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Maintaining the surface structure stability of LiCoO 2 (LCO) during rapid charge-discharge processes (>5C) and under high-voltage conditions (>4.2 V) is challenging due to interfacial side reactions, cobalt dissolution, and oxygen redox activity at deeply delithiated states, all of which contribute to performance degradation. Herein, different from traditional surface coating methods, we report a water-mediated strategy that modifies the surface architecture of LCO, creating a passivating layer to inhibit surface degradation and enhance cycling stability under fast charging conditions. The surface etching of LCO by H 2 O is accompanied by a concurrent Li + /H + cation exchange, which passivates surface oxygen with H + ions, thereby enhancing both the hydrophobicity and structural stability. Consequently, the modified LCO exhibits superior capacity retention, which is 2.5 times that of the pristine LCO, after 100 cycles at a current density of 1000 mA g -1 (∼6C at 4.5 V). Even at an elevated temperature of 45 °C, it maintains impressive cycling stability at a current density of 500 mA g -1 (∼3C), as demonstrated in practical full-cell configurations. Investigation with multiple samples confirmed that the water-mediated strategy demonstrated broad applicability. We emphasize that the water-mediated modification of the surface architecture on cathode materials offers significant insights into enhancing the stability of high-energy-density lithium-ion batteries (LIBs).

Mechanical forces are essential for regulating dynamic changes in cellular activities. A comprehensive understanding of these forces is imperative for unraveling fundamental mechanisms. Here, we develop a microprobe capable of facilitating the measurement of biological forces up to nanonewton levels in living cells. This probe is designed by coating the core of anatase titania particles with amorphous titania and silica shells and an upconversion nanoparticles (UCNPs) layer. Leveraging both antireflection and ion resonance effects from the shells, the optically trapped probe attains a maximum lateral optical trap stiffness of 14.24 pN μm -1 mW -1 , surpassing the best reported value by a factor of 3. Employing this advanced probe in a photonic force microscope, we determine the elasticity modulus of mitotic HeLa cells as 1.27 ± 0.3 kPa. Nanonewton probes offer the potential to explore 3D cellular mechanics with unparalleled precision and spatial resolution, fostering a deeper understanding of the underlying biomechanical mechanisms.

