bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a Novel Formulation of Bioactive Glass Based Calcium Phosphate Cement for Bone Grafting
Authors: D'Onofrio Alessia , Hill Robert G. , Kent Niall W. , Rawlinson Simon C.F. , Shahdad Shakeel A. 
Published: April 2024

AbstractParticulate bone grafting material can travel from the implantation site and diminish the magnitude of required bone formation response and hence its effectiveness. An easily prepared moldable graft that rapidly sets rigid in situ would alleviate this problem and in this study, such an injectable bone graft material is presented. By combining calcium phosphate (CP) salts with a bioactive glass (BG) mixed with a 2.5% Na2HPO4 solution a novel BG‐based calcium phosphate cement (CPC) is produced. Immersion in Tris buffer and simulated body fluid (SBF) solutions result in the rapid generation of octacalcium phosphate (OCP) and hydroxyapatite (HA) phases – a pre‐requisite for “bioactivity”. Cement‐conditioned media does not result in any cytotoxic potential with respect to MTT activity, DNA content, or alkaline phosphatase activity with an osteoblastic cell line. Application of the cement into standardized surgical defects in the minipig mandible results in short‐term, moderate irritation at 3 and 6 weeks and complete replacement of cement with new bone at 12 weeks.
Synaptic Plasticity and Visual Memory in a Neuromorphic 2D Memitter Based on WS2 Monolayers
Authors: Ferrarese Lupi Federico , Milano Gianluca , Angelini Angelo , Rosero‐Realpe Mateo , Torre Bruno , Kozma Erika , Martella Christian , Grazianetti Carlo 
Published: April 2024

AbstractNeuromorphic computing aims to leverage physical phenomena of adaptive materials for emulating information processing capabilities and effectiveness of biological neuronal circuits. In this framework, memristors (resistors with memory) based on 2D materials are demonstrated for the hardware implementation of highly integrated artificial neural networks. All the works reported thus far exploited electrical properties of 2D materials to emulate neuromorphic functionalities. Here, a 2D memitter (emitter with memory) is reported on that exploits the stimuli‐responsive photoluminescence of a monolayer WS2 for neuromorphic‐type of data processing. A combined experimental and modeling approach reveals that photoluminescent dynamics triggered by optical stimulation emulates Short‐Term synaptic Plasticity and Visual Short‐Term Memory typical of biological systems. While spatio‐temporal processing capabilities of input signals can be used for information processing in the context of reservoir computing, the capability of the 2D memitter of sensing, processing, and memorizing‐forgetting optical inputs in the same physical substrate can be utilized for in‐sensor computing.
Large‐Scale Ultrastable 2D Inorganic Molecular Crystal BiBr3 and Heterostructures with Superior Photoluminescence Enhancement
Authors: He Xiaoyu , Wu Yu , Liu Shenghong , He Wenke , Li Shaohua , Huo Gaohang , Jiang Letian , Kapitonov Yury , Xing Guichuan , Zhao Yinghe , Li Yuan , Zhai Tianyou 
Published: April 2024

AbstractIn contrast to conventional atomic crystals, two‐dimensional inorganic molecular crystals (2DIMCs) possess a unique crystal structure composed of small molecules held together by van der Waals force. Such distinctive structure grants them specific chemical and physical properties highly suitable for electronic and optoelectronic applications. However, the synthesis of 2DIMCs has posed significant challenges due to the inherent issues such as uncontrollable growth orientation stemming from their natural crystalline isotropy and poor stability resulting from the weak intermolecular connections. Addressing these obstacles, the preparation of large‐scale and highly‐stable 2DIMC BiBr3, and its heterostructure are reported here by developing crystallization orientation engineering strategies. This approach has successfully yielded centimeter‐scale 2DIMC BiBr3 with a clean and dense surface, showcasing exceptional long‐term air‐stability exceeding 80 days. Furthermore, the universal growth of large‐scale 2DIMC BiBr3 is demonstrated on diverse substrates, including SiO2, Al2O3, and MoS2 monolayers. Notably, the resultant 2D BiBr3/MoS2 heterostructure exhibits remarkable photoluminescence enhancement. This contribution paves a universal avenue for the mature synthesis of large‐scale 2DIMCs with superior stability, holding great promise for prompting their integration in practical electronic and optoelectronic devices.
Ultra‐Strong and Tough Bio‐Based Polyester Elastomer with Excellent Photothermal Shape Memory Effect and Degradation Performance
Authors: Sun Danting , Mo Jianbin , Liu Weifeng , Yan Ning , Qiu Xueqing 
Published: April 2024

