bluuebunny/crossref_metadata_2025 huggingface dataset:
Allotaxonometry and rank-turbulence divergence: a universal instrument for comparing complex systems
Authors: Dodds Peter Sheridan , Minot Joshua R. , Arnold Michael V. , Alshaabi Thayer , Adams Jane Lydia , Dewhurst David Rushing , Gray Tyler J. , Frank Morgan R. , Reagan Andrew J. , Danforth Christopher M.
Published: September 2023

Complex systems often comprise many kinds of components which vary over many orders of magnitude in size: Populations of cities in countries, individual and corporate wealth in economies, species abundance in ecologies, word frequency in natural language, and node degree in complex networks. Here, we introduce ‘allotaxonometry’ along with ‘rank-turbulence divergence’ (RTD), a tunable instrument for comparing any two ranked lists of components. We analytically develop our rank-based divergence in a series of steps, and then establish a rank-based allotaxonograph which pairs a map-like histogram for rank-rank pairs with an ordered list of components according to divergence contribution. We explore the performance of rank-turbulence divergence, which we view as an instrument of ‘type calculus’, for a series of distinct settings including: Language use on Twitter and in books, species abundance, baby name popularity, market capitalization, performance in sports, mortality causes, and job titles. We provide a series of supplementary flipbooks which demonstrate the tunability and storytelling power of rank-based allotaxonometry.
Mapping between eras in scale-covariant gravity with a van der Waals cosmological source
Authors: Ribas M. O. , Bail L. C. , Devecchi F. P.
Published: September 2023

In this paper, we apply the scale-covariant formalism established by Canuto et al. in order to connect different eras of fluid-driven universes. This technique depends on a scale function that can be adjusted by imposing different physical restrictions. In a previous work, Chaplygin fluid was considered as cosmological source; now a van der Waals constituent shows to be a consistent source to establish a mapping between an old decelerated-to-accelerated universe, ruled by Einstein equations, and an early universe, controlled by a modified gravitational theory. A similar situation emerges when a generalized Chaplygin fluid is considered. These cosmological properties are shown to be a direct consequence of an appropriate use of the scale-covariant technique, and can be seen as extensions of the original barotropic and plain Chaplygin cases.
Estimates of charm-mixing parameters in two-body charm decays
Authors: Amirkhanlou Elnaz , Mohammadi Behnam
Published: September 2023

The charm-mixing parameter [Formula: see text] is based on the [Formula: see text] meson system. The measurement of the ratios of the effective decay width [Formula: see text] decays to final states [Formula: see text] was recently reported in an LHCb analysis performed with the values of [Formula: see text] and [Formula: see text]. We have calculated the difference between the charm-mixing parameters, [Formula: see text], under the factorization approach with values of [Formula: see text] and [Formula: see text], respectively. The results obtained are comparable with experimental values.
Bayesian Analysis of k-out-of-n System Using Weighted Exponential-Lindley Distribution
Authors: Sharma Sunita , Kumar Vinod
Published: September 2023

This paper proposes the Bayesian paradigm to analyze the reliability characteristics of a [Formula: see text]-out-of-[Formula: see text] system consisting of [Formula: see text] independent and identically distributed components, using Weighted Exponential-Lindley distribution as failure times. The Bayesian approach is utilized to estimate reliability characteristics like system reliability and mean time to system failure. Lindley’s approximation is employed along with Jeffery prior under a squared error loss function to obtain the estimators for these reliability measures. A simulation study is carried out for comparing the performances of these estimators. Finally, a real data set is used to illustrate the findings.
Stochastic averaging principle for McKean–Vlasov SDEs driven by Lévy noise
Authors: Zhang Tingting , Shen Guangjun , Yin Xiuwei
Published: September 2023

In this paper, we study McKean–Vlasov stochastic differential equations driven by Lévy processes. Firstly, under the non-Lipschitz condition which include classical Lipschitz conditions as special cases, we establish the existence and uniqueness for solutions of McKean–Vlasov stochastic differential equations using Carathéodory approximation. Then under certain averaging conditions, we establish a stochastic averaging principle for McKean–Vlasov stochastic differential equations driven by Lévy processes. We find that the solutions to stochastic systems concerned with Lévy noise can be approximated by solutions to averaged McKean–Vlasov stochastic differential equations driven by Lévy processes in the sense of convergence in [Formula: see text]th moment.
Responses of a System Comprising a Rigid Block with Resettable Sliding Key Under Base Excitation
Authors: Liang Feng , Au Francis T. K. , Liu Ying-Qi
Published: September 2023

The relatively uncontrolled dynamic behavior of a rigid block resting on a flat surface under ground motion has been well studied. In contrast, a block with a gently inclined V- or W-shaped sliding key would ensure dynamic self-centering or resetting performance under various seismic conditions. To better understand the nonlinear responses of rigid blocks having this type of interface where both rocking and sliding movements are possible, an event-based algorithm is put forward to cover various types of motions, including the transition stages between different types of motions. A comprehensive study is carried out to examine the dynamic responses of blocks of different sizes and aspect ratios. Moreover, the simplified pure rocking model and pure sliding model are also adopted to obtain rough estimates of dynamic response for comparison. The results show that the simplified models are reliable for some special cases only, e.g. squat blocks and slender blocks. The study also evaluated the influence of the coefficient of friction and slope inclination on the resetting capabilities of typical sliding-prone and rocking-prone systems. For those cases that are prone to toppling or excessive sliding under strong earthquakes, the provision of vertical post-tensioning can effectively ensure stability and resetting performance. Such findings provide insight into the performance of precast segmental bridge columns with resettable sliding joints.
Number theoretical locally recoverable codes
Authors: Ferraguti Andrea , Goldfeld Dorian , Micheli Giacomo
Published: September 2023