Purpose: The current deep learning-based dose prediction methods only predict one dose distribution. If the predicted dose is inaccurate, no additional options can be selected. To overcome this limitation, we propose a novel dose prediction method called "dose-band prediction," which provides a spectrum of predicted dose distributions for planning and quality assurance (QA) purposes., Material and Methods: We utilized Upper/Lower-band losses in 3D neural networks to establish the Upper/Lower-band models (UBM/LBM). The maximum/minimum rational dose predicted in UBM/LBM defined the ideal dose spectrum for each voxel. We enrolled 104 nasopharyngeal carcinoma cases with tomotherapy (dataset 1), 54 cervical carcinoma cases with IMRT (dataset 2), and 37 cervical carcinoma cases with VMAT (dataset 3) in the study. Moreover, a dose band-based auto planning (Auto-plan dose-band ) attempt was carried out in dataset 3, compared with the MSE model (Auto-plan MSE )., Results: The UBM/LBM doses tend to be higher/lower than the clinical dose, forming a predicted dose spectrum. The Middle-line dose represents the average of the Upper/Lower-band, which was consistent with the clinical dose. The mean differences of the planning target volumes (PTVs) and organs at risk (OARs) for the Upper-band, Middle-line, and Lower-band in Dataset 1 were 3.66 %, -0.40 %, and -4.48 % in Dataset 2, they were 2.40 %, -1.62 %, and -5.57 %; in Dataset 3, they were 2.18 %, -0.59 %, and -3.31 %. When PTVs meet prescription, the mean difference between Auto-plan dose-band and Auto-plan MSE in OARs was -2.67 %., Conclusion: The dose-band prediction successfully predicted a spectrum of doses, making auto-planning and QA flexible and high quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: The field of artificial intelligence (AI)-based patient-specific quality assurance (PSQA) for volumetric modulated arc therapy (VMAT) faces challenges in terms of developing general models across institutions due to the prevalence of multi-institution data collection and multivariate heterogeneity. Building a general model that is capable of handling diverse multi-institution data is critical for enabling large-scale integration and analysis., Purpose: This study aims to develop a star generative adversarial network (StarGAN) and transformer-based hybrid classification-regression PSQA framework to address unification of heterogeneous data from different institutions., Methods: A StarGAN and transformer-based hybrid classification-regression model was developed as a general PSQA framework to predict gamma passing rates (GPRs) and classify quality assurance (QA) results as "Pass" or "Fail" at multiple institutions. A total of 1815 VMAT plans were collected from eight institutions to develop the general PSQA framework and perform clinical commissioning and implementation. Among them, 20 independent clinical plans from each of eight institutions, for a total of 160 plans, were used for the clinical commissioning, and 205 new clinical plans from eight institutions were used for clinical implementation., Results: For the 3%/3, 3%/2, and 2%/2 mm gamma criteria, the sensitivity of the proposed PSQA framework with pretraining was 90.13%, 92.03%, and 95.84%, respectively, while the specificity was 76.01%, 76.12%, and 85.34%, respectively. The mean absolute errors (MAEs) of the proposed PSQA framework with pretraining were 1.36%, 2.37%, and 3.96%, respectively, while the root-mean-square errors (RMSEs) were 2.31%, 3.89%, and 5.17%, respectively. The results demonstrated visible improvement at multiple institutions. For clinical commissioning, the deviations between the predicted and measured results were all within 3% for 3%/3 and 3%/2 mm at eight institutions. For clinical implementation, all failure plans were correctly identified by the proposed PSQA framework., Conclusions: The general PSQA framework enables diverse clinical data sources to be handled to achieve enhanced model performance and generalizability, and provides a solution to the unification of heterogeneous data from different institutions to construct robust QA models. This approach can be clinically deployed for VMAT QA., (© 2024 American Association of Physicists in Medicine.)

Surface engineering of BiVO 4 photoanodes is effective and feasible for photoelectrochemical (PEC) water splitting. To achieve superior PEC performance, however, more than one surface engineering method is usually indispensable, for which a positive synergistic effect is vital and thus highly desired. Herein, it is reported that the incorporation of borate moieties into ultrathin p-type NiO x catalysts can induce the reconfiguration of surface catalytic sites to form new highly active species, in addition to enhanced fast charge separation and transfer. The photocurrent density of BiVO 4 photoanodes is enhanced from 1.49 to 5.76 mA cm -2 at 1.23 V versus reversible hydrogen electrode (RHE) under AM 1.5G illumination, which is achieved by successive modifications of NiO x and borate moieties. It is found that BO 3 groups anchored to Ni atoms by replacing the surface hydroxyl sites of NiO x catalysts not only increase the relative ratio of Ni 3+ species to facilitate charge transfer but also provide efficient active sites for H 2 O molecule adsorption and oxidation reactions. This work demonstrates the positive synergistic effect of these two surface engineering methods and provides an effective pathway to construct highly efficient and stable photoanodes for PEC water splitting., (© 2024 Wiley‐VCH GmbH.)

Discoveries of above-room-temperature intrinsic ferromagnetism in two-dimensional (2D) van der Waals (vdW) materials offer a platform for studying fundamental 2D magnetism and spintronic devices, especially the recently discovered above-room-temperature 2D vdW Fe 3 GaTe 2 (FGaT). However, the magnetic mechanism in FGaT remains elusive. Here, a detailed investigation using magnetic force microscopy on the thickness-dependent magnetic behavior of FGaT single crystals is reported. The Heisenberg exchange interaction constant ( J ) at room temperature is determined to be 1.32836 × 10 -12 J/m. Our study combining angle-resolved photoemission spectroscopy and density functional theory suggests that the high Curie temperature in FGaT is attributed to the shift of the localized Fe d band toward the Fermi level as well as the enhanced magnetic exchange effect due to the strong itinerant ability of Fe. This work sheds light on the understanding of magnetism in FGaT and provides a promising platform to investigate the mechanisms of 2D magnetic materials.