AbstractThe exploitation of bio‐based materials derived from renewable resources represents a pivotal strategic approach in addressing environmental pollution and alleviating the scarcity of fossil resources. 2,5‐Furandicarboxylic acid (FDCA) is the most potential substitute for terephthalic acid. Lignin is the most abundant aromatic biomass resource. However, the preparation of high‐performance lignin/FDCA‐based bio‐polyesters remains a formidable challenge. Herein, a multifunctional lignin‐modified polyester elastomer (LFPEe) is designed using FDCA‐based polyester oligomer (PPeF) and lignin (AOH) as building blocks. The LFPEe exhibits superior mechanical properties with the optimum tensile strength, fracture strain, and elastic recovery ratio up to 58.9 MPa, 610% and 88.9%, respectively, attributing to the formation of dual cross‐linking network with nanophase separation structure. Furthermore, leveraging the inherent characteristics of lignin, the LFPEe demonstrates excellent light‐controlled shape memory and excellent UV shielding performance. This innovative work not only breaks the performance dependence of FDCA‐based polyester on high molecular weight but also highlights a novel paradigm for value‐added utilization of lignin in sustainable bio‐polyesters.
Aerosol‐Synthesized Surfactant‐Free Single‐Walled Carbon Nanotube‐Based NO2 Sensors: Unprecedentedly High Sensitivity and Fast Recovery
Authors: Kim Sihyeok , Han Jiye , Choi Jin‐Myung , Nam Jeong‐Seok , Lee Il Hyun , Lee Yeounggyu , Novikov Ilya V. , Kauppinen Esko I. , Lee Keekeun , Jeon Il 
Published: April 2024

AbstractThis study pioneers a chemical sensor based on surfactant‐free aerosol‐synthesized single‐walled carbon nanotube (SWCNT) films for detecting nitrogen dioxide (NO2). Unlike conventional CNTs, the SWCNTs used in this study exhibit one of the highest surface‐to‐volume ratios. They show minimal bundling without the need for surfactants and have the lowest number of defects among reported CNTs. Furthermore, the dry‐transferrable and facile one‐step lamination results in promising industrial viability. When applied to devices, the sensor shows excellent sensitivity (41.6% at 500 ppb), rapid response/recovery time (14.2/120.8 s), a remarkably low limit of detection (below ≈0.161 ppb), minimal noise, repeatability for more than 50 cycles without fluctuation, and long‐term stability for longer than 6 months. This is the best performance reported for a pure CNT‐based sensor. In addition, the aerosol SWCNTs demonstrate consistent gas‐sensing performance even after 5000 bending cycles, indicating their suitability for wearable applications. Based on experimental and theoretical analyses, the proposed aerosol CNTs are expected to overcome the limitations associated with conventional CNT‐based sensors, thereby offering a promising avenue for various sensor applications.
Water‐Stable High‐Entropy Metal‐Organic Framework Nanosheets for Photocatalytic Hydrogen Production
Authors: Qi Shengliang , Zhu Kaixin , Xu Ting , Zhang Hefeng , Guo Xiangyang , Wang Junhui , Zhang Fuxiang , Zong Xu 
Published: April 2024

AbstractMetal‐organic frameworks (MOFs) have emerged as promising platforms for photocatalytic hydrogen evolution reaction (HER) due to their fascinating physiochemical properties. Rationally engineering the compositions and structures of MOFs can provide abundant opportunities for their optimization. In recent years, high‐entropy materials (HEMs) have demonstrated great potential in the energy and environment fields. However, there is still no report on the development of high‐entropy MOFs (HE‐MOFs) for photocatalytic HER in aqueous solution. Herein, the authors report the synthesis of a novel p‐type HE‐MOFs single crystal (HE‐MOF‐SC) and the corresponding HE‐MOFs nanosheets (HE‐MOF‐NS) capable of realizing visible‐light‐driven photocatalytic HER. Both HE‐MOF‐SC and HE‐MOF‐NS exhibit higher photocatalytic HER activity than all the single‐metal MOFs, which are supposed to be ascribed to the interplay between the different metal nodes in the HE‐MOFs that enables more efficient charge transfer. Moreover, impressively, the HE‐MOF‐NS demonstrates much higher photocatalytic activity than the HE‐MOF‐SC due to its thin thickness and enhanced surface area. At optimum conditions, the rate of H2 evolution on the HE‐MOF‐NS is ≈13.24 mmol h−1 g−1, which is among the highest values reported for water‐stable MOF photocatalysts. This work highlights the importance of developing advanced high‐entropy materials toward enhanced photocatalysis.
Recent Progress in Intelligent Packaging for Seafood and Meat Quality Monitoring
Authors: Nami Mohammad , Taheri Mahtab , Siddiqui Junaid , Deen Imran A. , Packirisamy Muthukumaran , Deen M. Jamal 
Published: April 2024