In this paper, we give constructions for infinite sequences of finite nonlinear locally recoverable codes [Formula: see text] over a product of finite fields arising from basis expansions in algebraic number fields. The codes in our sequences have increasing length and size, constant rate, fixed locality, and minimum distance going to infinity.
Krull modules over integral domains
Authors: Nurwigantara Mu’amar Musa , Wijayanti Indah Emilia , Marubayashi Hidetoshi , Wahyuni Sri
Published: September 2023

We define a concept of strongly Krull (s-Krull) modules over integral domains. One of the main aims is to study arithmetic properties of s-Krull modules. There are two different definitions of Krull modules over integral domains, that is: Krull modules in the sense of Costa and Johnson and Krull modules in the sense of ours. It turns out that Krull modules in the sense of Costa and Johnson imply s-Krull modules and s-Krull modules imply Krull modules in the sense of ours. The reverse of the statements do not necessarily hold.
On the generalized Hamming weights of hyperbolic codes
Authors: Camps-Moreno Eduardo , García-Marco Ignacio , López Hiram H. , Márquez-Corbella Irene , Martínez-Moro Edgar , Sarmiento Eliseo
Published: September 2023

[Formula: see text]A hyperbolic code is an evaluation code that improves a Reed–Muller code because the dimension increases while the minimum distance is not penalized. We give necessary and sufficient conditions, based on the basic parameters of the Reed–Muller code, to determine whether a Reed–Muller code coincides with a hyperbolic code. Given a hyperbolic code [Formula: see text], we find the largest Reed–Muller code contained in [Formula: see text] and the smallest Reed–Muller code containing [Formula: see text]. We then prove that similar to Reed–Muller and affine Cartesian codes, the [Formula: see text]th generalized Hamming weight and the [Formula: see text]th footprint of the hyperbolic code coincide. Unlike for Reed–Muller and affine Cartesian codes, determining the [Formula: see text]th footprint of a hyperbolic code is still an open problem. We give upper and lower bounds for the [Formula: see text]th footprint of a hyperbolic code that, sometimes, are sharp.
On binary linear codes and binary pseudo-random sequences
Authors: Cardell Sara D. , Climent Joan-Josep , Requena Verónica
Published: September 2023

In this paper, we study the relation between the linear subspace of the pseudo-noise (PN)-sequences generated by a primitive polynomial and the simplex code. This family of sequences can be also seen as an Maximum Distance Separable (MDS) [Formula: see text]-linear code over [Formula: see text]. Furthermore, we see how to compute the family of generalized sequences produced by a primitive polynomial by means of a first-order Reed–Muller code.
MULTI-SCALE SKELETAL MUSCLE MODELING: A REVIEW
Authors: WANG MONAN , JING JUNTONG , YANG QIYOU , LI PENGCHENG
Published: September 2023

The musculoskeletal system, containing bones, cartilage, skeletal muscles, tendons, ligaments, and some other tissues, is a perfect system that undergoes the external and internal load properly and controls the body’s motion efficiently. In this system, skeletal muscle is obviously indispensable. People have been studying the mystery of skeletal muscle mechanics for the last 80 years. Many modeling methods have been used to study skeletal muscles. Among these methods, multi-scale modeling methods are increasingly frequently used in studying musculoskeletal systems, especially those of skeletal muscles. In this review, we summarize the multi-scale modeling methods in studying works of skeletal muscle modeling reported so far. Then, several multi-scale methods of other tissues which possibly could be used in research on skeletal muscle modeling are discussed. Finally, the future research direction and the main challenges of multi-scale skeletal muscle modeling are briefly presented.
A DEEP LEARNING FRAMEWORK-BASED EXERCISE ASSESSMENT FOR REHABILITATION OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE
Authors: CAO LEI , XIE ZHIHENG , LIU TIANYU , WANG ZIJIAN , FAN CHUNJIANG
Published: September 2023

Chronic obstructive pulmonary disease (COPD), which has a high prevalence and mortality rate, is an irreversible condition marked by airflow restriction with different degrees of reversible damage. Notably, there is no cure for COPD, whose treatment primarily relies on rehabilitation exercises to improve airflow limitation. In this paper, a vision-based rehabilitation exercise efficacy prediction system is proposed to assess the efficacy of rehabilitation training for COPD patients. A camera was utilized to capture rehabilitation training videos of COPD patients, and we also collected various physical indicators. In addition, we used clustering algorithm to divide patients with different rehabilitation effects for subsequent progression analysis. Our model achieved a classification of rehabilitation progress accuracy of 90.6%, making it possible to effectively obtain favorable rehabilitation training results without physician supervision. It was meaningful for helping COPD patients get effective feedback when training alone.
AN EMOTION RECOGNITION MODEL BASED ON LONG SHORT-TERM MEMORY NETWORKS AND EEG SIGNALS AND ITS APPLICATION IN PARAMETRIC DESIGN
Authors: ZHOU MINNING , ZHOU LIN , PAN MENGJIAO , CHEN XIANG
Published: September 2023

