporal data for human mobility and graph data for social networks. These two data structures make it challenging to model the complex relationships between them, which are essential for comprehensively understanding users’ lives. Previous studies have either modeled user trajectories and social networks separately or used classical simple graph-based methods, where a simple edge links only two nodes, failing to capture the multiple relationships inherent in LBSN. Furthermore, most studies have relied on Euclidean space to train their graph models, which could result in significant distortion because of tree-like social network data structure. To address these limitations, we propose a novel heterogeneous LBSN hypergraph that represents user check-in records and continuous trajectories—comprising multiple Points of Interest (POI)—as hyperedges, enabling the representation of complex spatio-temporal relationships. This approach enables us to link multiple nodes of different types by hyperedges and use hyperbolic spaces to create more efficient graph representations. Additionally, we devise a new type-specific attention mechanism for our Heterogeneous Hyperbolic Hypergraph Neural Network (H
3
GNN), which is end-to-end trainable and employs supervised contrastive learning to learn hypergraph node embeddings for the subsequent friend recommendation task with the help of hyperbolic space. Finally, our model H
3
GNN achieves better results than existing methods on six real-world city datasets, and our ablation studies demonstrate the effectiveness of each component. Additionally, our experiments indicate that H
3
GNN requires less data storage and training time compared to previous methods.
Chang-E: A High-Quality Motion Capture Dataset of Chinese Classical Dunhuang Dance
Authors: Wang Zeyu , He Chengan , Yan Zhe , Wang Jiashun , Wang Yingke , Liu Junhua , Shen Angela , Zeng Mengying , Rushmeier Holly , Xu Huazhe , Yu Borou , Lu Chenchen , Wang Eugene Y.
Published: December 2024

Derived from the mural drawings in the UNESCO-listed Mogao Caves, Dunhuang dance has unique cultural value but faces challenges of digitization and preservation. In this paper, we introduce the first open comprehensive motion capture dataset of Dunhuang dance,
Chang-E
, including full-body movements documented across eight categories, totaling 40 minutes of professional dance (preview available at
https://cislab.hkust-gz.edu.cn/projects/chang-e/
). This dataset contains three formats: skeleton data acquired from motion capture, body mesh generated from skeleton using machine learning, and multiview videos recorded on site. The dataset supports various creative applications for Dunhuang dance culture, as demonstrated by an immersive new media exhibition. Through the curation process, we applied motion inbetweening algorithms to concatenate different dance sequences for choreography. Also, these reinterpreted dance sequences are synchronized with music using retiming techniques, augmenting the rhythms and harmony between the music and dance performance. Furthermore, we applied visual effects on the regenerated motion sequences of digital dancers, achieving artistic and appealing visual results echoing Buddhist discourses of meditation and bodily cognition. The
Chang-E
dataset enables digital preservation and creative reimagination of Dunhuang dance, offering not only high-quality data but also an interdisciplinary collaboration framework for future graphics and cultural heritage research.
Top 10 Most-feared Diagnostic Errors for Radiology Trainees in Pediatric Neuroradiology Emergencies
Authors: Cárdenas Agustín , González Hugo , Martínez de Aragón Calvo Ana , Hilario Amaya , Salvador Elena , Romero Juan , Lechuga Vázquez Carmen , Chen Zhou Zhao Hui , Gonçalves Fabrício Guimarães , Ramos Ana
Published: December 2024

Recognition of imaging findings of the most-feared pediatric neuroradiology diagnostic errors for on-call trainees will aid in the identification and prevention of such errors.
Perspective—Prospects and Challenges of Cu-CNT Composite Interconnects
Authors: Uma Sathyakam P. , Mallick P. S. , Zhao Wen-Sheng , Jain Vasu , Barpanda Anshuman
Published: December 2024