AbstractFood waste plays a crucial role in environmental and human health issues. To address these issues, intelligent packaging systems are proposed for the accurate assessment of the quality of food products. Intelligent packaging is a technology that integrates sensing systems with conventional packaging to provide smart sensing communication functions for real‐time food quality monitoring. The most important parts of this technology are generally classified as quantitative sensors (sensors) and qualitative sensors (indicators). Since seafood and meat products can spoil easily if not stored properly, applying intelligent packaging for real‐time monitoring of the safety of these products is beneficial. In this review, the spoiling process and essential performance characteristics are indicators of the quality of these food products are first discussed. Then, The characteristics and importance of various sensors and indicators that can be used for seafood and meat quality monitoring are presented. While discussing these topics, an updated review of recent scientific studies, preconditions, materials, advantages, and limitations are provided. Furthermore, the future need for improvements in intelligent packaging systems for real‐time quality and safety monitoring of food products is discussed. Finally, several important research examples of the challenges and perspectives of intelligent packaging applications for meat and seafood quality monitoring are presented.
Measuring and Simulating the Transient Packing Density During Ultrasound Directed Self‐Assembly and Vat Polymerization Manufacturing of Engineered Materials
Authors: Noparast Soheyl , Guevara Vasquez Fernando , Francoeur Mathieu , Raeymaekers Bart 
Published: April 2024

AbstractUltrasound‐directed self‐assembly (DSA) uses ultrasound waves to organize and orient particles dispersed in a fluid medium into specific patterns. Combining ultrasound DSA with vat photopolymerization (VP) enables manufacturing materials layer‐by‐layer, wherein each layer the organization and orientation of particles in the photopolymer is controlled, which enables tailoring the properties of the resulting composite materials. However, the particle packing density changes with time and location as particles organize into specific patterns. Hence, relating the ultrasound DSA process parameters to the transient local particle packing density is important to tailor the properties of the composite material, and to determine the maximum speed of the layer‐by‐layer VP process. This paper theoretically derives and experimentally validates a 3D ultrasound DSA model and evaluates the local particle packing density at locations where particles assemble as a function of time and ultrasound DSA process parameters. The particle packing density increases with increasing particle volume fraction, decreasing particle size, and decreasing fluid medium viscosity is determined. Increasing the particle size and decreasing the fluid medium viscosity decreases the time to reach steady‐state. This work contributes to using ultrasound DSA and VP as a materials manufacturing process.
Environmentally Driven Intelligent Textiles That Reversibly Actuate to Provide Large Change in Porosity, Loft, Shape, or Their Combination
Authors: Göktepe Fatma , Göktepe Özer , Baughman Ray H. , Zhang Mengmeng , Oh Jiyoung 
Published: April 2024

AbstractTextiles that intelligently respond to changes in the environment by reversibly providing dramatic changes in structure for comfort, safety, or appearance are widely sought. In order to facilitate applications development, here novel intelligent textile structures are described and developed by using polymer artificial muscles and examples of structures and mechanisms are provided that can be used in the future. These actuating textiles, which deploy a host of muscle yarn and fiber types, can change their porosity with or without any change in fabric lateral dimension or can change their loft or can either bend or fold upon temperature change. The presented intelligent textiles provide a porosity increase up to 38.3% from room temperature to 40 °C, while they exhibit a decrease in porosity up to 26.1% from room temperature to −5 °C. Textiles that can bend at an angle of 60° at 40 °C, while exhibiting a complete roll‐up at 70 °C, are also presented. An important way to change the direction of actuation produced by environmental exposure is to transition from homochiral fibers to heterochiral fibers. Other more complicated yarn types can usefully deploy chirality effects, such as yarns that are twisted and coiled, or yarns that are twisted, coiled, and then plied.
A Hybrid Neural Network‐Based Improved PSO Algorithm for Gas Turbine Emissions Prediction
Authors: Yousif Samar Taha , Ismail Firas Basim , Al‐Bazi Ammar 
Published: April 2024