Background: Pulmonary embolism (PE) is life-threatening and requires timely and accurate diagnosis, yet current imaging methods, like computed tomography pulmonary angiography, present limitations, particularly for patients with contraindications to iodinated contrast agents. We aimed to develop a quantitative texture analysis pipeline using machine learning (ML) based on non-contrast thoracic computed tomography (CT) scans to discover intensity and textural features correlated with regional lung perfusion (Q) physiology and pathology and synthesize voxel-wise Q surrogates to assist in PE diagnosis., Methods: We retrospectively collected 99m Tc-labeled macroaggregated albumin Q-SPECT/CT scans from patients suspected of PE, including an internal dataset of 76 patients (64 for training, 12 for testing) and an external testing dataset of 49 patients. Quantitative CT features were extracted from segmented lung subregions and underwent a two-stage feature selection pipeline. The prior-knowledge-driven preselection stage screened for robust and non-redundant perfusion-correlated features, while the data-driven selection stage further filtered features by fitting ML models for classification. The final classification model, trained with the highest-performing PE-associated feature combination, was evaluated in the testing cohorts based on the Area Under the Curve (AUC) for subregion-level predictability. The voxel-wise Q surrogate was then synthesized using the final selected feature maps (FMs) and model score maps (MSMs) to investigate spatial distributions. The Spearman correlation coefficient (SCC) and Dice similarity coefficient (DSC) were used to assess the spatial consistency between FMs or MSMs and Q-SPECT scans., Results: The optimal model performance achieved an AUC of 0.863 during internal testing and 0.828 on the external testing cohort. The model identified a combination containing 14 intensity and textural features that were non-redundant, robust, and capable of distinguishing between high- and low-functional lung regions. Spatial consistency assessment in the internal testing cohort showed moderate-to-high agreement between MSMs and reference Q-SPECT scans, with median SCC of 0.66, median DSCs of 0.86 and 0.64 for high- and low-functional regions, respectively., Conclusions: This study validated the feasibility of using quantitative texture analysis and a data-driven ML pipeline to generate voxel-wise lung perfusion surrogates, providing a radiation-free, widely accessible alternative to functional lung imaging in managing pulmonary vascular diseases., Clinical Trial Number: Not applicable., (© 2024. The Author(s).)

Carrier dynamics is crucial in semiconductors, and it determines their conductivity, response time, and overall functionality. In flat bands (FBs), carriers with high effective masses are predicted to host unconventional transport properties. The FBs usually overlap with other trivial energy bands, however, making it difficult to accurately distinguish their carrier dynamics. In this paper, we have investigated the flat-band carrier dynamics of excited electrons in Nb 3 Cl 8 , which hosts ideal nonoverlapping FBs near the Fermi level. The optical transition between Hubbard bands is abnormally weakened, exhibiting weak interband absorption and its related slow photoresponse with a time constant of ∼120 s, which are associated with flat-band Mottness-induced large electron effective mass and parity-forbidden transitions. Besides, the localized states created by chlorine vacancies also act as trapping centers for carriers with a time constant of ∼600 s, which are similar to those of the compact localized states of the FB, making the relaxation behavior even more extraordinary. The presence and impacts of atomic defects are confirmed experimentally and theoretically. This work has revealed the abnormal flat-band carrier dynamics of Nb 3 Cl 8 , which is essential for understanding the optical, electrical, and thermal transport properties of flat-band materials.

We present the implementation of the Hubbard ( U ) and Hund ( J ) corrected Density Functional Theory (DFT + U + J ) functionality in the Quickstep program, which is part of the CP2K suite. The tensorial and Löwdin subspace representations are implemented and compared. Full analytical DFT + U + J forces are implemented and benchmarked for the tensorial and Löwdin representations. We also present the implementation of the recently proposed minimum-tracking linear-response method that enables the U and J parameters to be calculated on first-principles basis without reference to the Kohn-Sham eigensystem. These implementations are benchmarked against recent results for different materials properties including DFT + U band gap opening in NiO, the relative stability of various polaron distributions in TiO 2 , the dependence of the calculated TiO 2 band gap on + J corrections, and, finally, the role of the + U and + J corrections for the computed properties of a series of the hexahydrated transition metals. Our implementation provides results consistent with those already reported in the literature from comparable methods. We conclude the contribution with tests on the influence of the Löwdin orthonormalization on the occupancies, calculated parameters, and derived properties.