One of the design objectives of a product is to create a positive emotional user experience. Through careful design, the product can evoke emotional resonance in users and stimulate their pleasure and satisfaction. Therefore, emotion recognition is crucial for parameterized product design. Considering that emotion recognition based on electroencephalogram (EEG) signals is more objective and accurate compared to methods such as text and surveys, this paper proposes an emotion analysis model based on long short-term memory (LSTM) and EEG and applies it to parameterized design. The main contributions of this paper are as follows. (1) Constructing a high-accuracy emotion recognition model. First, EEG data reflecting the characteristic patterns of brain activities in different emotional states are collected through EEG electrodes. Then, the EEG data are input into the LSTM network for training, enabling it to learn and capture the features associated with emotional states. During the training process, the model learns to extract crucial emotional features from the EEG data for emotion state recognition. This model can automatically learn emotional features, handle long-term dependencies and provide a more accurate and reliable solution for emotion recognition tasks. (2) Creating an EEG dataset specifically for evaluating emotions related to a product and using the trained emotion recognition model to classify this dataset, obtaining emotion classification results. The emotion classification results can be used to determine which parameter designs in product development need to be retained or discarded. These parameter designs can involve aspects such as user experience, functionality, aesthetics, usability and user-friendliness. Decisions can be made based on the emotion classification results to improve the quality and user satisfaction of the product.
Applications of deferred Lebesgue product measurable convergence to approximation theorems
Authors: Narrania Devia , Raj Kuldip
Published: September 2023

In this paper, we introduce the notions of product measurable convergence, deferred Cesàro statistical product measurable convergence and deferred Cesàro statistical Lebesgue product measurable convergence for sequences of measurable functions on product measure spaces. We establish some fundamental relations among these convergences and also give several explanatory examples in support of our definitions and results. Finally, as an application, we prove a new version of Korovkin-type approximation theorems for sequences of measurable functions on product measure spaces by using the notion of deferred Cesàro statistical Lebesgue product measurable convergence.
Existence of mild solutions for a multi-term fractional differential equation via ψ-(γ,σ)-resolvent operators
Authors: El Asraoui Hiba , El Mfadel Ali , El Omari M’hamed , Hilal Khalid
Published: September 2023

In this paper, we consider a multi-term fractional differential equation involving the [Formula: see text]-Caputo fractional derivative. Under some suitable hypotheses, we prove that our proposed problem has at least one mild solution expressed in terms of the [Formula: see text]-[Formula: see text]-resolvent. As an application, we provide a suitable example at the end of this work to illustrate our theoretical results.
Cache Optimization and Performance Modeling of Batched, Small, and Rectangular Matrix Multiplication on Intel, AMD, and Fujitsu Processors
Authors: Deshmukh Sameer , Yokota Rio , Bosilca George
Published: September 2023

Factorization and multiplication of dense matrices and tensors are critical, yet extremely expensive pieces of the scientific toolbox. Careful use of low rank approximation can drastically reduce the computation and memory requirements of these operations. In addition to a lower arithmetic complexity, such methods can, by their structure, be designed to efficiently exploit modern hardware architectures. The majority of existing work relies on batched BLAS libraries to handle the computation of many small dense matrices. We show that through careful analysis of the cache utilization, register accumulation using SIMD registers and a redesign of the implementation, one can achieve significantly higher throughput for these types of batched low-rank matrices across a large range of block and batch sizes. We test our algorithm on three CPUs using diverse ISAs – the Fujitsu A64FX using ARM SVE, the Intel Xeon 6148 using AVX-512, and AMD EPYC 7502 using AVX-2, and show that our new batching methodology is able to obtain more than twice the throughput of vendor optimized libraries for all CPU architectures and problem sizes.
Multiresolution Local Spectral Attributed Community Search
Authors: Li Qingqing , Ma Huifang , Li Zhixin , Chang Liang
Published: September 2023

Community search has become especially important in graph analysis task, which aims to identify latent members of a particular community from a few given nodes. Most of the existing efforts in community search focus on exploring the community structure with a single scale in which the given nodes are located. Despite promising results, the following two insights are often neglected. First,
node attributes
provide rich and highly related auxiliary information apart from network interactions for characterizing the node properties. Attributes may indicate the community assignment of a node with very few links, which would be difficult to determine from the network structure alone. Second, the
multiresolution community
affords latent information to depict the hierarchical relation of the network and ensure that one of them is closest to the real one. It is essential for users to understand the underlying structure of the network and explore the community with strong structure and attribute cohesiveness at disparate scales. These aspects motivate us to develop a new community search framework called
Multiresolution Local Spectral Attributed Community Search
(MLSACS). Specifically, inspired by the local modularity, graph wavelets, and scaling functions, we propose a new Multiresolution Local modularity (MLQ) based on a reconstructed node attribute graph. Furthermore, to detect local communities with cohesive structures and attributes at different scales, a sparse indicator vector is developed based on MLQ by solving a linear programming problem. Extensive experimental results on both synthetic and real-world attributed graphs have demonstrated the detected communities are meaningful and the scale can be changed reasonably.
A Review of Modern Fashion Recommender Systems
Authors: Deldjoo Yashar , Nazary Fatemeh , Ramisa Arnau , McAuley Julian , Pellegrini Giovanni , Bellogin Alejandro , Noia Tommaso Di
Published: September 2023