This paper examines the present state of the art of Cu-carbon nanotube (Cu-CNT) composite interconnects in terms of modelling and fabrication. Cu-CNT composites show promise as an upcoming material for very large scale integrated interconnects technology. Different studies show different aspects of aligning CNTs in the composite. The differences in these studies are highlighted and a possible way forward to address the ambiguities is presented with the help of finite element simulations of Joule heating and heat propagation in Cu and Cu-CNT interconnects.
Ultra-Long and Rapid Operating Sodium Metal Batteries Enabled By Multifunctional Polarizable Interface Stabilizer
Authors: Ryu Won-Hee , Jun Seo-Young
Published: December 2024

Sodium metal batteries (SMBs) have been considered as one of the most favorable and economic candidates for next generation batteries to overcome low enenrgy density limitation of sodium ion batteries (SIBs) due to high theoretical specific capacity (1166 mAh g-1), low electrochemical redox potential (-2.71 V vs. SHE). However, ‘moss-like’ dendrite growth that occurs during continuous charging and discharging processes not only threatens the safety of batteries, but also poses several problems to be solved, such as electrolyte consumption, hugh volume expansion, dead Na formation, and low coulombic efficiency. The dendrite problem in the SMBs is similr to that of lithium-metal batteries (LMBs), yet the degree of the issue is further severe than LMBs. Surface stabilization of sodium metal anode should be achieved to realize SMB technologies.

The introduction of functional electrolyte additives is an effective and economical way to overcome these problems and improve the cyclability of SMBs. Based on the similarity between electroplating and sodium deposition reaction, utilization of surface leveler additive in the electrolyte could allow a substantial impact to stabilize sodium metal surface during repeated deposition and stripping process.

In this presentation, we confirmed the surface flattening effect of molecular dipole electrolyte additives at the anode through the Na-Na symmetric cell test. Sodium metal deposition and stripping behavior has been successfully controlled by introducing surface leveler additives for realization of SMBs. Even under rapid charging and discharging situations, additive containing Na-Na symmetric cells showed stable performance for over 2000 hours, which is 5 times longer than the pristine cell without the additive. We confirmed that controlling intrinsic properties of surface leveler additive can effectively further improve cycle performance of SMBs.

[1] S.-Y. Jun, K. Shin, C. Y. Son, J. Park, H.-S. Kim, J.-Y. Hwang, W.-H. Ryu, Advanced Energy Materials, 2024, 2304504

[2] S.-Y. Jun, K. Shin, Y. Lim, S. Kim, H. Kim, C. Y. Son, W.-H. Ryu, Small Structures, 2024, 5, 2300578

[3] S.-Y. Jun, K. Shin, J.-S. Lee, S. Kim, J. Chun, W.-H. Ryu, Advanced Science, 2023, 10, 2301426

[4] J.-S. Lee, K. Shin, S.-Y. Jun, S. Kim, W.-H. Ryu, Chemical Engineering Journal, 2023, 458, 141383

Figure 1
Laser-Scribed Battery Electrodes for Ultrafast Zinc-Ion Energy Storage
Authors: Liu Bo , Huang Ailun , Yuan Xintong , Chang Xueying , Yang Zhiyin , Lyle Katelyn , Kaner Richard , Li Yuzhang
Published: December 2024

Aqueous Zn batteries are promising for large-scale energy storage but are plagued by the lack of high-performance cathode materials that enable high specific capacity, ultrafast charging, and outstanding cycling stability. Here, we design a laser-scribed nano-vanadium oxide (LNVO) cathode that can simultaneously achieve these properties. Our material stores charge through Faradaic redox reactions on/near the surface at fast rates owing to the small grain size of vanadium oxide and interpenetrating three-dimensional graphene network, displaying a surface-controlled capacity contribution (90%-98%). Multiple characterization techniques unambiguously reveal that zinc and hydronium ions co-insert with minimal lattice change upon cycling. We demonstrate that a high specific capacity of 553 mAh g-1 is achieved at 0.1 A g-1
, and an impressive 264 mAh g-1 capacity is retained at 100 A g-1 within 10 s, showing excellent rate capability. The LNVO/Zn can also reach >90% capacity retention after 3,000 cycles at a high rate of 30 A g-1, as well as achieving both high energy (369 Wh kg-1) and power densities (56,306 W kg-1). Moreover, the LNVO cathode retains its excellent cycling performance when integrated into quasi-solid-state pouch cells, further demonstrating mechanical stability and its potential for practical application in wearable and grid-scale applications.