Confined motions in complex environments are ubiquitous in microbiology. These situations invariably involve the intricate coupling between fluid flow, soft boundaries, surface forces, and fluctuations. In the present study, such a coupling is investigated using a method combining holographic microscopy and advanced statistical inference. Specifically, the Brownian motion of soft micrometric oil droplets near rigid walls is quantitatively analyzed. All the key statistical observables are reconstructed with high precision, allowing for nanoscale resolution of local mobilities and femtonewton inference of conservative or nonconservative forces. Strikingly, the analysis reveals the existence of a novel, transient, but large, soft Brownian force . The latter might be of crucial importance for microbiological and nanophysical transport, target finding, or chemical reactions in crowded environments, and hence the whole life machinery., Competing Interests: Competing interests statement:The authors declare no competing interest.

Various factors such as mechanical trauma, chemical trauma, local ischemia, and inflammation can impair voltage-gated sodium channels (Nav) in neurons. These impairments lead to a distinctive leftward shift in the activation and inactivation curves of voltage-gated sodium channels. The resulting sodium channel impairments in neurons are known to affect firing patterns, which play a significant role in neuronal activities within the nervous system. However, the underlying dynamic mechanism for the emergence of these firing patterns remains unclear. In this study, we systematically investigated the effects of sodium channel dysfunction on individual neuronal dynamics and firing patterns. By employing codimension-1 bifurcation analysis, we revealed the underlying dynamical mechanism responsible for the generation of different firing patterns. Additionally, through codimension-2 bifurcation analysis, we theoretically determined the distribution of firing patterns on different parameter planes. Our results indicate that the firing patterns of impaired neurons are regulated by multiple parameters, with firing pattern transitions caused by the degree of sodium channel impairment being more diverse than those caused by the ratio of impaired sodium channel and current. Furthermore, we observed that the firing pattern of tonic firing is more likely to be the norm in impaired sodium channel neurons, providing valuable insights into the signaling of impaired neurons. Overall, our findings highlight the intricate relationships among sodium channel impairments, neuronal dynamics, and firing patterns, shedding light on the impact of disruptions in ion concentration gradients on neuronal function., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

Monoatomic-layered carbon materials, such as graphene 1 and amorphous monolayer carbon 2,3 , have stimulated intense fundamental and applied research owing to their unprecedented physical properties and a wide range of promising applications 4,5 . So far, such materials have mainly been produced by chemical vapour deposition, which typically requires stringent reaction conditions compared to solution-phase synthesis. Herein, we demonstrate the solution preparation of free-standing nitrogen-doped amorphous monolayer carbon with mixed five-, six- and seven-membered (5-6-7-membered) rings through the polymerization of pyrrole within the confined interlayer cavity of a removable layered-double-hydroxide template. Structural characterizations and first-principles calculations suggest that the nitrogen-doped amorphous monolayer carbon was formed by radical polymerization of pyrrole at the α, β and N sites subjected to confinement of the reaction space, which enables bond rearrangements through the Stone-Wales transformation. The spatial confinement inhibits the C-C bond rotation and chain entanglement during polymerization, resulting in an atom-thick continuous amorphous layer with an in-plane π-conjugation electronic structure. The spatially confined radical polymerization using solid templates and ion exchange strategy demonstrates potential as a universal synthesis approach for obtaining two-dimensional covalent networks, as exemplified by the successful synthesis of monolayers of polythiophene and polycarbazole., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Photocatalysis and photoelectrocatalysis are promising ways in the utilization of solar energy. To address the low efficiency of photocatalysts and photoelectrodes, in-depth understanding of their catalytic mechanism is in urgent need. Recently, polaron is considered as an influential factor in catalysis, which brings researchers a new approach to modify photocatalysts and photoelectrodes. In this review, brief introduction of polaron is given first, followed by which models and recent experimentally observations of polarons are reviewed. Studies about roles of polarons in photocatalysis and photoelectrocatalysis are listed in order to provide some inspiration in exploring the mechanism and improving the efficiency of photocatalysis and photoelectrocatalysis., (© 2023 The Authors. Advanced Science published by Wiley‐VCH GmbH.)

