bluuebunny/crossref_metadata_2025 huggingface dataset:
An exactly divergence-free hybridized discontinuous Galerkin method for the generalized Boussinesq equations with singular heat source
Authors: Leng Haitao
Published: May 2024

The purpose of this work is to propose and analyze a hybridized discontinuous Galerkin (HDG) method for the generalized Boussinesq equations with singular heat source. We use polynomials of order k, k − 1 and k to approximate the velocity, the pressure and the temperature. By introducing Lagrange multipliers for the pressure, the approximate velocity field obtained by the HDG method is shown to be exactly divergence-free and H(div)-conforming. Under a smallness assumption on the problem data and solutions, we prove by Brouwer’s fixed point theorem that the discrete system has a solution in two dimensions. If the viscosity and thermal conductivity are further assumed to be positive constants, a priori error estimates with convergence rate O(h) and efficient and reliable a posteriori error estimates are derived. Finally numerical examples illustrate the theoretical analysis and show the performance of the obtained a posteriori error estimator.
Fünf Faktoren für einen positiven Führungsstil – PERMA-Lead
Authors: Holtmeier Lisa
Published: May 2024

Weniger Fluktuation, gesunde Mitarbeitende, mehr Engagement, höhere Zufriedenheit und Motivation – zu schön, um wahr zu sein? Ganz und gar nicht! PERMA-Lead ist ein Führungsansatz, der all das ermöglicht und sogar die passende Evidenz liefert. Hier bekommen Sie einen Einblick in den Führungsansatz der Positiven Psychologie.
Ich weiß nur, dass ich nichts weiß – Wie Evidenz zu (Nicht-)Wissen führen kann
Authors: Kiesele Julian
Published: May 2024

Seit der Antike machen sich Menschen Gedanken über das Problem von Wissen und Nichtwissen. Dieser Diskurs erlebt aktuell mit dem Aufkeimen wissenschaftsbasierter Praktiken eine Renaissance. Infolgedessen werden Begrifflichkeiten wie „Evidence-Based Medicine“ zu bloßen Worthülsen degradiert. Julian Kiesele erklärt, was Wissen und Evidenz überhaupt sind, wie sie zustande kommen, welche Formen es gibt und wofür diese notwendig sind.
Aktiv gegen das Vergessen – Demenz – ein Zukunftsthema für die Physiotherapie
Authors: Kemper Claudia , Emicke Renske
Published: May 2024

Demenzielle Erkrankungen spielen eine zunehmend wichtige Rolle im therapeutischen Alltag. Studien zeigen jedoch, dass der Zugang zur Physiotherapie für Menschen mit Demenz nicht rechtzeitig und in ausreichendem Umfang gegeben ist. Dabei wird eine Versorgung, die die Selbstständigkeit, den Verbleib in der eigenen Häuslichkeit und die Unterstützung Angehöriger in den Mittelpunkt stellt, immer bedeutender.
Effect of Postrinsing Times and Methods on Surface Roughness, Hardness, and Polymerization of 3D-Printed Photopolymer Resin
Authors: Katheng Awutsadaporn , Prawatvatchara Wisarut , Tonprasong Watcharapong , Namano Sahaprom , Kongkon Paweena
Published: May 2024

Objectives This in vitro study investigated the effects of different postrinsing times and methods on the surface roughness, surface hardness, and degree of polymerization of materials manufactured via stereolithography (SLA).

Materials and Methods A total of 288 disk-shaped specimens were manufactured using an SLA three-dimensional (3D) printer. The specimens were randomly divided into nine groups (n = 32) based on rinsing times and methods. The groups were categorized into three rinsing methods: automated, ultrasonic, and hand washing, with rinsing times of 5, 10, and 15 minutes using a 99% isopropanol alcohol as a solvent. Linear roughness (Ra) and area roughness (Sa) were measured using a 3D confocal laser microscopy; the roughness morphology was evaluated by using scanning electron microscopy. Vickers hardness (VHN) tests were performed using a Vickers microhardness tester. Fourier-transform infrared spectrometry was used to determine the degree of conversion of treated specimens.

Statistical Analysis Data were statistically analyzed using two-way analysis of variance. The post hoc Tukey tests were conducted to compare the differences between groups (p < 0.05).

Results The choice of the rinsing time and method affected the surface properties of the SLA photopolymer resin. The 15 minutes of ultrasonic method exhibited the highest Ra scores (0.86 ± 0.1 µm), while the 15 minutes of automated method presented the highest Sa scores (1.77 ± 0.35 µm). For the VHN test, the 15 minutes of ultrasonic method displayed the highest VHN score (18.26 ± 1.03 kgf/mm2). For the degree of polymerization, the 15 minutes of automated method was initially identified as the most effective (87.22 ± 6.80).