AbstractIn gas‐fired power plants, emissions may reduce turbine blade rotation, thus decreasing power output. This study proposes a hybrid model integrating the Feed forward Neural Network (FFNN) model and Particle Swarm Optimization (PSO) algorithm to predict gas emissions from natural gas power plants. The FFNN predicts gas turbine nitrogen oxides (NOx) and carbon monoxide (CO) emissions, while the PSO optimizes FFNN weights, improving prediction accuracy. The PSO adopts a unique random number selection strategy, incorporating the K‐Nearest Neighbor (KNN) algorithm to reduce prediction errors. Neighbor Component Analysis (NCA) selects parameters most correlated with CO and NOx emissions. The hybrid model is constructed, trained, and testedusing publicly available datasets, evaluating performance with statistical metrics like Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). Results show significant improvement in FFNN training with the PSO algorithm, boosting CO and NOx prediction accuracy by 99.18% and 82.11%, respectively. The model achieves the lowest MSE, MAE, and RMSE values for CO and NOx emissions. Overall, the hybrid model achieves high prediction accuracy, particularly with optimized PSO parameter selection using seed random generators.
Supply chain risk in grain trading: Inventories as real options for shipping grain
Authors: Wilson William W. , Klebe Jesse 
Published: April 2024

AbstractIntegrating trading and logistics is an important challenge in commodity trading. Trading and logistics are strategic decisions and are integral to most commodities including grain shipping by rail, in addition to other modes (barges, ocean shipping). There are substantial risks, such as the ordering and placement of rail cars. The other risk is having sufficient grain stocks to load rail cars. Alternatives for managing these risks include holding grain inventories and the strategic use of shipping options. The purpose of this study is to develop a model for determining an optimal grain inventory strategy for shippers. The real option methodology is used to value uncertainty in rail car velocity and determine optimal purchases and inventories. The results show the importance of integrating trading and logistics decisions and illustrate that inventories can be interpreted and valued as real options that are affected by uncertainties. Taken together, the real options indicate how much extra inventory shippers should maintain to mitigate risks and maximize profits.
Phase behavior of sodium and potassium salts in their aqueous solutions: Experiment and computational thermodynamics
Authors: Kang Hongwei , Li Guoxuan , Lei Zhigang 
Published: April 2024

AbstractWith the rapid development of the semiconductor industry, the demand for ultraclean and high‐purity electronic chemicals, especially ultrapure water as a general solvent for cleaning semiconductor chips, has increased dramatically. The distillation process is a good choice for large‐scale production of ultrapure water that can be used to clean semiconductor chips, but there is a lack of basic thermodynamic theory for removing ionic impurities. In this work, the temperature and vapor–liquid phase composition of sodium and potassium salts aqueous solutions at vapor–liquid equilibrium (VLE) were investigated by experiments. The microstructure of each inorganic salt aqueous solution was explored by molecular dynamics simulation and quantum chemical calculation, and the interaction between each ion and water molecule was analyzed. A volatilization mechanism of inorganic salts was proposed, and it was found that the volatilization of inorganic salts in an aqueous solution was affected by the strength of interaction between the dissociated anions and cations and water molecules. Finally, the conductor‐like screening model segment activity coefficient (COSMO‐SAC) model predicted the VLE values of inorganic salt aqueous solutions. The prediction at low concentrations (xs < 0.06) was in good agreement with the experimental data.
Strategies of hepatitis C virus elimination for people who inject drugs receiving opioid agonist therapy in the era of direct‐acting antivirals
Authors: Sou Fai‐Meng , Chen Chien‐Hung , Huang Pao‐Yuan , Tsai Ming‐Chao , Yen Yi‐Hao , Lu Sheng‐Nan , Hung Chao‐Hung , Kuo Yuan‐Hung 
Published: April 2024