Flexible electronic devices extended abilities of humans to perceive their environment conveniently and comfortably. Among them, flexible magnetic field sensors are crucial to detect changes in the external magnetic field. State-of-the-art flexible magnetoelectronics do not exhibit low detection limit and large working range simultaneously, which limits their application potential. Herein, a flexible magnetic field sensor possessing a low detection limit of 22 nT and wide sensing range from 22 nT up to 400 mT is reported. With the detection range of seven orders of magnitude in magnetic field sensor constitutes at least one order of magnitude improvement over current flexible magnetic field sensor technologies. The sensor is designed as a cantilever beam structure accommodating a flexible permanent magnetic composite and an amorphous magnetic wire enabling sensitivity to low magnetic fields. To detect high fields, the anisotropy of the giant magnetoimpedance effect of amorphous magnetic wires to the magnetic field direction is explored. Benefiting from mechanical flexibility of sensor and its broad detection range, its application potential for smart wearables targeting geomagnetic navigation, touchless interactivity, rehabilitation appliances, and safety interfaces providing warnings of exposure to high magnetic fields are explored., (© 2023 The Authors. Advanced Science published by Wiley‐VCH GmbH.)

Dispersionless flat bands (FBs) in momentum space, given rise to electron destructive interference in frustrated lattices, offer opportunities to enhance electronic correlations and host exotic many-body phenomena, such as Wigner crystal, fractional quantum hall state, and superconductivity. Despite successes in theory, great challenges remain in experimentally realizing FBs in frustrated lattices due to thermodynamically structural instability. Here, the observation of electronic FB in a potassium distorted colouring triangle (DCT) lattice is reported, which is supported on a blue phosphorene-gold network. It is verified that the interaction between potassium and the underlayer dominates and stabilizes the frustrated structures. Two-dimensional electron gas is modulated by the DCT lattice, and in turn results in a FB dispersion due to destructive quantum interferences. The FB exhibits suppressed bandwidth with high density of states, which is directly observed by scanning tunneling microscopy and confirmed by the first-principles calculation. This work demonstrates that DCT lattice is a promising platform to study FB physics and explore exotic phenomena of correlation and topological matters., (© 2023 The Authors. Advanced Science published by Wiley‐VCH GmbH.)

Combinations of phosphorus with main group III, IV, and V elements are theoretically predicted to generate 2D binary phosphides with extraordinary properties and promising applications. However, experimental synthesis is significantly lacking. Here, a general approach for preparing 2D binary phosphides is reported using single crystalline surfaces containing the constituent element of target 2D materials as the substrate. To validate this, SnP 3 and BiP, representing typical 2D binary phosphides, are successfully synthesized on Cu 2 Sn and bismuthene, respectively. Scanning tunneling microscopy imaging reveals a hexagonal pattern of SnP 3 on Cu 2 Sn, while α-BiP can be epitaxially grown on the α-bismuthene domain on Cu 2 Sb. First-principles calculations reveal that the formation of SnP 3 on Cu 2 Sn is associated with strong interface bonding and significant charge transfer, while α-BiP interacts weakly with α-bismuthene so that its semiconducting property is preserved. The study demonstrates an attractive avenue for the atomic-scale growth of binary 2D materials via substrate phase engineering., (© 2024 Wiley‐VCH GmbH.)