Conclusion To facilitate the overall surface roughness, surface hardness, and degree of polymerization, the optimal choice of postprocessing rinsing time and method for achieving a clear photopolymer resin was determined to be the ultrasonic method with a rinsing time of 15 minutes.
Electron transport through degenerate electron level in single-molecular junction in the presence of electron-vibrational coupling and attractive electron-electron correlations
Authors: Ponezha E. A.
Published: May 2024

Electron transport through a molecular junction consisted of a single molecule coupled to macroscopic leads is studied in the nonequilibrium regime. The molecule is modeled as a degenerate energy level with an electron-vibrational interaction and attractive electron-electron correlation which lifts the degeneracy. The level occupancy and differential conductance are calculated in the antiadiabatic regime with an account of molecule-lead coupling at low temperature and finite voltage. The method of transport spectroscopy made it possible to determine through which of the split levels tunneling takes place depending on the applied voltages and to estimate the current through these levels. The cases of a negative differential conductance are discussed. The influence of the electron-vibrational coupling of different strength on electron tunneling through 2- and 4-fold degenerate level on the molecule in the presence of the attractive electron-electron interaction is analyzed.
Fourier transform with matched non-linear frequency modulation in femtosecond laser ranging with imbalanced dispersion
Authors: Bychkov A. S. , Kubasov P. V. , Kamenev V. G. , Dormidonov A. E.
Published: May 2024

We propose a new algorithm based on the Fourier transform with matched non-linear frequency modulation for processing femtosecond laser ranging data. The algorithm allows us to compensate for both the influence of the third-order dispersion in the fiber-based dispersive Fourier spectrometer and the influence of imbalanced second- and third-order dispersions in the interferometer. Computer simulations and experimental results show that the proposed algorithm significantly increases the accuracy of measuring the position of an object at larger displacements than the well-established non-linear time stretching.
Graphics processing unit/artificial neural network-accelerated large-eddy simulation of swirling premixed flames
Authors: Zhang Min , Mao Runze , Li Han , An Zhenhua , Chen Zhi X.
Published: May 2024

Within the scope of reacting flow simulations, the real-time direct integration (DI) of stiff ordinary differential equations for the computation of chemical kinetics stands as the primary demand on computational resources. Meanwhile, as the number of transport equations that need to be solved increases, the computational cost grows more substantially, particularly for those combustion models involving direct coupling of chemistry and flow such as the transported probability density function model. In the current study, an integrated graphics processing unit-artificial neural network (GPU-ANN) framework is introduced to comply with heavy computational costs while maintaining high fidelity. Within this framework, a GPU-based solver is employed to solve partial differential equations and compute thermal and transport properties, and an ANN is utilized to replace the calculation of reaction rates. Large eddy simulations of two swirling flames provide a robust validation, affirming and extending the GPU-ANN approach's applicability to challenging scenarios. The simulation results demonstrate a strong correlation in the macro flame structure and statistical characteristics between the GPU-ANN approach and the traditional central processing unit (CPU)-based solver with DI. This comparison indicates that the GPU-ANN approach is capable of attaining the same degree of precision as the conventional CPU-DI solver, even in more complex scenarios. In addition, the overall speed-up factor for the GPU-ANN approach is over two orders of magnitude. This study establishes the potential groundwork for widespread application of the proposed GPU-ANN approach in combustion simulations, addressing various and complex scenarios based on detailed chemistry, while significantly reducing computational costs.
Uncertainty analysis of the plasma impedance probe
Authors: Brooks J. W. , Paliwoda M. C.
Published: May 2024

A plasma impedance probe (PIP) is a type of in situ, radio frequency (RF) probe that is traditionally used to measure plasma properties (e.g., density) in low-density environments such as the Earth's ionosphere. We believe that PIPs are underrepresented in laboratory settings, in part because PIP operation and analysis have not been optimized for signal-to-noise ratio (SNR), reducing the probe's accuracy, upper density limit, and acquisition rate. This work presents our efforts in streamlining and simplifying the PIP design, circuit-based-model, calibration, and analysis for unmagnetized laboratory plasmas, in both continuous and pulsed PIP operation. The focus of this work is a Monte Carlo uncertainty analysis, which identifies operational and analysis procedures that improve SNR by multiple orders of magnitude. Additionally, this analysis provides evidence that the sheath resonance (and not the plasma frequency as previously believed) sets the PIP's upper density limit, which likely provides an additional method for extending the PIP's density limit.
Phase shifter based on two-dimensional electron system on a dielectric substrate
Authors: Dzhikirba K. R. , Khudaiberdiev D. A. , Shuvaev A. , Astrakhantseva A. S. , Kukushkin I. V. , Muravev V. M.
Published: May 2024

We experimentally investigate phase shift gained by electromagnetic radiation transmitted through a two-dimensional electron system (2DES) on a dielectric substrate. We systematically examined the dependence of the phase shift on the radiation frequency and 2DES electron density for the GaAs semiconductor substrate. A theoretical approach was developed that found good agreement with experimental results. We demonstrate a practically achievable phase shift of 105°. Obtained findings pave the way for the design of terahertz devices that can manipulate the radiation phase in a controlled and precise manner.
ANN based LIBS models for quasi-experimental spectra relevant for materials for next-step fusion reactors
Authors: Gąsior P. , Kastek M. , Ladygina M. , Sokulski D.
Published: May 2024