Figure 1
Multifunctional Cyclic Phosphoramidate Solvent for Safe Lithium-Ion Batteries
Authors: Ko Seongjae , Matsuoka Ayaka , Chen Wenting , Iwata Taiga , Otsuka Hiromi , Yamaguchi Shoji , Masuda Takuya , Zheng Qifeng , Shang Rui , Nakamura Eiichi , Yamada Atsuo
Published: December 2024

To enhance the overall safety of electronic devices and energy storage systems, the development of functional electrolytes that improve the thermal stability of rechargeable batteries is of utmost importance. Here, we report a novel cyclic phosphoramidate, 2-(N,N-dimethylamino)-1,3,2-dioxaphospholane-2-oxide (DMAP), which has been newly designed and synthesized as a multifunctional solvent for safe Li-ion batteries.1 Its unique molecular structure, incorporating an amine moiety into a five-membered cyclic phosphate, provides both high electrochemical and thermal benefits: (i) a stable DMAP-derived passivation film (solid electrolyte interphase, SEI) is formed on the graphite surface, thereby suppressing electrolyte reduction, (ii) exothermic reactions induced by the thermal decomposition of the SEI and direct reactions between a lithiated graphite anode and electrolyte salt, which are known to trigger and accelerate battery temperature rise, are largely mitigated thanks to DMAP's inherently high radicals-/Lewis acids-/HF-scavenging abilities, (iii) the moisture sensitivity is improved with reduced nucleophilic attack at the P atom caused by water contamination in the electrolyte due to the presence of a substituted N atom in the DMAP, thus enhancing storage stability, and (iv) the stable cycling of LiFePO4 cathodes is achieved based on moderate oxidation stabilities and suppressed aluminum current collector dissolution in the DMAP-based electrolytes. Importantly, all these advantages can be obtained with DMAP used as both an electrolyte solvent and additive, regardless of the types of salts (LiFSI or LiPF6) and co-solvents (fluorinated ethyl methyl carbonate or dimethyl carbonate) employed.

We believe that our solvent-design strategies, based on molecular modification and optimization, combined with fine-tuning the elements in the molecular structure, can endow the electrolyte with highly functional physicochemical and electrochemical properties, thus opening new possibilities for developing safe batteries with high energy densities.1,2

S.Ko, A.Matsuoka et al., R.Shang and A.Yamada, ACS Energy Lett., 9, 7, 3628–3635 (2024)

Q.Zheng et al., E.Nakamura and A.Yamada, Nat. Energy, 5, 291-298 (2020)

Figure 1
Imaging in-Situ Silver Reduction Mechanisms By Zn-Ion Cathodes
Authors: Smith Paul
Published: December 2024

The incorporation of silver ions into cathodes has significant potential to enableimprovement in electrical conductivity via in-situ generatedatomic and nano-distributed silver metal, which in turn can improve fast rate performance in devices spanning Li, Na, Al and Zn ion batteries. While the silver metal produced is widely cited to enhance intraparticle conductivity very few studies test the "effective range" of in-situ generated silver metal; namely, whether interparticle contact is enabled on a wide enough scale to effectively mimic a functional carbon/binder composite. Here, we use operando spectroelectrochemistry to show the evolution of silver networks produced from mixed silver metal oxide precursors on first discharge in aqueous Zn-ion electrolyte. Numerous contemporary silver vanadates struggle under the same conditions where silver molybdates attain total reduction efficiencies exceeding 94% and with higher energy. However, due to the subsequent molybdate mechanism, this result may be a trade for cycle stability.
Ultrasonic Atomization of New Alloys for Powder-Based Anodes in Next-Generation Non-Lithium Batteries
Authors: Ciftci Jakub , Kalicki Bartosz , Choma Tomasz , Morończyk Bartosz , Żrodowski Łukasz
Published: December 2024