AbstractIncreased uptake of hepatitis C virus (HCV) treatment among people who inject drugs (PWID) is critical to achieve HCV elimination goals. This study attempted to observe the influence of different referral strategies among HCV‐infected PWID for direct‐acting antivirals (DAA). From January 2019 to November 2020, approximately 190 PWID regularly received opioid agonist therapies (OAT) in the drug addiction rehabilitation clinic of our institute. Among these, those with positive anti‐HCV were further referred to our hepatology clinics for HCV viremia screening and treatment. According to physician involvement, referral strategies were divided into three models including patient self‐intention referral (SR); intensive referral (IR) where patients were referred by clinicians; and fast‐intensive referral (FIR) where patients were referred by clinicians with a fast‐screening and easy‐treatment program. A total of 121 HCV‐infected PWID were enrolled and 71 (58.7%) of them received the referrals: 16 (22.5%) in the SR model, 36 (50.7%) in the IR model, and 19 (26.8%) in the FIR model. Monthly average referred patient number was 2.7 people in the SR model, 2.8 people in the IR model, and 4.8 people in the FIR model, respectively. Among the 71 referred patients, 64 (90.1%) had detectable HCV viremia with genotype distributions being genotype 1a (G1a) in 23 patients (35.9%), G1b in 10 (15.6%), G2 in 5 (7.8%), G3 in 6 (9.4%), and G6 in 20 (31.3%). Except for three patients who refused treatment, 61 patients underwent and completed DAA treatment including 35 patients for Maviret, 15 for Epclusa, 9 for Harvoni, and 2 for Zepatier. Excluding three patients who were lost to follow‐up and one becoming reinfected, 57 (93.4%) eventually achieved a sustained virologic response. Although HCV treatment uptake among PWID in this hospital‐based setting remained suboptimal, the FIR model with a quick‐to‐screen and easy‐to‐treat program was proven practicable in the hospital setting. Further innovative strategies are required to reach all HCV‐infected PWID receiving OAT.
What do recently housed young people imagine for the future of third places? Using game‐based inquiry to (re)imagine affirming, youth‐centered third places
Authors: Littman Danielle Maude , Milligan Tara , Berry Rebecca , Holloway Brendon , Scott Marquisha Lawrence 
Published: April 2024

AbstractThird places—public and community settings like parks and libraries—are theorized to serve as sources of social connection, community, and play. Yet, young people who hold marginalized identities, such as those experiencing homelessness and housing instability, often endure discrimination in third place settings. This study used game‐based inquiry to partner with recently housed young people who have experienced chronic housing instability (N = 21) to understand how they would (re)imagine future third places. We then analyzed transcripts from these game sessions through qualitative thematic analysis. Participants suggested that certain tenets must be present in third places: they must offer opportunities for agency and individualization; they must meet everyday needs; and they must be explicitly inclusive. To actualize these tenets, participants imagined places that meet many needs and do many things; portable and adaptable physical spaces; freedom to choose how to play; attending to and subverting oppressive social hierarchies; providing choice for privacy or connection; knowing people will be around; and free amenities. These findings have implications for theoretical development, practices in present and future third places, and methodological development of games in research.
Modular Design of Highly Stable Semiconducting Porous Coordination Polymer for Efficient Electrosynthesis of Ammonia
Authors: Xue Ziqian , Yao Ming‐Shui , Otake Ken‐ichi , Nishiyama Yusuke , Aoyama Yoshitaka , Zheng Jia‐Jia , Zhang Siquan , Kajiwara Takashi , Horike Satoshi , Kitagawa Susumu 
Published: April 2024

AbstractDeveloping highly stable porous coordination polymers (PCPs) with integrated electrical conductivity is crucial for advancing our understanding of electrocatalytic mechanisms and the structure–activity relationship of electrocatalysts. However, achieving this goal remains a formidable challenge because of the electrochemical instability observed in most PCPs. Herein, we develop a “modular design” strategy to construct electrochemically stable semiconducting PCP, namely, Fe‐pyNDI, which incorporates a chain‐type Fe‐pyrazole metal cluster and π‐stacking column with effective synergistic effects. The three‐dimensional electron diffraction (3D ED) technique resolves the precise structure. Both theoretical and experimental investigation confirms that the π‐stacking column in Fe‐pyNDI can provide an efficient electron transport path and enhance the structural stability of the material. As a result, Fe‐pyNDI can serve as an efficient model electrocatalyst for nitrate reduction reaction (NO3RR) to ammonia with a superior ammonia yield of 339.2 μmol h−1 cm−2 (14677 μg h−1 mgcat.−1) and a faradaic efficiency of 87 % at neutral electrolyte, which is comparable to state‐of‐the‐art electrocatalysts. The in‐situ X‐ray absorption spectroscopy (XAS) reveals that during the reaction, the structure of Fe‐pyNDI can be kept, while part of the Fe3+ in Fe‐pyNDI was reduced in situ to Fe2+, which serves as the potential active species for NO3RR.