Following the successful demonstration of machine learning (ML) models for laser induced breakdown spectroscopy (LIBS) adaptation in fusion reactor fuel retention monitoring using synthetic data [Gąsior et al., Spectrochim. Acta, Part B 199, 106576 (2023)], this study focuses on implementing operability on experimental data. To achieve this, Simulated Eperimental Spectra (SES) data are generated and used for validation of a chemical composition estimation model trained on dimensionally reduced synthetic spectral data (DRSSD). Principal component analysis is employed for dimensionality reduction of both SES and DRSSD. To simulate real experimental conditions, the synthetic data, generated by a dedicated tool [M. Kastek (2022), “SimulatedLIBS,” Zenodo. http://dx.doi.org/10.5281/zenodo.7369805] is processed through the transmission function of a real spectroscopy setup at IPPLM. Separate and optimized artificial neural network models are implemented for conversion and chemical composition estimation. The conversion model takes DR-SES as features and DR-SSD as targets. Validation using converted SES data demonstrates chemical composition predictions comparable to those from synthetic data, with the highest relative uncertainty increase below 40% and a normalized root-mean-square error of prediction below 7%. This work represents a significant step toward adapting ML-based LIBS for fuel and impurity retention monitoring in the walls of next-generation fusion devices.
Polarization and coherence properties of a partially coherent elegant Laguerre–Gaussian vortex beam in turbulent plasma
Authors: Hassan Labiba F. , Alkelly Abdu A. , Khaled M. A. H.
Published: May 2024

The analytical expressions for the cross-spectral density matrix elements of the partially coherent elegant Laguerre–Gaussian (eLG) vortex beam propagating through anisotropic turbulent plasma were derived based on the extended Huygens-Fresnel principle and used to study the changes in the polarization degree and the coherence degree of the partially coherent eLG vortex beam in the turbulent plasma. The numerical results show that the polarization degree of a partially coherent eLG vortex beam reaches a specific value (which is equal to the degree of polarization in the source plane) after a long propagation distance in the turbulent plasma. Moreover, this value is independent of the beam order, topological charge, correlation coefficient, wavelength of the source plane, anisotropy parameter, refractive index fluctuation variance, and outer and inner scales of the turbulent plasma. The results also show that with increasing distance, the coherence degree first decreases from unity and then oscillates around zero. However, this oscillation gradually disappears after traveling a long distance. Our results intuitively present the beam polarization and coherence properties through anisotropic hypersonic turbulence, which can be useful for optical communication in hypersonic turbulent environments.
Features of the contact angle hysteresis at the nanoscale: A molecular dynamics insight
Authors: Mandrolko Viktor , Castanet Guillaume , Burian Sergii , Grosu Yaroslav , Klochko Liudmyla , Lacroix David , Isaiev Mykola
Published: May 2024

Understanding the physics of a three-phase contact line between gas, liquid, and solid is important for numerous applications. At the macroscale, the response of a three-phase contact line to an external force action is often characterized by a contact angle hysteresis, and several models are presented in the literature for its description. Yet, there is still a need for more information about such model applications at the nanoscale. In this study, a molecular dynamics approach was used to investigate the shape of a liquid droplet under an external force for different wetting regimes. In addition, an analytic model for describing the droplet shape was developed. It gives us the possibility to evaluate the receding and advancing wetting angle accurately. With our modeling, we found that the interplay between capillary forces and viscous forces is crucial to characterize the droplet shape at the nanoscale. In this frame, the importance of the rolling movement of the interface between liquid and vapor was pointed out. We also demonstrate that in the range of the external forces when capillary forces are most significant compared to others, hysteresis is well described by the macroscale Cox–Voinov model.
Negative longitudinal resistance of monolayer graphene in the quantum Hall regime
Authors: Kaverzin Alexey A. , Daimon Shunsuke , Kikkawa Takashi , Ohtsuki Tomi , Saitoh Eiji
Published: May 2024

In the quantum Hall regime, the charge current is carried by ideal one-dimensional edge channels where the backscattering is prohibited by topology. This results in the constant potential along the edge of the Hall bar leading to zero 4-terminal longitudinal resistance rxx. Finite scattering between the counter-propagating edge states, when the topological protection is broken, commonly results in rxx > 0. However, a local disorder, if allowing intersection of the edge states, can result in a counter-intuitive scenario when rxx < 0. In this work, we report the observation and a systematic study of such unconventional negative longitudinal resistance seen in an encapsulated monolayer graphene Hall bar device measured in the quantum Hall regime. We supplement our findings with the numerical calculations, which allow us to outline the conditions necessary for the appearance of negative rxx and to exclude the macroscopic disorder (contamination bubble) as the main origin of it.
Tunable temporal dynamics of dipole response in graphene-wrapped core–shell nanoparticles
Authors: Yang Mingliang , Jiang Xinchen , Shalin Alexander S. , Gao Lei
Published: May 2024