Improved battery performance has led to significant advancements in anode materials, with powder-based anodes emerging as a promising alternative to traditional graphite anodes[1,2]. Next-Generation Non-Lithium Batteries, like potassium and magnesium–ion batteries require anodes tailored to the ion diffusivity and anode-electrolyte-cathode compatibility[3,4]. Candidates like bismuth, magnesium, and antimony-based anodes can maximize specific capacity and cycling stability. Passivation film formed on their surface causes large potential drop and energy loss[5]. The alloys with tailored chemical composition can improve the electrochemical behavior of the anodes and significantly promote film formation influencing the interface with electrolyte[6]. Current powder-based anodes preparation methods involve mechanical milling, which produces irregular particles and distorts the structure obtained by eutectic solidification, which can showcase outstanding electrochemical properties[7,8]. We propose a powder production method based on ultrasonic atomization technology[9]. This technology uses the vibrations to eject the particles from liquid metal. Plasma or induction heating can be used for melting, allowing a wide range of metals to be processed. Powders obtained by ultrasonic atomization possess high sphericity which can stabilize the dissolution rate of the anode during cyclic charging and facilitate obtaining uniform coating thickness. Thanks to vibrations instead of high-velocity gases the powder production unit is much smaller and suitable for research and alloy development.

[1] J. Zhao, Z. Wei, N. Chen, F. Meng, R. Tian, Y. Zeng, F. Du, Energy Storage Mater
2024, 65, DOI 10.1016/j.ensm.2023.103127.

[2] B. Fu, G. Liu, Y. Zhang, Z. Liu, X. Xie, G. Fang, S. Liang, ACS Energy Lett
2024, 3292.

[3] Z. Zhao-Karger, Y. Xiu, Z. Li, A. Reupert, T. Smok, M. Fichtner, Nat Commun
2022, 13, DOI 10.1038/s41467-022-31261-z.

[4] D. Gu, Y. Yuan, J. Liu, D. Li, W. Zhang, L. Wu, F. Cao, J. Wang, G. Huang, F. Pan, J Power Sources
2022, 548, DOI 10.1016/j.jpowsour.2022.232076.

[5] F. Liu, G. Cao, J. Ban, H. Lei, Y. Zhang, G. Shao, A. Zhou, L. zhen Fan, J. Hu, Journal of Magnesium and Alloys
2022, 10, DOI 10.1016/j.jma.2022.09.004.

[6] X. You, X. Zhang, C. Yu, Y. Chen, H. Li, Y. Hou, L. Tian, N. Yang, G. Xie, Journal of Rare Earths
2023, 41, DOI 10.1016/j.jre.2022.04.011.

[7] S. B. Wang, Q. Ran, R. Q. Yao, H. Shi, Z. Wen, M. Zhao, X. Y. Lang, Q. Jiang, Nat Commun
2020, 11, DOI 10.1038/s41467-020-15478-4.

[8] L. Cao, M. Zheng, G. Dong, J. Xu, R. Xiao, T. Huang, J Mater Sci Technol
2025, 211, 278.

[9] A. Priyadarshi, S. Bin Shahrani, T. Choma, L. Zrodowski, L. Qin, C. L. A. Leung, S. J. Clark, K. Fezzaa, J. Mi, P. D. Lee, D. Eskin, I. Tzanakis, Addit Manuf
2024, 83, DOI 10.1016/j.addma.2024.104033.
Enhancing Ni-Rich Lithium Metal Battery Performance By Mitigating Transition Metal Migration with Functional Separators and Additives
Authors: Seo Junhyeok , Kim Minjae , Cho Jaegu , Cho Kuk Young
Published: December 2024

Achieving high energy density in lithium-ion batteries remains an ongoing challenge. To meet this requirement, electrodes with high capacity are essential. Lithium metal batteries, employing high-nickel NMC cathodes and lithium metal anodes, represent next-generation secondary batteries that can fulfill these demands. Despite the advantage of high energy density in lithium metal batteries, they tend to exhibit unstable long-term charge-discharge behavior due to issues such as dendrite formation on lithium metal and the collapse of active materials in the cathode.