Miniaturized on-chip spectrometers with small footprints, lightweight, and low cost are in great demand for portable optical sensing, lab-on-chip systems, and so on. Such miniaturized spectrometers are usually based on engineered spectral response units and then reconstruct unknown spectra with algorithms. However, due to the limited footprints of computational on-chip spectrometers, the recovered spectral resolution is limited by the number of integrated spectral response units/filters. Thus, it is challenging to improve the spectral resolution without increasing the number of used filters. Here we present a computational on-chip spectrometer using electrochromic filter-based computational spectral units that can be electrochemically modulated to increase the efficient sampling number for higher spectral resolution. These filters are directly integrated on top of the photodetector pixels, and the spectral modulation of the filters results from redox reactions during the dual injection of ions and electrons into the electrochromic material. We experimentally demonstrate that the spectral resolution of the proposed spectrometer can be effectively improved as the number of applied voltages increases. The average difference of the peak wavelengths between the reconstructed and the reference spectra decreases from 1.61 nm to 0.29 nm. We also demonstrate the proposed spectrometer can be worked with only four or two filter units, assisted by electrochromic modulation. In addition, we also demonstrate that the electrochromic filter can be easily adapted for hyperspectral imaging, due to its uniform transparency. This strategy suggests a new way to enhance the performance of miniaturized spectrometers with tunable spectral filters for high resolution, low-cost, and portable spectral sensing, and would also inspire the exploration of other stimulus responses such as photochromic and force-chromic, etc, on computational spectrometers., (© 2024. The Author(s).)

Cavity optomechanical systems have enabled precision sensing of magnetic fields, by leveraging the optical resonance-enhanced readout and mechanical resonance-enhanced response. Previous studies have successfully achieved mass-produced and reproducible microcavity optomechanical magnetometry (MCOM) by incorporating Terfenol-D thin films into high-quality (Q) factor whispering gallery mode (WGM) microcavities. However, the sensitivity was limited to 585 pT Hz -1/2 , over 20 times inferior to those using Terfenol-D particles. In this work, we propose and demonstrate a high-sensitivity and mass-produced MCOM approach by sputtering a FeGaB thin film onto a high-Q SiO 2 WGM microdisk. Theoretical studies are conducted to explore the magnetic actuation constant and noise-limited sensitivity by varying the parameters of the FeGaB film and SiO 2 microdisk. Multiple magnetometers with different radii are fabricated and characterized. By utilizing a microdisk with a radius of 355 μm and a thickness of 1 μm, along with a FeGaB film with a radius of 330 μm and a thickness of 1.3 μm, we have achieved a remarkable peak sensitivity of 1.68 pT Hz -1/2 at 9.52 MHz. This represents a significant improvement of over two orders of magnitude compared with previous studies employing sputtered Terfenol-D film. Notably, the magnetometer operates without a bias magnetic field, thanks to the remarkable soft magnetic properties of the FeGaB film. Furthermore, as a proof of concept, we have demonstrated the real-time measurement of a pulsed magnetic field simulating the corona current in a high-voltage transmission line using our developed magnetometer. These high-sensitivity magnetometers hold great potential for various applications, such as magnetic induction tomography and corona current monitoring., (© 2024. The Author(s).)

With advantages such as low cost, high stability, and ease of production, visible light photocatalytic C3N4 with a unique microscopic layered structure holds significant potential for development. However, its hydrogen production efficiency remains low due to the pronounced recombination of photo-generated charge carriers and limited surface reaction sites. Normally, the photocatalytic performance of C3N4 can be enhanced by loading noble metals with surface plasmon resonance. It is worth noting that the size of noble metal nanoparticles has a great influence on photocatalytic performance. In this study, accurate controlling of the size and distribution of Au nanoparticles was achieved on the surface of C3N4 by introducing amino groups to improve photocatalytic performance. Results show that uniformly distributed Au nanoparticles in the range of 2-6 nm can be obtained on C3N4 with a remarkable enhancement of hydrogen production efficiency, which is about 114 times the property of pure C3N4. The small-sized and uniformly distributed Au nanoparticles can provide more reaction sites and increase the separation of photo-generated charge carriers, in turn improving Au/NH3-C3N4 photocatalytic hydrogen release rate to 6.85 mmol g-1 h-1. This work offers a facile way to enhance photocatalytic performance by controlling the size of metal nanoparticles on C3N4 precisely., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