The textile and apparel industries have grown tremendouslyover the past few years.Customers no longer have to visit many stores, stand in long queues, or try on garments in dressing rooms, as millions of products are now available in online catalogs. However, given the plethora of options available, an effective recommendation system is necessary to properly sort, order, and communicate relevant product material or information to users. Effective fashion recommender systems (RSs) can have a noticeable impact on billions of customers’ shopping experiences and increase sales and revenues on the provider side.

The goal of this survey is to provide a review of RSs that operate in the specific vertical domain of garment and fashion products. We have identified the most pressing challenges in fashion RS research and created a taxonomy that categorizes the literature according to the objective they are trying to accomplish (e.g., item or outfit recommendation, size recommendation, and explainability, among others) and type of side information (users, items, context). We have also identified the most important evaluation goals and perspectives (outfit generation, outfit recommendation, pairing recommendation, and fill-in-the-blank outfit compatibility prediction) and the most commonly used datasets and evaluation metrics.
KAPE:
k
NN-based Performance Testing for Deep Code Search
Authors: Guo Yuejun , Hu Qiang , Xie Xiaofei , Cordy Maxime , Papadakis Mike , Le Traon Yves
Published: September 2023

Code search is a common yet important activity of software developers. An efficient code search model can largely facilitate the development process and improve the programming quality. Given the superb performance of learning the contextual representations, deep learning models, especially pre-trained language models, have been widely explored for the code search task. However, studies mainly focus on proposing new architectures for ever-better performance on designed test sets but ignore the performance on unseen test data where only natural language queries are available. The same problem in other domains, e.g., CV and NLP, is usually solved by test input selection that uses a subset of the unseen set to reduce the labeling effort. However, approaches from other domains are not directly applicable and still require labeling effort. In this article, we propose the
k
NN-b
a
sed
p
erformance t
e
sting (
KAPE
) to efficiently solve the problem without manually matching code snippets to test queries. The main idea is to use semantically similar training data to perform the evaluation. Extensive experiments on six programming language datasets, three state-of-the-art pre-trained models, and seven baseline methods demonstrate that KAPE can effectively assess the model performance (e.g., CodeBERT achieves MRR 0.5795 on JavaScript) with a slight difference (e.g., 0.0261).
Programmed Cell Death in Unicellular Versus Multicellular Organisms
Authors: Kulkarni Madhura , Hardwick J. Marie
Published: September 2023

Programmed cell death (self-induced) is intrinsic to all cellular life forms, including unicellular organisms. However, cell death research has focused on animal models to understand cancer, degenerative disorders, and developmental processes. Recently delineated suicidal death mechanisms in bacteria and fungi have revealed ancient origins of animal cell death that are intertwined with immune mechanisms, allaying earlier doubts that self-inflicted cell death pathways exist in microorganisms. Approximately 20 mammalian death pathways have been partially characterized over the last 35 years. By contrast, more than 100 death mechanisms have been identified in bacteria and a few fungi in recent years. However, cell death is nearly unstudied in most human pathogenic microbes that cause major public health burdens. Here, we consider how the current understanding of programmed cell death arose through animal studies and how recently uncovered microbial cell death mechanisms in fungi and bacteria resemble and differ from mechanisms of mammalian cell death.
Dynamic Multiplex Tissue Imaging in Inflammation Research
Authors: Uderhardt Stefan , Neag Georgiana , Germain Ronald N.
Published: September 2023

Inflammation is a highly dynamic process with immune cells that continuously interact with each other and parenchymal components as they migrate through tissue. The dynamic cellular responses and interaction patterns are a function of the complex tissue environment that cannot be fully reconstructed ex vivo, making it necessary to assess cell dynamics and changing spatial patterning in vivo. These dynamics often play out deep within tissues, requiring the optical focus to be placed far below the surface of an opaque organ. With the emergence of commercially available two-photon excitation lasers that can be combined with existing imaging systems, new avenues for imaging deep tissues over long periods of time have become available. We discuss a selected subset of studies illustrating how two-photon microscopy (2PM) has helped to relate the dynamics of immune cells to their in situ function and to understand the molecular patterns that govern their behavior in vivo. We also review some key practical aspects of 2PM methods and point out issues that can confound the results, so that readers can better evaluate the reliability of conclusions drawn using this technology.
A Systematic Review of Implementation Research on Determinants and Strategies of Effective HIV Interventions for Men Who Have Sex with Men in the United States
Authors: Mustanski Brian , Queiroz Artur , Merle James L. , zamantakis alithia , Zapata Juan Pablo , Li Dennis H. , Benbow Nanette , Pyra Maria , Smith Justin D.
Published: September 2023