Therefore, we aim to mitigate the crosstalk of transition metals in the cathode, thereby enhancing cell performance. To achieve this, we have developed a functional separator designed to shield the migration of dissolved transition metal ions. By incorporating this new functional separator along with an additive that stabilizes the cathode active material, we have successfully reduced the migration of dissolved ions by 84% and significantly improved cycle performance.
Investigation of the Temperature Behavior of Silicon-Rich Multilayer Pouch Lithium-Ion Battery Cells and Its Effect on Cycle Life and Rate Capability
Authors: Bosch Hannah , Diller Felix
Published: December 2024

Due to its high energy density and fast charge capability, silicon is an excellent active material, especially in electrical vehicles (EV) applications. The fast charging capability can be reasoned through its higher potential against Li/Li+ when compared to graphite, reducing the risk of Li-plating. As a result of the volume change of silicon during the (de-) lithiation processes, a continuous reformation of the solid electrolyte interface (SEI) takes place. FEC is used as an additive or as a co-solvent to improve the SEI formation. It reported in literature that FEC decomposes at elevated temperatures starting from 45°C [1]. As such elevated temperatures can easily be reached, especially during the charge step in applications where bigger battery formats are used, the temperature behavior of high silicon wt% Lithium-Ion Batteries should be investigated more thoroughly.

To the best of our knowledge, a focus on the temperature behavior of multilayer pouch cells (MLP) with a very high silicon content (70wt%) has not been subject of research so far. Therefore, this study gives important insights into the electrochemical and thermal behavior of silicon within bigger battery formats.

MLP cells with 5 Ah were built and tested for their rate capabilities and their temperature behavior. The cells consisted of 70wt% of silicon as the anode material and a high nickel cathode material. Rate tests were conducted at 10 °C, 25 °C and 40 °C with MLP cells. The resistances were measured at three States of Charge points 25%, 50%, and 75% to investigate the temperature impact on the resistance. Additionally, the cycle lifetimes of the MLP cells were investigated at different fast charging C-rates (C/2, 2C, 5C) until 80% State of Health (SoH) at 25 °C.

These results give important information on the performance of silicon based 5Ah lithium-ion batteries in a bigger format. The temperature behavior needs to be understood, as the battery‘s thermal management has to be adapted accordingly, especially for application purposes such as EVs.

The study is investigated in the project “CAESAR”, funded by the German Federal Ministry for Economic Affairs and Climate Action (BMWK) under grant number 03El3046F. We thank BASF SE for the NCM cathode material, Wacker Chemie AG for the silicon anode material and E-Lyte for the electrolyte.

[1] T. Teufl, D. Pritzl, L. Hartmann, S. Solchenbach, M. Mendez, H. Gasteiger, “Implications oft he Thermal Stability of FEC-Based Electrolytes for Li-Ion Batteries”, J. Electrochem. Soc., 2023, 170, 020531, DOI: 10.1149/1945-7111/acbc52.
Analysis of Lithium-Ion Distribution Uniformity and Artifacts in Lipon Solid Electrolyte Material Based on Esm
Authors: Choi Youngwoo , Kim Seonghyun , Cho Su-Ho , Ahn Chi Won , Hong Seungbum
Published: December 2024

The advancement of electronic devices, such as electric vehicles and drones, has led to an increased focus on battery research. Lithium-ion batteries are widely used for their high energy density and long cycle life. However, using liquid electrolytes in these batteries presents several challenges, including leakage risks, flammability, and the formation of dendrites, which can lead to safety hazards and reduced battery performance.

