bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Approach for Mixed‐Methods Research Using Large Language Models: A Report Using Patients’ Perspectives on Barriers to Arthroplasty
Authors: Mannstadt Insa , Goodman Susan M. , Rajan Mangala , Young Sarah R. , Wang Fei , Navarro‐Millán Iris , Mehta Bella 
Published: March 2024

ObjectiveMixed‐methods research is valuable in health care to gain insights into patient perceptions. However, analyzing textual data from interviews can be time‐consuming and require multiple analysts for investigator triangulation. This study aims to explore a novel approach to investigator triangulation in mixed‐methods research by employing a large language model (LLM) for analyzing data from patient interviews.MethodsThis study compared the thematic analysis and survey generation performed by human investigators and ChatGPT‐4, which uses GPT‐4 as its backbone model, using data from an existing study that explored patient perceptions of barriers to arthroplasty. The human‐ and ChatGPT‐4–generated themes and surveys were compared and evaluated based on their representation of salient themes from a predetermined topic guide.ResultsChatGPT‐4 generated analogous dominant themes and a comprehensive corresponding survey as the human investigators but in significantly less time. The survey questions generated by ChatGPT‐4 were less precise than those developed by human investigators. The mixed‐methods flowchart proposes integrating LLMs and human investigators as a supplementary tool for the preliminary thematic analysis of qualitative data and survey generation.ConclusionBy utilizing a combination of LLMs and human investigators through investigator triangulation, researchers may be able to conduct more efficient mixed‐methods research to better understand patient perspectives. Ethical and qualitative implications of using LLMs should be considered.
Enhanced Transport Kinetics of Electrochromic Devices by W18O49 NW/Ti3C2Tx Composite Films
Authors: Hassan Muhammad , Ghaffar Abdul , Lou Gang , Miao Ziang , Peng Zhengchun , Celebi Kemal 
Published: March 2024

AbstractElectrochromic devices can facilitate the realization of a wide set of future applications, ranging from energy‐saving windows to smart wearables and stealth. Historically, tungsten oxides have been the most studied materials for electrochromism, albeit with bottlenecks like limited conductivity, high charge transport barrier, and low ion diffusivity. Here, inspired by the recent MXene materials, the study has engineered an electrochromic composite of MXene nanosheets (Ti3C2Tx) and W18O49 nanowires (NWs). A transparent conductive electrode is fabricated by co‐assembly of Ag and W18O49NWs, followed by depositing W18O49 NW/Ti3C2Tx layers for the fabrication of the electrochromic device. The incorporation of Ti3C2Tx nanosheets enhances the transport of electrons and ions within the electrochromic layer, leading to a significant improvement in the electrochromic performance. Noteworthily, the film structure comprising 15 layers of W18O49 NW/Ti3C2Tx composite reveals enhanced transmittance modulation (61%), rapid response time (4.5 s coloration, 6.5 s bleaching), and high coloration efficiency (139.1 cm2 C−1). Moreover, the electrode also presents a high diffusion coefficient of Li+ and good cycling stability (96.66% after 250 switching cycles). Finally, a large‐scale (15 × 20 cm2) flexible electrochromic device with a solid electrolyte is successfully fabricated and utilized as a smart window and a flexible stealth patch.
First Advanced Bilayer Scaffolds for Tailored Skin Tissue Engineering Produced via Electrospinning and Melt Electrowriting
Authors: Girard Fabien , Lajoye Caroline , Camman Marie , Tissot Nicolas , Berthelot Pedurand Florence , Tandon Biranche , Moedder Denise , Liashenko Ievgenii , Salameh Sacha , Dalton Paul D. , Rielland Maïté 
Published: March 2024

AbstractIn vitro skin models are validated methods for screening cosmetics and pharmaceuticals, but still have limitations. The bilayer poly(ε‐caprolactone) scaffold/membrane model described here overcomes some of these deficits by integrating a solution electrospun (SES) membrane at the dermoepidermal interface and a melt electrowritten (MEW) scaffold that provides an optimal open‐pore environment for the dermis. To the knowledge, this scaffold/membrane model is the only one capable of creating a properly differentiated, full thickness skin model with neosynthesized extracellular matrix (ECM) in only 18 days. Both the wavy and straight fiber scaffold designs create a well‐organized dermis, but dermal collagen organization differs between designs. Adding cells and vitamin C to the scaffolds improves the mechanical properties to more closely mimic native human skin. These findings establish bicomponent scaffolds as a promising advancement for rapidly creating different skin models with varied properties. The versatility and adaptability of the described model can be used for studying how the biological and physical microenvironment impact skin, and testing dermo‐cosmetics and pharmaceutical treatments on different ages of skin. Furthermore, it can be an excellent new tool for studying wound healing and development into its use as a graft or wound dressing is ongoing.
Enhanced Piezoelectric Energy Harvester by Employing Freestanding Single‐Crystal BaTiO3 Films in PVDF‐TrFE Based Composites
Authors: Peng Ruobo , Zhang Butong , Dong Guohua , Wang Yinghui , Yang Guannan , Zhang Jie , Peng Bin , Zhao Yanan , Liu Ming 
Published: March 2024