Men who have sex with men (MSM) are disproportionately affected by HIV, accounting for two-thirds of HIV cases in the United States despite representing ∼5% of the adult population. Delivery and use of existing and highly effective HIV prevention and treatment strategies remain suboptimal among MSM. To summarize the state of the science, we systematically review implementation determinants and strategies of HIV-related health interventions using implementation science frameworks. Research on implementation barriers has focused predominantly on characteristics of individual recipients (e.g., ethnicity, age, drug use) and less so on deliverers (e.g., nurses, physicians), with little focus on system-level factors. Similarly, most strategies target recipients to influence their uptake and adherence, rather than improving and supporting implementation systems. HIV implementation research is burgeoning; future research is needed to broaden the examination of barriers at the provider and system levels, as well as expand knowledge on how to match strategies to barriers—particularly to address stigma. Collaboration and coordination among federal, state, and local public health agencies; community-based organizations; health care providers; and scientists are important for successful implementation of HIV-related health innovations.
Time-Dependent Corrosion Behavior of Aluminum Using Advanced Electrochemical and Characterization Techniques
Authors: Witharamage C. S. , Darwish A. A. , Christudasjustus J. , Soltis J. , Gupta R. K.
Published: September 2023

The time-dependent corrosion behavior of pure aluminum (Al) in a chloride-containing environment was investigated using various electrochemical and characterization techniques for up to 336 h. Transmission electron microscopic and secondary ion mass spectroscopic analysis revealed the continuous dissolution of the surface film over the immersion time. In the meantime, the increasing passive oxide thickness resulted in the surface film resistance enhancement over the immersion time, as indicated by the electrochemical impedance spectroscopic analysis. The electrochemical noise measurements showed an increase in the corrosion kinetics with immersion time until 60 h because of the accelerated localized corrosion in the early stage of immersion. However, an inhibition in corrosion kinetics occurred after longer immersion times due to corrosion product deposition inside the pit.
Quasi-Rechargeability in Li-CFx Batteries
Authors: Eschler Christopher M. , Krishnamurthy Venkatesh , Pu Jiankun , Zhang Shu Yang , Viswanathan Venkat , Chiang Yet-Ming
Published: September 2023

Lithium–fluorinated graphite (Li-CFx) has long been prized as a primary battery chemistry for its outstanding specific capacity (860 mAh/kg for CF1.0) and low self-discharge rate (<0.5%/year). Enabling rechargeability of this chemistry would make it an appealing candidate for short-haul electric aviation. However, progress toward this goal has been impeded by the high driving force required to revert the final discharge products: LiF and graphite. In this work, we instead aim to recharge from the temporary intermediate LiyCFx phase and dub this quasi-recharging. Chemical lithiation followed by potentiometry and XRD is used to assess the presence of the intermediate as a function of time. Shallow galvanostatic cycling (<10% depth of discharge) is proposed as a way to enable some capacity to be recharged by minimizing the time available for the intermediate to decompose, compared to full depth of discharge cycling. A 4-electrode setup using separate counter electrodes for discharge and charge has been constructed to indirectly observe the delithiation of CFx during charge, thereby separating the desired Faradaic capacity from capacitive and parasitic capacities. Results obtained from these methods with varying discharge rate, temperature, and rest time between discharge and charge will be discussed.
(Invited) Manipulating Photoexcitations of Flexible-Chain Polymer Semiconductors Via the Local Environment
Authors: Stingelin Natalie
Published: September 2023

Semiconducting:ferroelectric blends are interesting as an optoelectronic system because the strong coulombic interactions in excitons may be reduced by an enhanced polar environment provided by the ferroelectric component. Here, we demonstrate variations in the photoluminescence and charge dynamics of photo-induced absorption with model blends of the archetypal semiconducting polymer poly(3-hexylthiophene) (P3HT) and ferroelectric commodity polymer poly(vinylidene difluoride) (PVDF). This result suggests correlations between local polarity and photophysical processes of exciton dissociation and recombination, likely due to some degree of intermixing in specific blend ratios. Indeed, we see evidence of vitrification, i.e. glass formation, often leading to intermixing in these blends by varying the composition and molecular weight of the blend components. Furthermore, we will exploit the ferroelectric nano-domains, exhibited by the ter-polymer of PVDF, poly[(vinylidene fluoride‐co-trifluoro ethylene‐co-chlorotrifluoro ethylene)] [P(VDF-TrFE-CTFE)] to deliver fundamental insights into the required length scale of intermixing for photophysical processes.
Rapid, Large Area Fabrication of Porous Graphene Networks Using Photothermal Flash Lamp Carbonization for High Performance Supercapacitors
Authors: Bhardwaj Ayush , Okoroanyanwu Uzodinma , Watkins James J.
Published: September 2023

Graphene materials exhibit intriguing physical, chemical, and mechanical properties. Remarkably high surface area and electrical conductivity make them excellent materials for energy storage applications, especially supercapacitors. The production of graphene requires relatively long processing times, extremely high temperatures within controlled atmospheres, and/or involves multi-step reactions that present challenges for high-throughput fabrication of energy storage devices. Moreover, supercapacitor devices fabricated using graphene suffer from low areal capacitance mainly due to the tortuous path of electrolytes in accessing the bulk of the material, which limits charge storage and transport throughout the thickness of the device.