Solid electrolytes offer several advantages, such as enhanced safety, prevention of leakage, and suppression of dendrite formation. These benefits can potentially address the issues associated with liquid electrolytes. However, solid electrolytes also face challenges, including difficulties in manufacturing, lower ionic conductivity, and mechanical stability issues, which hinder their commercialization. Uniform distribution of lithium ions within solid electrolytes is crucial to ensure consistent performance and prevent the formation of hotspots that can lead to battery failure.

Electrochemical Strain Microscopy (ESM) is a powerful technique that can analyze ion concentration and conductivity by detecting the strain generated in the material due to ionic movement. When applied to solid electrolyte materials, ESM provides valuable insights into the uniformity of ion distribution and ion conduction pathways. This capability is particularly beneficial in developing and optimizing solid electrolytes, where understanding and controlling ion distribution is critical to improving battery performance and reliability.

This study verified the uniformity of ion concentration in LiPON, a representative solid electrolyte material, based on ESM images. Simultaneously, by comparing Trace and Retrace images at different scan speeds, the impact of scan speed on ESM imaging was assessed, and the causes of artifacts occurring during the ESM imaging process were identified. Furthermore, methodologies to reduce these artifacts were proposed.
Exploring High-Entropy Thin Films for Advanced Energy Storage Applications
Authors: Serikkazyyeva Assel , Mashekova Aiym , Yegamkulov Mukagali , Nurpeissova Arailym , Mukanova Aliya , Bakenov Zhumabay
Published: December 2024

High-entropy thin films (HETF) represent a novel and promising avenue in the field of materials science, offering unique properties and functionalities that hold great potential for energy storage applications. This work delves into the synthesis, characterization, and application of HETF in energy storage systems.

Through the integration of multiple elements in equimolar or near-equimolar ratios, HETF exhibit exceptional mechanical strength, thermal stability, and corrosion resistance. Moreover, their tunable compositions and structures allow for tailored electrochemical properties, enhancing the performance and efficiency of energy storage devices.

This presentation will discuss recent advancements in the fabrication techniques of high-entropy thin films, elucidate their fundamental electrochemical mechanisms, and highlight their applications in various energy storage platforms, including batteries, supercapacitors, and beyond. By elucidating the potential of high-entropy thin films, this research aims to contribute to the development of next-generation energy storage technologies, paving the way towards sustainable and efficient energy solutions.
Development of Highly Adhesive and Conductive Polymers As Primer Coating Layer for Stable Large-Area Lithium Metal Powder Electrode
Authors: Minseok Jeong , Jeonghun Kim , Kang Dongyoon , Lee Yong Min
Published: December 2024

Faced with the challenges of conventional extrusion and pressing methods, which are limited in producing thinner and wider electrodes due to the malleability of lithium (Li) metal, this research pioneered a slurry-based coating process for lithium metal powder (LMP) electrodes. This innovative approach offers a solution to existing manufacturing constraints by enabling the production of wider and ultra-thin lithium anodes through simple adjustments to the coater settings. Despite the advantages of this method, challenges such as the separation of the LMP composite layer from the collector due to electrolyte impregnation and volume changes during charge/discharge cycles remain significant. To address these issues, an adhesively conductive polymeric interlayer (ACL) was synthesized from 3,4-ethylenedioxythiophene (EDOT) and acrylic acid functional group. The prepared polymer layer could significantly improve the interfacial stability of the electrode. With the application of the ACL, the lithium stripping overpotential was reduced by 60% from 0.0898 V to 0.0358 V. Additionally, improved cycling stability of 200 cycles was achieved with 91% capacity retention at a discharge rate of 4 mA cm-2 in a carbonate-based electrolyte. The successful fabrication of a 300 mm wide and 20 μm thick slurry-coated LMP electrode is a significant advancement for lithium metal batteries (LMBs) and signifies progress in enhancing the energy density of battery technology.
(Invited) The Role of Counterion Chemistry on the Nature of Charge Carriers in Redox-Doped Nanocarbons
Authors: Ferguson Andrew J , Blackburn Jeff
Published: December 2024