The investigation on the temporal dynamics of graphene-wrapped core–shell nanoparticles under the illumination of a Gaussian impulse have been carried out. By altering the graphene layers and the aspect ratio of the core–shell structure, we can adjust the resonant modes into typical cases in regime of terahertz. Accordingly, different scenarios for the temporal evolution are detected, which include two kinds of ultrafast oscillation with exponential decay tendency, pure exponential decay, and Gaussian shape, when the pulse duration of the incident pulse is much shorter than, similar to, and much longer than the localized surface plasmon lifetime. To one's interest, when the coupling between two resonant modes exists, one predicts the long-periodic oscillation, whose period is just the difference between the frequencies of the resonant modes. Hence, the intrinsic properties of the ultrafast oscillation can be hardly influenced by the input signals. Further quantitative calculation demonstrate that the periods of the ultrafast oscillations can be tuned by different physical mechanisms, which are, respectively, based on the self-interacting correction of a single resonance and the strong coupling between the resonant modes in frequency domain. Our results may be applicable in the fields of optical sensors, optical information processing, and other nanophotonic devices.
An analytical study on generation of waves due to the rolling of flexible porous barriers
Authors: Mondal T. K. , Ashok R. , Manam S. R.
Published: May 2024

Complete analytical solution for generation of waves due to rolling of a partially immersed vertical elastic porous plate or a tensioned membrane is obtained. The originally defined boundary value problem in the half-plane has been decomposed first into a couple of flexible porous wave potential problems in the quarter-plane. Then, a pair of integral relations are introduced to establish a connection among the flexible porous wave potentials, solid wave potentials, and auxiliary wave potentials. By utilizing the connection, the flexible porous wave potentials can be determined in terms of the solid and the auxiliary wave potentials. The problems for the latter two types of potentials are easier to handle mathematically than the problems for the flexible porous wave potentials because of the involved structural boundary condition. Thus, the solid and the auxiliary wave potentials have been obtained analytically by the existing methods of solutions. Explicit analytical expressions are derived for the radiated wave amplitudes and velocity potentials. These radiated wave amplitudes are numerically computed and analyzed for different parameters involved. The results are validated with those derived for the problem involving a solid plate.
A novel attention enhanced deep neural network for hypersonic spatiotemporal turbulence prediction
Authors: Du Jiaoxi , Li Xin , Dong Siwei , Liu Ziyang , Chen Gang
Published: May 2024

High Reynolds number turbulent flow of hypersonic vehicles exhibits multi-scale flow structures and non-equilibrium high-frequency characteristics, presenting a significant challenge for accurate prediction. A deep neural network integrated with attention mechanism as a reduced order model for hypersonic turbulent flow is proposed, which is capable of capturing spatiotemporal characteristics from high-dimensional numerical turbulent data directly. The network model leverages encoder–decoder architecture where the encoder captures high-level semantic information of input flow field, Convolutional Long Short-Term Memory network learns low-dimensional characteristic evolution, and the decoder generates pixel-level multi-channel flow field information. Additionally, skip connection structure is introduced at the decoding stage to enhance feature fusion while incorporating Dual-Attention-Block that automatically adjusts weights to capture spatial imbalances in turbulence distribution. Through evaluating the time generalization ability, the neural network effectively learns the evolution of multi-scale high-frequency turbulence characteristics. It enables rapid prediction of high Reynolds number turbulence evolution over time with reasonable accuracy while maintaining excellent computational efficiency.
One Health antimicrobial resistance: stewardship in Australia
Authors: Hardefeldt Laura Y. , Thursky Karin
Published: May 2024

Antimicrobial stewardship (AMS) is promoted as a core set of actions that aim to mitigate the emergence of antimicrobial resistance, but to also ensure safety and quality use of antimicrobials. By improving the appropriate use of antimicrobials we can improve patient care, reduce adverse effects and perhaps slow the emergence of antimicrobial resistance. However, changing behaviour of prescribers is challenging, with barriers and facilitators often common across diverse prescribing groups – doctors and veterinarians. Many of the physical challenges facing prescribers are also shared and lessons can be learned about implementation of interventions between groups. In this article we discuss qualitative and quantitative research, and interventions in AMS, in Australia from a One Health perspective.
Mobilizing climate finance towards agricultural adaptation and nature-based solutions
Authors:   Commercial Agriculture for Smallholders and Agribusiness (CASA), Chapple Alice
Published: May 2024

The Commercial Agriculture for Smallholders and Agribusiness (CASA) Programme aims to drive global investment towards inclusive climate-resilient agri-food systems that increase smallholder incomes. CASA's research component has recently identified the challenges faced in mobilizing climate finance in agriculture, and particularly in climate adaptation, as well as the existence of a funding gap for small and medium-sized agriculture enterprises (agri-SMEs) of around $106 billion (ISF Advisors, 2022). Of particular concern is the minimal funding that would be needed to help smallholder farmers adapt to the challenge of climate change and increase their resilience. Adaptation for smallholder farmers might include investment in drought-resistant seeds, technologies and practices that enable climate-smart agriculture, investment in improved water management, and investment in improved management of food waste, including facilities for storage of crops. Smallholder farmers may also benefit from interventions that protect the natural environment on which they depend (e.g. interventions relating to water supplies, soil quality or soil stabilization), or from activities that augment their incomes through payments for the protection of natural capital. Investment in these nature-based solutions (NbS) can potentially contribute to capital flows to smallholder farmers, even though they are often primarily designed to deliver carbon sequestration benefits to companies or investors seeking a 'net zero' position. This report seeks to answer the following questions, which were explored through interviews with key sectoral stakeholders (principally in Asia): What types of investments in agricultural adaptation and NbS are being made by different categories of investors? What are the barriers to investment in climate adaptation in agriculture and in NbS? What opportunities are emerging for these types of investment? What partnerships are required to help drive capital towards these areas of investment? What evidence is needed to drive capital towards these areas of investment?
A first-principles study of the formation and regulation of the electric double layers at Cu (0 0 1)/mineral oil interfaces
Authors: Ren Yuanyang , Zhang Qiankai , Wang Yang , Li Jianfei , Yan Wenchao , Xu Hao , Cheng Chuanhui , Wu Kai
Published: May 2024