Determining the stability of complex phases in HfO 2 is fundamental to advancing its development and application as ferroelectric material. However, there is ongoing debate regarding whether the ferroelectric phase of HfO 2 originates from the orthorhombic phase or the rhombohedral one. Using first-principles calculations with symmetry group and phonon structure analysis, we have derived multiple phase transitions and ferroelectric switching pathways for the rhombohedral phase, and analyzed their static and dynamic stability. The results indicate that the R 3 m phase, characterized by imaginary frequencies, is a metastable structure that spontaneously transitions to the tetragonal one through multiple pathways. Although the R 3 phase lacks imaginary frequencies, the high formation energy due to internal stress leads to all its ferroelectric switching pathways decaying to lower energy orthorhombic or tetragonal phases. Additionally, different Zr distributions in Hf 0.5 Zr 0.5 O 2 disrupt the spatial group symmetry of the R 3 phase, causing it to spontaneously transition to orthorhombic or monoclinic phases. Consequently, both the phase stability and ferroelectric cycling endurance of the rhombohedral phase are inferior to those of the orthorhombic phase for practical applications. These findings are crucial for experimentally determining the phase structure of HfO 2 and further developing its ferroelectric mechanisms and potential.

The development of hydrogen technologies is at the heart of a green economy. As prerequisite for implementation of hydrogen storage, active and stable catalysts for (de)hydrogenation reactions are needed. So far, the use of precious metals associated with expensive costs dominates in this area. Herein, we present a new class of lower-cost Co-based catalysts (Co-SAs/NPs@NC) in which highly distributed single-metal sites are synergistically combined with small defined nanoparticles allowing efficient formic acid dehydrogenation. The optimal material with atomically dispersed CoN 2 C 2 units and encapsulated 7-8 nm nanoparticles achieves an excellent gas yield of 1403.8 mL·g -1 ·h -1 using propylene carbonate as solvent, with no activity loss after 5 cycles, which is 15 times higher than that of the commercial Pd/C. In situ analytic experiments show that Co-SAs/NPs@NC enhances the adsorption and activation of the key intermediate monodentate HCOO*, thereby facilitating the following C-H bond breaking, compared to related single metal atom and nanoparticle catalysts. Theoretical calculations show that the integration of cobalt nanoparticles elevates the d-band center of the Co single atoms as the active center, which consequently enhances the coupling of the carbonyl O of the HCOO* intermediate to the Co centers, thereby lowering the energy barrier., (© 2024. The Author(s).)

Magnetic skyrmions are swirl-like spin configurations that present topological properties, which have great potential as information carriers for future high-density and low-energy-consumption devices. The optimization of skyrmion-hosting materials that can be integrated with semiconductor-based circuits is the primary challenge for their industrialization. Two-dimensional van der Waals ferromagnets are emerging materials that have excellent carrier mobility and compatibility with integrated circuits, making them an ideal candidate for spintronic devices. Here, we report the realization of skyrmions at above room temperature in the 2D ferromagnet Fe 3 GaTe 2 . The thickness tunability of their skyrmion size and the formation of the skyrmion lattice are revealed. Furthermore, we demonstrate that the skyrmions can be moved by a low-density current at room temperature, together with an apparent skyrmion Hall effect, which is consistent with our quantitative micromagnetic simulation. Our work offers a promising 2D material platform for harnessing magnetic skyrmions in practical device applications.