We have developed an efficient photothermal route to large-scale production of few-layer graphene within milliseconds from polymers using high intensity xenon flash lamp on carbon fiber at ambient conditions. The xenon flash lamp provides large-area illumination and a wide emission band (300 nm –1100 nm) that was used to convert the polymeric material directly into few-layer graphene upon millisecond exposures. Specifically, photothermally heating of polyaniline, a rod like polymer with a large absorption cross-section in the emission spectra of xenon flash lamp, led to the formation of macroporous network as shown in Figure 1a. Characterization revealed the formation of few layer graphene ( ID/IG ratio less than 0.3) with good adhesion to the carbon fiber support, enabling the formation of devices in-situ. We investigated the influence of morphology as well as graphene quality on the energy storage capabilities of the obtained devices as shown in Figure 1b. The supercapacitor devices prepared with macroporous few-layer graphene network exhibited a superior areal capacitance of 200 mF/cm2 at 10 mV/s which is an order of magnitude higher than few layer graphene with a conventional film like structure. Also, it retained more than 70% of its capacitance even after increasing the scan rate to 100 mV/s. Moreover, large area processability enabled by this photothermal approach allowed us to easily produce graphene-derived high-performance supercapacitor devices over areas greater than 100 cm2 (Figure 1c) within a few milliseconds at ambient conditions. Hence, this work provides an energy efficient and scalable route to produce high-quality few layer graphene devices with superior energy storage capabilities.

Figure 1
Bodipy and Dipyrrin as Unexpected Robust Anchoring Groups on TiO2 Nanoparticles
Authors: Jayworth Josephine A. , Capobianco Matt D. , Liu Han-Yu , Decavoli Cristina , Crabtree Robert H. , Brudvig Gary W.
Published: September 2023

Devising cost effective methods for efficiently capturing and storing solar energy is among the grand challenges of science (1). We are using insights from studies of natural photosynthetic systems (2) to develop bioinspired materials for photo-electrochemical water oxidation and solar fuel production by using molecular catalysts and dyes attached to mesoporous metal oxide photoanodes. Covalent attachment of molecules to metal oxide surfaces typically demands the presence of an anchoring group that in turn requires synthetic steps to introduce (3). BODIPY (4,4-difluoro-4-bora-3a,4a-diaza-s-indacene) chromophores have long been used in dye-sensitized solar cells, but carboxylic acid groups typically had to be installed to act as surface anchors. We now find that even without the introduction of such anchors, the unmodified BODIPY can bind to TiO2 surfaces via its BF2 group through boron–oxygen surface bonds. Dipyrrin, the parent molecule of BODIPY, is also capable of binding directly to TiO2 surfaces, likely through its chelating nitrogen atoms. These binding modes prove to be even more robust than that of an installed carboxylate and offer a new way to attach molecular complexes to surfaces for (photo)electrocatalytic applications since, once bound, we show that surface bound BODIPY and dipyrrin derivatives exhibit ultrafast photoinjection of electrons into the conduction band of TiO2 (4).

Directing Matter and Energy: Five Challenges for Science and the Imagination, U.S. Department of Energy, Washington, DC, December 2007.

D.J. Vinyard and G.W. Brudvig, Annu. Rev. Phys. Chem. (2017) 68, 101.

K.L. Materna, R.H. Crabtree and G.W. Brudvig, Chem. Soc. Rev. (2017) 46, 6099.

J.A. Jayworth et al., Dalton Trans. (2022) 51, 14260.
Photocatalytic Use of Porphyrin Based Functional Materials
Authors: Lee Tai Yong , Lee Suk Joong
Published: September 2023

Porphyrin-containing materials have been often used in photocatalysis for chemical transformations such as hydrogen evolution, CO2 reduction, purification, sterilization, and photoelectrochemical conversion. Reactive oxygen species (ROS) including free radicals/electrons and singlet oxygen (1O2) generated by photosensitizers are known to undergo secondary reactions such as multiple organic transformations and degradation of a wide variety of contaminants. Specially, they are often used for decomposition of chemical warfare agents (CWAs) such as sulfur mustard gas, which is one of the most notorious and effective chemical weapons. Various photocatalysts have been developed with successful use of ROS in photooxidation reactions. For example, in photodegradation of 2-chloroethyl ethyl sulfide (2-CEES), a sulfur mustard simulant, and demonstrated a selective decomposition to 2-chloroethyl ethyl sulfoxide (2-CEESO). Note that overoxidation of 2-CEESO generates 2-chloroethyl ethyl sulfone (2-CEESO2, fully oxidized product) and becomes a highly toxic material. Therefore, selective oxidation of 2-CEES without generating 2-CEESO2 is considered an important process in the detoxification of sulfur mustard gas.