AbstractAdvancements in wearable electronics and Internet of Things (IoT) sensors have catalyzed the need for effective micro‐energy harvesting. Piezoelectric nanogenerators (PENGs) are ideal due to their high conversion efficiency and durability. However, the contrast between the high piezoelectric coefficients of brittle inorganic ceramics and the lower coefficients of superior flexibility and biocompatibility of organic polymers poses a significant challenge. This work introduces a novel multilayer composite PENG, integrating a single‐crystal BaTiO3 (BTO) film between poly(vinylidene fluoride‐co‐trifluoroethylene) (PVDF‐TrFE) layers. The PVDF‐TrFE/BTO/PVDF‐TrFE PENGs demonstrate substantially improved energy harvesting performance, with outputs reaching up to 15.1 V, 2.39 µA, and power density of 17.33 µW cm−2 during bending deformation. This power density represents a significant increase compared to pure PVDF‐TrFE and nanoparticle BTO‐doped PVDF‐TrFE PENGs. Durability tests show consistent performance, with a stable ∼15.0 V output across 2000 bending cycles. Additionally, when attached to the human body, these PENGs efficiently convert body motions into electrical responses. This work demonstrates a significant enhancement in the performance of PENGs using sandwich‐structured composite of PVDF‐TrFE and freestanding single‐crystal BTO films, showing its potential to address the power requirements of wearable and flexible electronic devices.
Triboelectric‐Responsive Drug Delivery Hydrogel for Accelerating Infected Wound Healing
Authors: Qin Xuan , Shi Haoliang , Wen Zhen , Chu Binbin , Li Hongyang , Wang Houyu , He Yao , Sun Xuhui 
Published: March 2024

AbstractElectrotherapy is of great interest in the field of tissue repair as an effective, well‐tolerated, and noninvasive treatment. Triboelectric nanogenerator (TENG) has shown advantages in promoting wound healing due to its peak output characteristic and low Joule heating effect. However, it is limited in infected wound healing due to poor antimicrobial capacity. Here, a wearable triboelectric stimulator (WTS) is developed that consists of a flexible TENG (F‐TENG) and a triboelectric‐responsive drug delivery hydrogel (TR‐DDH) for healing of bacterium‐infected wounds. F‐TENG can generate pulsed current to wounds by converting mechanical energy from body movements. Polypyrrole is prone to reduction and volume contraction under electrical stimulation, resulting in desorption of curcumin nanoparticles (CUR NPs) from the polypyrrole in TR‐DDH. Therefore, the highly efficient and controllable release of CUR NPs can be achieved by triboelectric stimulation. According to the in vitro and in vivo experiments, WTS has the greatest antimicrobial effect and the fastest promotion of infected wound healing compared to treatment with electrical stimulation or curcumin. Finally, the safety assessment demonstrates that the WTS has excellent tissue safety for chronic wound healing. Synergistic therapy with WTS provides an efficient strategy for chronic wound healing and smart‐responsive drug delivery systems.
Rationally Designed Benzobisthiadiazole‐Based Covalent Organic Framework for High‐Performance NIR‐II Fluorescence Imaging‐Guided Photodynamic Therapy
Authors: Zhang Xian , Dou You , Liu Shuang , Chen Peiyao , Wen Yating , Li Junrong , Sun Yao , Zhang Ruiping 
Published: March 2024