Copper-mineral oil interfaces are key components of oil-impregnated power transformers and are commonly believed to be one of their weak points. The formation of an electric double layer (EDL) at this interface as a result of charge accumulation and transfer is crucial to its insulating properties, but a molecular-level understanding of this phenomenon remains unclear. To understand this fundamental aspect, we have investigated the effect of different EDLs on the electric potential and interfacial potential barrier between copper and mineral oil by using first principle calculations. Based on the calculations, the EDL is shown to reduce the interfacial potential barrier and enhance the diffusion of oil molecules at the interface when the copper side is negatively charged and the mineral oil side is positively charged. In contrast, when the copper side is positively charged and the mineral oil side is negatively charged, the corresponding EDL can increase the interfacial potential barrier and reduce the diffusion of oil molecules at this interface. Our findings shed light on the relationship between the structure of EDLs and their electrical properties in oil-impregnated power transformers.
Spectroscopy of phononic switching of magnetization in the terahertz gap
Authors: Gidding Maxime , Davies Carl S , Stupakiewicz Andrzej , Dessmann Nils , Kirilyuk Andrei
Published: May 2024

All-optical schemes for switching magnetization offer a pathway towards the creation of more advanced data-storage technologies, both in terms of recording speed and energy-efficiency. It has previously been shown that picosecond-long optical pulses with central frequencies ranging between 12 and 30 THz are capable of driving magnetic switching in yttrium-iron-garnet films, provided that the excitation frequency matches the characteristic frequency of longitudinal optical phonons. Here, we explore how the phononic mechanism of magnetic switching in three distinct ferrimagnetic iron-garnet films evolves at optical frequencies below 10 THz, within the so-called terahertz gap. We find that at long wavelengths the magnetic switching rather correlates with phonon modes associated with the substrate. Our results show that the process of phononic switching of magnetization, previously discovered in the mid- to far-infrared spectral range, becomes much more complex at frequencies within the terahertz gap.
Fault diagnosis of driving gear in a battery swapping system based on audio features and SRC-Adaboost
Authors: You Xianglong , Wu Hao , Li Jiacheng , You Xiaowen , Zhang Chi , Yuan Hang
Published: May 2024

Because of electrification conditions, key components of battery swapping systems (BSSs) for electric heavy trucks are always damaged by electric erosion, which presents challenges to the safety and efficiency of high-intensity transportation. Due to the special working conditions of a BSS, the fault diagnosis of its driving gear encounters several issues, including reciprocation motion, low and fluctuating speed, and complicated noises. To solve these problems, audio features, including Mel-frequency cepstral coefficients and Gammatone cepstral coefficients, are extracted from the vibration signals. Then, these features are utilized to construct an original dictionary. Next, based on data augmentation and dictionary learning, a robust dictionary is generated from the original dictionary. Finally, with the robust dictionary, sparse representation-based classification is integrated into AdaBoost to achieve accurate fault diagnosis for the driving gear in BSS. The effectiveness of the fault diagnosis scheme is validated based on the monitoring data of the BSS, and the accuracy of fault diagnosis is 99.17%.
A de-texturing model for enhancing the accuracy of centroid positioning
Authors: Wang Yanqi , Xu Zheng , Wang Xiaodong , He Jiaheng , Ren Tongqun
Published: May 2024