In this presentation, photocatalytic application of porphyrin based materials including PIM, silica, MOF and nanofiber will be demonstrated. Although porphyrins are well-known photosensitizers for effective photocatalytic reactions, they often suffer from self-degradation. Incorporation of porphyrins into nano materials may prevent self-degradation, resulting in effective systems with a long lifetime.
Additive Manufacturing of Colloidal Nanocrystals for Flexible Thermoelectric Generators
Authors: Valayil Varghese Tony , Valayil Varghese Tony , Estrada Isaac , Rajabi Kouchi Fereshteh , Estrada David
Published: September 2023

2D Chalcogenides, a narrow gap layered semiconductor and a topological insulator has been reported to have excellent room temperature thermoelectric performances. Alloying and nanostructuring of the material have been widely studied for reducing the lattice thermal conductivity (ΚL) of the materials to enhance the thermoelectric figure of merit (ZT). But the performance of printed thermoelectric devices is significantly low compared to bulk counterparts due to low density and porosity, here we report interface engineering and Nano inclusion in the crystals as an effective way to increase the performance of thermoelectric materials. This work demonstrates the scalable solvothermal synthesis of crystalline nanomaterials with engineered defects and interface engineering to improve the thermoelectric performance of the colloidal nano-inks. The engineered nanomaterials are transformed into devices using multiple additive manufacturing methods including Screen printing, Aerosol Jet Printing, Plasma Jet Printing, and Direct Writing. The low-cost scalable additive manufacturing methods and interface engineering developed in this work demonstrate a significant advance in the field of high-performing low-cost thermoelectric generators, advancing the commercial viability of the technology for energy harvesting, sensing, and cooling applications.
Correlating Corrosion to Surface Grain Orientations by Scanning Electrochemical Cell Microscopy
Authors: Mauzeroll Janine
Published: September 2023

The study of grain-dependent corrosion behaviors of practical polycrystalline metals remains challenging due to the difficulty in eliminating the influences of other microstructural features, such as intermetallic particles and grain boundaries. In this work, we performed thousands of microscopic potentiodynamic polarization measurements on a polycrystalline alloys using the spatially resolved oil-immersed scanning electrochemical cell microscopy measurement. This work highlights the capability of oil-immersed scanning electrochemical cell microscopy in resolving small electrochemical differences, which will greatly promote the study of grain-dependent behaviors of practical polycrystalline samples.
Characterization and Optimization of Plasma Electrolytic Process for Conversion of Molecular Nitrogen to Ammonia in Aqueous Water at Atmospheric Pressure
Authors: Kamiyama Brandon , Pierrard Robert , Sankaran R. Mohan
Published: September 2023

Ammonia (NH3) is widely used in the chemical and agricultural industries and is of growing interest as a potential energy carrier. Most of the current global NH3 production utilizes the Haber-Bosch process which has a large environmental and physical footprint. For this reason, there have been substantial efforts to develop an alternative process that can be sustainable and distributed. Recently, plasma-based electrolysis reactors have shown promise to convert molecular nitrogen to various forms of fixed nitrogen such as ammonia, nitrate, and nitrite in water at atmospheric pressure. However, selectivity and control over the products has not been adequately demonstrated. In this work, we studied a plasma formed in pure nitrogen gas or mixtures containing nitrogen gas at the surface of liquid water. Various products were characterized in the liquid phase including ammonium ions, nitrate ions, nitrite ions, and hydrogen peroxide as a function of pH, discharge current, and time. In addition, continuous direct current (DC) was compared to pulsed DC voltage plasma operation. We find that the selectivity to different nitrogen products depends on the solution conditions. These results could be used to inform optimization and scale up of similar plasma-liquid systems for sustainable nitrogen fixation.
Plasma-Made Nanogold for DNA Sensing with SERS
Authors: Shvalya Vasyl , Modic Martina , Zavašnik Janez , Vasudevan Aswathy , Skubic Cene , Abdulhalim Ibrahim , Rozman Damjana , Cvelbar Uros
Published: September 2023

Facilitated electrochemical properties of plasma are crucial for improving functional nanomaterials synthesis and design for novel sensor development. Controlled customization and functionality tailoring at multiscale is the targeted challenge for better detection devices performance. In the modern era of optoelectronics, among various probing approaches, plasmonic sensing accompanied by Raman, FTIR or Fluorescent spectroscopy is considered a tool for the efficient investigation of molecular properties. In particular, Raman scattering is often called SERS (surface-enhanced Raman scattering) due to plasmonic enhancers, which are used to improve the probing of analytes at a reduced scale. This feature is extremely useful for biologically relevant analytical tasks when samples alike DNA and similar need to be investigated fast and accurately. DNA/RNA-related investigations are highly important in modern nanomedicine due to the solid progress of bionanotechnology, DNA vaccines, and functional gene engineering. DNA is the most valued substance for microbiologists because it contains information about bio-species' nature.[1] Currently, the number of molecular-sensitive methods for DNA-level study is quite limited, among which PCR (polymer chain reaction) related methods dominate the field. However, it is challenging to investigate it with optical techniques like SERS. Despite being promising, SERS is still under technological and analytical improvement. Better performance comes with sophisticated plasmonic nanomaterials, which provide considerably improved photon scattering due to the strongly localized field confinement effect.[2] In the current report, a well-performing nanoplasmonic sensor was designed using a plasma-driven electrochemical reduction mechanism. Exploiting atmospheric pressure He-plasma jet setup operating kHz frequency, the reactive oxidative species donated electrons via liquid-gas electrochemistry towards the Ar-delivered Au(3+)-containing microdroplets. Through this method, microscaled aggregates composed of AuNPs were obtained from the nebulized ionic gold liquid precursor. Due to the strong coupling between nanoparticles, a high analytical enhancement factor of about 107 was achieved and the substrate allowed to obtain Raman fingerprints of bacterial DNA fragments (M. luteus and S. aureus, E. coli, J. lividum) at nanovolume sample quantities. In addition, main DNA molecular vibrational signatures associated with nucleobase motions were extracted from spectra collected and used to classify the bacterial strains reliably by employing statistical principal component analysis.