AbstractAlthough being applied as photosensitizers for photodynamic therapy, covalent organic frameworks (COFs) fail the precise fluorescence imaging in vivo and phototherapy in deep‐tissue, due to short excitation/emission wavelengths. Herein, this work proposes the first example of NIR‐II emissive and benzobisthiadiazole‐based COF‐980. Comparing to its ligands, the structure of COF‐980 can more efficiently reducing the energy gap (ΔES1‐T1) between the excited state and the triplet state to enhance photodynamic therapy efficiency. Importantly, COF‐980 demonstrates high photostability, good anti‐diffusion property, superior reactive oxygen species (ROS) generation efficiency, promising imaging ability, and ROS production in deep tissue (≈8 mm). Surprisingly, COF‐980 combined with laser irradiation could trigger larger amount of intracellular ROS to high efficiently induce cancer cell death. Notably, COF‐980 NPs precisely enable PDT guided by NIR‐II fluorescence imaging that effectively inhibit the 4T1 tumor growth with negligible adverse effects. This study provides a universal approach to developing long‐wavelength emissive COFs and exploits its applications for biomedicine.
Progress and Opportunities for Machine Learning in Materials and Processes of Additive Manufacturing
Authors: Ng Wei Long , Goh Guo Liang , Goh Guo Dong , Ten Jyi Sheuan Jason , Yeong Wai Yee 
Published: March 2024

AbstractIn recent years, there has been widespread adoption of machine learning (ML) technologies to unravel intricate relationships among diverse parameters in various additive manufacturing (AM) techniques. These ML models excel at recognizing complex patterns from extensive, well‐curated datasets, thereby unveiling latent knowledge crucial for informed decision‐making during the AM process. The collaborative synergy between ML and AM holds the potential to revolutionize the design and production of AM‐printed parts. This review delves into the challenges and opportunities emerging at the intersection of these two dynamic fields. It provides a comprehensive analysis of the publication landscape for ML‐related research in the field of AM, explores common ML applications in AM research (such as quality control, process optimization, design optimization, microstructure analysis, and material formulation), and concludes by presenting an outlook that underscores the utilization of advanced ML models, the development of emerging sensors, and ML applications in emerging AM‐related fields. Notably, ML has garnered increased attention in AM due to its superior performance across various AM‐related applications. It is envisioned that the integration of ML into AM processes will significantly enhance 3D printing capabilities across diverse AM‐related research areas.
Top‐Down Induced Crystallization Orientation toward Highly Efficient p‐i‐n Perovskite Solar Cells
Authors: Jiang Xiaofen , Liu Baoze , Wu Xin , Zhang Shoufeng , Zhang Dong , Wang Xue , Gao Shuang , Huang Zongming , Wang Haolin , Li Bo , Xiao Zhengguo , Chen Tao , Jen Alex K.‐Y. , Xiao Shuang , Yang Shangfeng , Zhu Zonglong 
Published: March 2024

AbstractCrystallization orientation plays a crucial role in determining the performance and stability of perovskite solar cells (PVSCs), whereas effective strategies for realizing oriented perovskite crystallization is still lacking. Herein, a facile and efficient top‐down strategy is reported to manipulate the crystallization orientation via treating perovskite wet film with propylamine chloride (PACl) before annealing. The PA+ ions tend to be adsorbed on the (001) facet of the perovskite surface, resulting in the reduced cleavage energy to induce (001) orientation‐dominated growth of perovskite film and then reduce the temperature of phase transition, meanwhile, the penetrating Cl ions further regulate the crystallization process. As‐prepared (001)‐dominant perovskite films exhibit the ameliorative film homogeneity in terms of vertical and horizontal scale, leading to alleviated lattice mismatch and lowered defect density. The resultant PVSC devices deliver a champion power conversion efficiency (PCE) of 25.07% with enhanced stability, and the unencapsulated PVSC device maintains 95% of its initial PCE after 1000 h of operation at the maximum power point under simulated AM 1.5G illumination.
Correlation between Voltage, Strain, and Impedance as a Function of Pressure of a Nickel‐Rich NMC Lithium‐Ion Pouch Cell
Authors: Laufen Hendrik , Berg Sascha , Engeser Julian , Strautmann Maya , Koprivc Aleksander , Rahe Christiane , Figgemeier Egbert , Sauer Dirk Uwe 
Published: March 2024