In tasks guided by microvision, extracting centroids is a common method for positioning, which is negatively affected by texture. Here, an attention-related de-texturing model is proposed to eliminate the texture of microparts and preserve accurate edges. A network with an attention module called De-texturing Net is built, in which both the transformer and channel attention modules are included. Considering the importance of texture, the additional factor in loss function is constructed based on the Gram matrix difference between target images and generated images. Results show that De-texturing Net can generate de-texturized images with high Peak Signal to Noise Ratio/SSIM, indicating the similarity between de-texturized and target images. Moreover, for the centroid positioning, the error in de-texturized images is significantly lower than the error in original images. This study helps improve the accuracy of centroid positioning due to the de-texturized images with accurate edges.
Roadmap on data-centric materials science
Authors: Bauer Stefan , Benner Peter , Bereau Tristan , Blum Volker , Boley Mario , Carbogno Christian , Catlow C Richard A , Dehm Gerhard , Eibl Sebastian , Ernstorfer Ralph , Fekete Ádám , Foppa Lucas , Fratzl Peter , Freysoldt Christoph , Gault Baptiste , Ghiringhelli Luca M , Giri Sajal K , Gladyshev Anton , Goyal Pawan , Hattrick-Simpers Jason , Kabalan Lara , Karpov Petr , Khorrami Mohammad S , Koch Christoph T. , Kokott Sebastian , Kosch Thomas , Kowalec Igor , Kremer Kurt , Leitherer Andreas , Li Yue , Liebscher Christian H , Logsdail Andrew J , Lu Zhongwei , Luong Felix , Marek Andreas , Merz Florian , Mianroodi Jaber R , Neugebauer Jörg , Pei Zongrui , Purcell Thomas A R , Raabe Dierk , Rampp Markus , Rossi Mariana , Rost Jan-Michael , Saal James , Saalmann Ulf , Sasidhar Kasturi Narasimha , Saxena Alaukik , Sbailò Luigi , Scheidgen Markus , Schloz Marcel , Schmidt Daniel F , Teshuva Simon , Trunschke Annette , Wei Ye , Weikum Gerhard , Xian R Patrick , Yao Yi , Yin Junqi , Zhao Meng , Scheffler Matthias
Published: May 2024

Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of artificial intelligence and its subset machine learning, has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research.
Construction of sub micro-nano-structured silicon based anode for lithium-ion batteries
Authors: Su Chen , Shodievich Kurbanov Mirtemir , Zhao Yi , Ji Puguang , Zhang Xin , Wang Hua , Zhang Chengwei , Wang Gongkai
Published: May 2024

The significant volume change experienced by silicon (Si) anodes during lithiation/delithiation cycles often triggers mechanical-electrochemical failures, undermining their utility in high-energy-density lithium-ion batteries (LIBs). Herein, we propose a sub micro-nano-structured Si based material to address the persistent challenge of mechanic-electrochemical coupling issue during cycling. The mesoporous Si-based composite submicrospheres (M-Si/SiO2/CS) with a high Si/SiO2 content of 84.6 wt.% is prepared by magnesiothermic reduction of mesoporous SiO2 submicrospheres followed by carbon coating process. M-Si/SiO2/CS anode can maintain a high specific capacity of 740 mAh g−1 at 0.5 A g−1 after 100 cycles with a lower electrode thickness swelling rate of 63%, and exhibits a good long-term cycling stability of 570 mAh g−1 at 1 A g−1 after 250 cycles. This remarkable Li-storage performance can be attributed to the synergistic effects of the hierarchical structure and SiO2 frameworks. The spherical structure mitigates stress/strain caused by the lithiation/delithiation, while the internal mesopores provide buffer space for Si expansion and obviously shorten the diffusion path for electrolyte/ions. Additionally, the amorphous SiO2 matrix not only servers as support for structure stability, but also facilitates the rapid formation of a stable solid electrolyte interphase layer. This unique architecture offers a potential model for designing high-performance Si-based anode for LIBs.
Starch/chitosan nanoparticles bionanocomposite membranes for methylene blue dye removal
Authors: Ilias Hanis Masyithah , Othman Siti Hajar , Shapi’i Ruzanna Ahmad , Yunos Khairul Faezah Md
Published: May 2024

This research aims to develop relatively new membranes from starch biopolymer incorporated with different concentrations (0, 5, 10, 15, 20% w/w of solid starch) of chitosan nanoparticles (CNP) that can be used for water treatment. The membranes were fabricated using the solvent casting method while the CNP was produced using the ionic gelation method. The membranes were characterized in terms of morphology, porosity, water vapor permeability (WVP), and water contact angle. The application of the membranes to treat water was demonstrated on methylene blue solution because methylene blue is a commonly used dye in many industries. It was found that the starch/10% CNP membrane was the optimum membrane for methylene blue dye treatment because the membrane exhibits a smooth surface, high WVP (1.67 × 10−10 g Pa−1 h−1 m−1), high porosity (59.92%), low water contact angle value (44.8°), and resulted in the highest percentage removal of methylene blue (94.0%) after the filtration. After filtration, the starch/10% CNP membrane was still in good condition without breakage. In conclusion, the starch/CNP membranes produced in this study are promising for sustainable and environmentally friendly water treatment, especially for water containing methylene blue dye. This research aligns with current thematic trends in bionanohybrid composite materials utilization, offering innovative solutions for addressing water pollution challenges.
Modulation of polyaniline memristive device switching voltage by nucleotide-free analogue of vitamin B12
Authors: Prudnikov Nikita V , Emelyanov Andrey V , Serenko Maria V , Dereven’kov Ilia A , Maiorova Larissa A , Erokhin Victor V
Published: May 2024