References

[1] Garcia-Rico, E., Alvarez-Puebla, R. A., & Guerrini, L. (2018). Chemical Society Reviews, 47(13), 4909-4923.

[2] Shvalya, V., Filipič, G., Zavašnik, J., Abdulhalim, I., & Cvelbar, U. (2020). Applied Physics Reviews, 7(3), 031307.
(Invited) Redox Chemistry Driven by Atmospheric Pressure Plasma Jet
Authors: Caruana Daren
Published: September 2023

Plasmas may be considered as mixed ionic and electronic conductors. From an electrochemical point of view, a conducting gas presents a wonderful opportunity to explore redox reactions without all the restrictions a solvent medium provides. Identifying a plasma medium suitable to allow electrochemical measurements can be technically challenging, often due to the electrical energy used to create the plasma. However, atmospheric pressure plasma jets (APPJ)1&2 have been shown to be accessible and convenient as laboratory plasma sources. They present a medium that may be considered as an electrode, due to the presence of electrons or as electrolytes, due to their electrical conduction.3 Although its definition is not too important, the presence of free electrons gives an opportunity to drive reduction processes.

The interesting aspect of non-thermal plasmas, and the root of their interesting chemistry, is partly due to the imbalance of thermal kinetic energy distribution between the electron and all the other species, neutral or ionized. As a consequence plasma jets are found in routine industrial applications such as etching or cleaning of surfaces for adhesion promotion. Furthermore, there is a growing body of evidence to suggest that APPJ may be used for the treatment of solid tumors. These highly energized electrons can drive redox reactions, as well as other chemical reactions, at solid or liquid can be unexpected. In this presentation I will explore the use of APPJ for reduction of metal oxides under potentiostatic control and material synthesis.4-6

References

Ratcliffe, L.V., et al., Surface analysis under ambient conditions using plasma-assisted desorption/ionization mass spectrometry. Analytical Chemistry, 2007. 79(16): p. 6094-6101.

Golda, J., et al., Concepts and characteristics of the 'COST Reference Microplasma Jet'. Journal of Physics D-Applied Physics, 2016. 49(8).

Rumbach, P.; Bartels, D. M.; Sankaran, R. M.; Go, D. B., The solvation of electrons by an atmospheric-pressure plasma. Nature Communications
2016, 6, 7248.

Sener, M. E., Quesada Cabrera, R., Parkin, I.P., Caruana, D. J., Facile formation of black titania films using an atmospheric-pressure plasma jet, Green Chemistry
2022
, 24, 2499-2505.

Sener, M. E., Palgrave, R., Quesada Cabrera, R., Caruana, D. J., Patterning of Metal Oxide thin Films using H2/He Atmospheric Pressure Plasma Jet. Green Chemistry
2020, 22, 1406-1413.

Sener, M. E.; Caruana, D. J., Modulation of copper(I) oxide reduction/oxidation in atmospheric pressure plasma jet. Electrochemistry Communications
2018,
95, 38-42.
Novel Thermal Batteries Based on Sodium Chemistries
Authors: Bateman Katherine , Gover Richard K. B. , Irvine John Thomas Sirr
Published: September 2023

Thermal batteries are high temperature primary batteries that function when an electrolyte, that is solid at room temperature, becomes molten at the operating temperature of the battery between 350 and 550 °C. This type of battery is valuable in high consequence scenarios when high power is required rapidly such as in ejector seats and space flight. Thermal batteries can withstand very harsh treatments and can be stored for many years without self-discharge. The most common thermal battery used today consists of an Li13Si4 anode, LiCl-KCl electrolyte and an FeS2 or CoS2 cathode. However, rising concerns regarding the sustainability of lithium has required that alternative chemistries such as using sodium be explored.

The use of sodium as an anode on its own is not suitable in thermal batteries due to its low melting point of 100 °C, so the use of sodium-based alloys such as NaSn (melting point 578 °C) and Na3Sb (melting point 859 °C) is investigated in this work. The identification of electrolytes with suitable melting points that are compatible with the operating temperature of the thermal battery and the melting point of the anode has also been undertaken since the electrolyte needs to melt at least 100 °C lower than the anode. Three such eutectic salts are NaCl-MgCl2 (melting point 451 °C), NaCl-MgCl2-KCl (melting point 383 °C) and NaCl-MgCl2-CaCl2 (melting point 424 °C).

Solid state and mechano-synthesis methods for preparation of the anode and electrolyte materials will be discussed as well as characterisation techniques such as PXRD, SEM, EDS, impedance measurements and DSC for the individual components of the battery. The impedance measurements are used to evaluate the conductivity of both the electrolyte and anode materials. The conductivity of the sodium-based electrolytes has been found to have the same order of magnitude as the LiCl-KCl electrolyte used in the standard thermal battery, typically between 0.5 and 2 Scm-1. Assembly and testing of a thermal battery cell will also be elucidated. Preliminary tests of a sodium based thermal battery with an FeS2 cathode have given voltages up to 2 V.