AbstractFulfilling the service life of a Lithium‐Ion battery in each intended application requires further understanding of the cells' lifetime and reliability. Derived from literature, controlling the external pressure constant on Lithium‐Ion battery cells is an inevitable factor to extend the cycle lifetime. Thus, active knowledge of the cells' strain and understanding the impact of an external pressure on the impedance is mandatory to evaluate an optimum pressure to improve the cell performance. This work presents correlations between voltage, strain, and impedance as a function of the applied constant external pressure on a nickel‐rich nickel‐mangan‐cobalt (NMC) lithium‐ion pouch cell. Utilizing a high precision universal testing machine reveals a negligible change of the cells' maximum stroke within the pressure range from 0 to 1000 kPa. Additionally, an optimum pressure between 100 and 300 kPa is revealed by analyzing a series of electrochemical impedance spectroscopy data measured at different constant external pressures. Within this pressure range the charge transfer resistance as well as the diffusive processes exhibit its optimum.
Precisely Engineering Asymmetric Atomic CoN4 by Electron Donating and Extracting for Oxygen Reduction Reaction
Authors: Lv Minghui , Cui Cheng‐Xing , Huang Niu , Wu Mingzhu , Wang Qiao , Gao Tao , Zheng Yong , Li Hui , Liu Wei , Huang Yingping , Ma Tianyi , Ye Liqun 
Published: March 2024

AbstractThe development of nonpyrolytic catalysts featuring precisely defined active sites represents an effective strategy for investigating the fundamental relationship between the catalytic activity of oxygen reduction reaction (ORR) catalysts and their local coordination environments. In this study, we have synthesized a series of model electrocatalysts with well‐defined CoN4 centers and nonplanar symmetric coordination structures. These catalysts were prepared by a sequential process involving the chelation of cobalt salts and 1,10‐phenanthroline‐based ligands with various substituent groups (phen(X), where X=OH, CH3, H, Br, Cl) onto covalent triazine frameworks (CTFs). By modulating the electron‐donating or electron‐withdrawing properties of the substituent groups on the phen‐based ligands, the electron density surrounding the CoN4 centers was effectively controlled. Our results demonstrated a direct correlation between the catalytic activity of the CoN4 centers and the electron‐donating ability of the substituent group on the phenanthroline ligands. Notably, the catalyst denoted as BCTF−Co‐phen(OH), featuring the electron‐donating OH group, exhibited the highest ORR catalytic activity. This custom‐crafted catalyst achieved a remarkable half‐wave potential of up to 0.80 V vs. RHE and an impressive turnover frequency (TOF) value of 47.4×10−3 Hz at 0.80 V vs. RHE in an alkaline environment.
Multi‐Functional Integration of Phosphor, Initiator, and Crosslinker for the Photo‐Polymerization of Flexible Phosphorescent Polymer Gels
Authors: Cao Yanyan , Wang Dan , Zhang Yongfeng , Li Gengchen , Gao Chong , Li Wei , Chen Xiaoting , Chen Xiaofei , Sun Peng , Dong Yuping , Cai Zhengxu , He Zhiyuan 
Published: March 2024

AbstractA general approach to constructing room temperature phosphorescence (RTP) materials involves the incorporation of a phosphorescent emitter into a rigid host or polymers with high glass transition temperature. However, these materials often suffer from poor processability and suboptimal mechanical properties, limiting their practical applications. In this work, we developed benzothiadiazole‐based dialkene (BTD‐HEA), a multifunctional phosphorescent emitter with a remarkable yield of intersystem crossing (ΦISC, 99.83 %). Its high triplet exciton generation ability and dialkene structure enable BTD‐HEA to act as a photoinitiator and crosslinker, efficiently initiating the polymerization of various monomers within 120 seconds. A range of flexible phosphorescence gels, including hydrogels, organogels, ionogels, and aerogels were fabricated, which exhibit outstanding stretchability and recoverability. Furthermore, the unique fluorescent‐phosphorescent colorimetric properties of the gels provide a more sensitive method for the visual determination of the polymerization process. Notably, the phosphorescent emission intensity of the hydrogel can be increased by the formation of ice, allowing for the precise detection of hydrogel freezing. The versatility of this emitter paves the way for fabricating various flexible phosphorescence gels with diverse morphologies using microfluidics, film‐shearing, roll coating process, and two/three‐dimensional printing, showcasing its potential applications in the fields of bioimaging and bioengineering.
Molecular Twist‐Induced Single‐Crystal Isomerization and Valence Tautomeric Transitions in a Cobalt‐Dioxolene Complex
Authors: Yue Ling‐Tai , Shapovalova Svetlana O. , Hu Jie‐Sheng , Chegerev Maxim G. , Zhao Yu‐Meng , Liu Cheng‐Dong , Yu Meng , Starikova Alyona A. , Guda Alexander A. , Yao Zi‐Shuo , Tao Jun 
Published: March 2024