Memristive devices offer essential properties to become a part of the next-generation computing systems based on neuromorphic principles. Organic memristive devices exhibit a unique set of properties which makes them an indispensable choice for specific applications, such as interfacing with biological systems. While the switching rate of organic devices can be easily adjusted over a wide range through various methods, controlling the switching potential is often more challenging, as this parameter is intricately tied to the materials used. Given the limited options in the selection conductive polymers and the complexity of polymer chemical engineering, the most straightforward and accessible approach to modulate switching potentials is by introducing specific molecules into the electrolyte solution. In our study, we show polyaniline (PANI)-based device switching potential control by adding nucleotide-free analogue of vitamin B12, aquacyanocobinamide, to the electrolyte solution. The employed concentrations of this molecule, ranging from 0.2 to 2 mM, enabled organic memristive devices to achieve switching potential decrease for up to 100 mV, thus providing a way to control device properties. This effect is attributed to strong aromatic interactions between PANI phenyl groups and corrin macrocycle of the aquacyanocobinamide molecule, which was supported by ultraviolet-visible spectra analysis.
Dose–toxicity surface histogram-based prediction of radiation dermatitis severity and shape
Authors: Hong Chae-Seon , Park Ye-In , Cho Min-Seok , Son Junyoung , Kim Changhwan , Han Min Cheol , Kim Hojin , Lee Ho , Kim Dong Wook , Choi Seo Hee , Kim Jin Sung
Published: May 2024

Objective. This study aimed to develop a new approach to predict radiation dermatitis (RD) by using the skin dose distribution in the actual area of RD occurrence to determine the predictive dose by grade. Approach. Twenty-three patients with head and neck cancer treated with volumetric modulated arc therapy were prospectively and retrospectively enrolled. A framework was developed to segment the RD occurrence area in skin photography by matching the skin surface image obtained using a 3D camera with the skin dose distribution. RD predictive doses were generated using the dose–toxicity surface histogram (DTH) calculated from the skin dose distribution within the segmented RD regions classified by severity. We then evaluated whether the developed DTH-based framework could visually predict RD grades and their occurrence areas and shapes according to severity. Main results. The developed framework successfully generated the DTH for three different RD severities: faint erythema (grade 1), dry desquamation (grade 2), and moist desquamation (grade 3); 48 DTHs were obtained from 23 patients: 23, 22, and 3 DTHs for grades 1, 2, and 3, respectively. The RD predictive doses determined using DTHs were 28.9 Gy, 38.1 Gy, and 54.3 Gy for grades 1, 2, and 3, respectively. The estimated RD occurrence area visualized by the DTH-based RD predictive dose showed acceptable agreement for all grades compared with the actual RD region in the patient. The predicted RD grade was accurate, except in two patients. Significance. The developed DTH-based framework can classify and determine RD predictive doses according to severity and visually predict the occurrence area and shape of different RD severities. The proposed approach can be used to predict the severity and shape of potential RD in patients and thus aid physicians in decision making.
Biological optimization for hybrid proton-photon radiotherapy
Authors: Li Wangyao , Lin Yuting , Li Harold H , Shen Xinglei , Chen Ronald C , Gao Hao
Published: May 2024

Objective. Hybrid proton-photon radiotherapy (RT) is a cancer treatment option to broaden access to proton RT. Additionally, with a refined treatment planning method, hybrid RT has the potential to offer superior plan quality compared to proton-only or photon-only RT, particularly in terms of target coverage and sparing organs-at-risk (OARs), when considering robustness to setup and range uncertainties. However, there is a concern regarding the underestimation of the biological effect of protons on OARs, especially those in close proximity to targets. This study seeks to develop a hybrid treatment planning method with biological dose optimization, suitable for clinical implementation on existing proton and photon machines, with each photon or proton treatment fraction delivering a uniform target dose. Approach. The proposed hybrid biological dose optimization method optimized proton and photon plan variables, along with the number of fractions for each modality, minimizing biological dose to the OARs and surrounding normal tissues. To mitigate underestimation of hot biological dose spots, proton biological dose was minimized within a ring structure surrounding the target. Hybrid plans were designed to be deliverable separately and robustly on existing proton and photon machines, with enforced uniform target dose constraints for the proton and photon fraction doses. A probabilistic formulation was utilized for robust optimization of setup and range uncertainties for protons and photons. The nonconvex optimization problem, arising from minimum monitor unit constraint and dose-volume histogram constraints, was solved using an iterative convex relaxation method. Main results. Hybrid planning with biological dose optimization effectively eliminated hot spots of biological dose, particularly in normal tissues surrounding the target, outperforming proton-only planning. It also provided superior overall plan quality and OAR sparing compared to proton-only or photon-only planning strategies. Significance. This study presents a novel hybrid biological treatment planning method capable of generating plans with reduced biological hot spots, superior plan quality to proton-only or photon-only plans, and clinical deliverability on existing proton and photon machines, separately and robustly.
Design and characterisation of a minibeam collimator utilising Monte Carlo simulation and a clinical linear accelerator
Authors: Carver Antony , Baker Sam , Dumbill Andrew , Horton Steven , Green Stuart
Published: May 2024