The performance of many emerging electronic and optoelectronic devices based on organic and nanoscale carbon semiconductors can be fine-tuned by control of the charge carrier density injected by redox dopants. We have recently demonstrated that the chemical structure (size, shape, and redox properties) of the dopant counterion has a significant influence on the electrostatic interactions with the charge carrier, which affects charge (de)localization and transport. We have exploited this to enhance the thermoelectric properties of thin film networks of single-walled carbon nanotubes (SWCNTs) and have observed strong modulation of the complex dielectric properties of isolated SWCNTs dispersed in a low dielectric solvent. Here we extend these studies to the redox doping of graphene nanoribbons (GNRs). We once again show that the chemical structure of the dopant counterion has a critical influence on the properties of the injected charge carriers. Large, spherical dopant counterions based on bulky benzyloxy-substituted icosahedral dodecaborane cluster dopants, DDBs, lead to enhanced delocalization of charge carriers and transport, as observed by UV-Vis-NIR / Fourier Transform Infrared (FTIR) spectroscopy and microwave conductivity, respectively. In contrast, the increased electrostatic interactions with the planar dopant counterion 2,3,5,6-Tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4-TCNQ) results in stronger carrier localization, inhibiting transport. We will provide a comparison of the doping of GNRs, with SWCNTs and conjugated polymers.
Electrochemical Studies of Ion Transport through Single‐Walled Carbon Nanotubes Using Polyoxometalate/Nanotube Composite Electrodes
Authors: Walsh Darren Anthony
Published: December 2024

In this presentation, I describe the development of a hybrid material based on polyoxometalate (POM) clusters encapsulated within single-walled carbon nanotubes (SWNTs). Encapsulation of the POMs within the SWNTs is driven by electron transfer from the SWNTs to the POMs clusters, resulting in the spontaneous formation of host–guest POM@SWNT redox‐active materials. The SWNTs can conduct charge to and from the encapsulated guest molecules, allowing electrical access to >90% of the redox species. I then describe the use of this material as a model system for exploring ion transport across atomically thin structures. The nanotube sidewall creates a barrier between the redox-active molecules and bulk electrolytes, which can be probed by addressing the redox states of the POMs voltammetrically. While acidic electrolytes facilitate rapid, reversible electron transfer during repeated redox cycling, the use of electrolytes containing cations larger than protons and deuterons hinders redox switching of the encapsulated species. By “plugging” the {POM}@SWNT material with sized-matched C60-fullerenes, we demonstrate that the primary mode of charge balancing during redox cycling is proton/deuteron transport through the lattice of the SWNT sidewalls, proving that these small ions can traverse the sp2 carbon lattice.
Separation and Isolation of Rare-Earth Clusters Trapped inside Uncommon Carbon Cages
Authors: Schmitt Riley , Stevenson Steven
Published: December 2024

During our chemical-based separation of fullertubes and fullerenes, we have found that aminopropanol is selective for separating spheroidal molecular carbon (fullerenes) versus tubular molecular carbon (fullertubes). In this poster presentation, we will discuss the experiments using aminopropanol as the selective agent to separate metallofullerenes from fullerenes. Preliminary results indicate a rich variety of rare-earth clusters entrapped within uncommon carbon cages. We also report our recent advances in their chromatographic separation. In our multi-step isolation approach, Stage 1 consists of a chemical purification that simplifies the complex mixture of fullerenes/metallofullerenes present in soot extract. In Stage 2, we introduce a two-column approach with two different stationary phases to further resolve co-eluting rare-earth endohedrals. We conclude the presentation with initial characterization as we seek to isolate sufficient quantities for X-ray crystallography and structural elucidation.