AbstractA mononuclear valence tautomeric (VT) complex, [Co(pycz)2(Sq)(Cat)] (1‐trans), where pycz = 9‐(pyridin‐4‐yl)‐9H‐carbazole, Sq⋅− = 3,5‐di‐tert‐butyl‐semiquinonato, and Cat2− = 3,5‐di‐tert‐butyl‐catecholato, is synthesized in the trans configuration, which undergoes one‐step valence tautomeric transition above room temperature. Remarkably, 1‐trans can transform into its isomeric structure, [Co(pycz)2(Sq)(Sq)] (1‐cis), at temperature above 350 K in a single‐crystal‐to‐single‐crystal way by in situ molecular twist, and the resulting 1‐cis exhibits a pronounced two‐step VT transition during magnetic measurements that is rare for mononuclear VT complexes. Such drastic solid‐state structural transformation is reported in VT compounds for the first time, which is actuated by a crystal surface's melting‐recrystallization induced phase transition process. DFT calculations offer an underlying mechanism suggesting a concerted bond rotation during the structural transformation. The results demonstrate an unconventional approach that realizes structural transformation of VT complexes and the control of VT performance.
Bringing a scalable adaptive hybrid modeling framework closer to industrial use: Application on a multiscale fungal fermentation
Authors: Rydal Thomas , Frandsen Jesper , Nadal‐Rey Gisela , Albæk Mads Orla , Ramin Pedram 
Published: March 2024

AbstractDigitalization has paved the way for new paradigms such as digital shadows and digital twins for fermentation processes, opening the door for real‐time process monitoring, control, and optimization. With a digital shadow, real‐time model adaptation to accommodate complex metabolic phenomena such as metabolic shifts of a process can be monitored. Despite the many benefits of digitalization, the potential has not been fully reached in the industry. This study investigates the development of a digital shadow for a very complex fungal fermentation process in terms of microbial physiology and fermentation operation on pilot‐scale at Novonesis and the challenges thereof. The process has historically been difficult to optimize and control due to a lack of offline measurements and an absence of biomass measurements. Pilot‐scale and lab‐scale fermentations were conducted for model development and validation. With all available pilot‐scale data, a data‐driven soft sensor was developed to estimate the main substrate concentration (glucose) with a normalized root mean squared error (N‐RMSE) of 2%. This robust data‐driven soft sensor was able to estimate accurately in lab‐scale (volume < 20× pilot) with a N‐RMSE of 7.8%. A hybrid soft sensor was developed by combining the data‐driven soft sensor with a mass balance to estimate the glycerol and biomass concentrations on pilot‐scale data with N‐RMSEs of 11% and 21%, respectively. A digital shadow modeling framework was developed by coupling a mechanistic model (MM) with the hybrid soft sensor. The digital shadow modeling framework significantly improved the predictability compared with the MM. The contribution of this study brings the application of digital shadows closer to industrial implementation. It demonstrates the high potential of using this type of modeling framework for scale‐up and leads the way to a new generation of in silico‐based process development.
Enhancing real‐time cell culture monitoring: Automated Raman model optimization with Taguchi method
Authors: Dong Xiaoxiao , Yan Xu , Wan Yuxiang , Gao Dong , Jiao Jingyu , Wang Haibin , Qu Haibin 
Published: March 2024

AbstractRaman spectroscopy has found widespread usage in monitoring cell culture processes both in research and practical applications. However, commonly, preprocessing methods, spectral regions, and modeling parameters have been chosen based on experience or trial‐and‐error strategies. These choices can significantly impact the performance of the models. There is an urgent need for a simple, effective, and automated approach to determine a suitable procedure for constructing accurate models. This paper introduces the adoption of a design of experiment (DoE) method to optimize partial least squares models for measuring the concentration of different components in cell culture bioreactors. The experimental implementation utilized the orthogonal test table L25(56). Within this framework, five factors were identified as control variables for the DoE method: the window width of Savitzky–Golay smoothing, the baseline correction method, the order of preprocessing steps, spectral regions, and the number of latent variables. The evaluation method for the model was considered as a factor subject to noise. The optimal combination of levels was determined through the signal‐to‐noise ratio response table employing Taguchi analysis. The effectiveness of this approach was validated through two cases, involving different cultivation scales, different Raman spectrometers, and different analytical components. The results consistently demonstrated that the proposed approach closely approximated the global optimum, regardless of data set size, predictive components, or the brand of Raman spectrometer. The performance of models recommended by the DoE strategy consistently surpassed those built using raw data, underscoring the reliability of models generated through this approach. When compared to exhaustive all‐combination experiments, the DoE approach significantly reduces calculation times, making it highly practical for the implementation of Raman spectroscopy in bioprocess monitoring.