Objective. Spatially fractionated radiotherapy is showing promise as a treatment modality. Initial focus was on beams of photons at low energy produced from a synchrotron but more recently research has expanded to include applications in proton therapy. Interest in photon beams remains and this is the focus of this paper Approach. This study presents a 3D printed tungsten minibeam collimator intended to produce peak-to-valley dose ratios (PVDR) of between seven and ten with a 1 MV, bremsstrahlung generated, photon beam. The design of the collimator is motivated by a Monte Carlo study estimating the PVDR for different collimator designs at different energies. This collimator was characterised on a clinical linear accelerator (Elekta VersaHD) as well as an orthovoltage unit. Main results. The performance of the fabricated collimator was measured on Elekta VersaHD running in unflattened mode with a 6 MV beam. On the Elekta VersaHD units the PVDR was measured to be between approximately 1.5 and 2.0 at 3 cm deep. For measurements with the orthovoltage unit PVDRs of greater than 10 were observed at a depth of 4 cm. Significance. The results confirmed that the predictions from simulation could be reproduced on linear accelerators currently in clinical usage, producing PVDRs between 2–2.5. Using the model to predict PVDRs using 1 MV photon beams, the threshold considered to produce enhanced normal tissue dose tolerance (

>

7) was surpassed. This suggests the possibility of using such techniques with versions of existing Linac technology which have been modified to operate at low energy and high beam currents.
Effect of dual dispersion of carbon fiber and silica nanoparticles on recovery performance of shape memory epoxy
Authors: Yadav Avadesh , Das Sreetam , Badardinni Rushikethu , Kumar Satish , Kumar Abhishek
Published: May 2024

Shape memory polymers are utilized in diverse fields, including deployable structures and components, owing to their advantageous properties like low density, cost-effectiveness, and ease of processing. The current study investigates the effect of dual dispersion of carbon fibers (CF) and silica nanoparticles (SN) on the recovery performance of shape memory epoxy composites. CF (0.25 wt.%) reinforced epoxy composite, SN (0.25 wt.%) reinforced epoxy composite, and dual (CF and SN 0.25 wt.% each) dispersed epoxy composite were developed using magnetic stirring and ultrasonic mixing to study the mechanical properties and shape memory behaviour. Flexural strength, tensile strength and fracture toughness of pristine epoxy was found to be 134.38, 52.15 MPa and 1.91 MPa∙m1/2, respectively. The addition of CF resulted in a flexural strength of 135.70 MPa and a tensile strength of 53.01 MPa, while the incorporation of SN led to a flexural and tensile strength of 138.40 and 53.69 MPa, respectively. The fracture toughness of composites after adding CF and SN was found to be 2.22 and 2.39 MPa∙m1/2, respectively. With dual dispersion, the flexural strength of 139.82 MPa, tensile strength of 54.64 MPa, and fracture toughness of 2.75 MPa∙m1/2 were achieved. Dual dispersion has shown improved mechanical properties compared to single dispersion. The introduction of CF slightly decreased the shape fixity ratio (Rf
) and shape recovery ratio (Rr
) of the pristine epoxy from 98.67% and 96.62% to 96.67% and 95.15%, respectively. Similarly, the addition of SN further reduced these ratios to 98.00% and 91.83%, respectively. With a dual dispersion approach Rf
and Rr
were observed to be about 97.33% and 93.83%, respectively. The addition of fillers led to a reduction in Rf
and Rr
due to inhibition of polymeric chains, resulting in partial shape recovery. However, recovery time improved from 28 to 23 and 26 s with addition of CF and SN, respectively, in epoxy. With dual dispersion, a speedy recovery was achieved with a recovery time of 21 s. The findings of this study demonstrate the potential of dual dispersed fillers to improve the mechanical and shape memory properties of epoxy, which could find applications in the smart materials and structural engineering.
Development of novel magnetorheological dampers with low-speed sensitivity for flying car suspensions
Authors: Jiang Lan , Gong Xinglong , Hu Tao , Pan Liyan , Gong Ning , Sun Shuaishuai
Published: May 2024

As urban traffic environments continue to grow in complexity, there is an urgent need for a versatile mode of transportation that seamlessly transitions between terrestrial and aerial mobility. In conventional magnetorheological damper (CMRD), the magnetorheological fluid flowing through the narrow annular gap between the piston and cylinder in CMRD results in a damping force directly proportional to velocity. As velocity increases, the damping force rises sharply, posing a significant risk to the vehicle’s mechanical structure and passenger safety. This velocity sensitivity restricts their applications primarily to standard commercial vehicle suspension systems. They face significant challenges when it comes to high-speed impact scenarios. To overcome this limitation, enhance the shock-absorbing capacity of flying cars, ensure passenger safety, and improve passenger comfort during the landing phase, this study introduces a novel magnetorheological damper (NMRD) with unique internal channel structure embedded in a circular permanent magnet. In road travel mode, NMRD maintains a wide dynamic range. During high-speed impact landing, when the impact force exceeds the threshold, the pressure relief channel opens, effectively reducing the peak impact force. This feature greatly expands the application range of magnetorheological dampers. The researches included simulations of the electromagnetic induction phenomenon within the piston, The pressure relief damping force inside the NMRD valve was accurately measured by using material testing system, the peak force and peak acceleration experienced by the two dampers during impact were tested using a dedicated drop hammer apparatus. These tests demonstrate that the NMRD exhibits superior impact resistance performance compared to CMRD. This highlights the promising potential for the NMRD’s application within the suspension systems of flying cars.