Utilizing softly confined self-assembly at the water surface represents a promising approach for the fabrication of two-dimensional molecular monolayers (2D MMs), which have predominantly been concentrated on amphiphilic organic compounds before. Herein, we introduce a straightforward method termed "water surface-assisted molecular deposition (WSAMD)" to organize nonamphiphilic molecules into dense monolayers with high reproducibility. To underscore the versatility and merit of this methodology in the field of supramolecular electronics, we have successfully fabricated a range of defect-free, uniform semiconducting polymer monolayers, featuring a thickness reflective of molecular architectures. The charge carrier mobility could reach 0.05 cm 2 V -1 s -1 for holes and 3.5 × 10 -4 cm 2 V -1 s -1 for electrons, respectively, in p-type and n-type polymeric monolayers when tested as the active layer in field-effect transistors. Furthermore, in situ polymerization reactions can be exploited to generate conductive monolayers of macromolecules such as polybenzylaniline (PBnANI) and polypyrrole (PPy), where PBnANI monolayers exhibit channel length-dependent conductivity, up to 0.37 S cm -1 . The advent of the WSAMD method heralds a significant leap forward in the advancement of molecular 2D materials, catalyzing new avenues of exploration within material chemistry.

We report the first search for the elastic scatterings between cosmic-ray boosted sub-MeV dark matter (DM) and electrons in the PandaX-4T liquid xenon experiment. Sub-MeV DM particles can be accelerated by scattering with electrons in the cosmic rays and produce detectable electron recoil signals in the detector. Using the commissioning data from PandaX-4T of 0.63  tonne·year exposure, we set new constraints on DM-electron scattering cross sections for DM masses ranging from 10  eV/c^{2} to 3  keV/c^{2}.

Structural topology and symmetry of a two-dimensional (2D) network play pivotal roles in defining its electrical properties and functionalities. Here, a binary buckled honeycomb lattice with C 3v symmetry, which naturally hosts topological Dirac fermions and out-of-plane polarity, is proposed. It is successfully achieved in a group IV-V compound, namely monolayer SiP epitaxially grown on Ag(111) surface. Combining first-principles calculations with angle-resolved photoemission spectroscopy, the degeneration of the Dirac nodal lines to points due to the broken horizonal mirror symmetry is elucidated. More interesting, the SiP monolayer manifests metallic nature, which is mutually exclusive with polarity in conventional materials. It is further found that the out-of-plane polarity is strongly suppressed by the metallic substrate. This study not only represents a breakthrough of realizing intrinsic polarity in 2D metallic material via ingenious design but also provides a comprehensive understanding of the intricate interplay of many exotic low-dimensional quantum phenomena., (© 2024 Wiley‐VCH GmbH.)

Purpose: The formulation and optimization of radiation therapy plans are complex and time-consuming processes that heavily rely on the expertise of medical physicists. Consequently, there is an urgent need for automated optimization methods. Recent advancements in reinforcement learning, particularly deep reinforcement learning (DRL), show great promise for automating radiotherapy planning. This review summarizes the current state of DRL applications in this field, evaluates their effectiveness, and identifies challenges and future directions., Methods: A systematic search was conducted in Google Scholar, PubMed, IEEE Xplore, and Scopus using keywords such as "deep reinforcement learning", "radiation therapy", and "treatment planning". The extracted data were synthesized for an overview and critical analysis., Results: The application of deep reinforcement learning in radiation therapy plan optimization can generally be divided into three categories: optimizing treatment planning parameters, directly optimizing machine parameters, and adaptive radiotherapy. From the perspective of disease sites, DRL has been applied to cervical cancer, prostate cancer, vestibular schwannoma, and lung cancer. Regarding types of radiation therapy, it has been used in HDRBT, IMRT, SBRT, VMAT, GK, and Cyberknife., Conclusions: Deep reinforcement learning technology has played a significant role in advancing the automated optimization of radiation therapy plans. However, there is still a considerable gap before it can be widely applied in clinical settings due to three main reasons: inefficiency, limited methods for quality assessment, and poor interpretability. To address these challenges, significant research opportunities exist in the future, such as constructing evaluators, parallelized training, and exploring continuous action spaces., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.)

Artificial two-dimensional (2D) moiré superlattices provide a platform for generating exotic quantum matter or phenomena. Here, an epitaxial heterostructure composed of bilayer Bi(111) and an Fe 3 GeTe 2 substrate with a zero-twist angle is acquired by molecular beam epitaxy. Scanning tunneling microscopy and spectroscopy studies reveal the spatially tailored Kondo resonance and interfacial magnetism within this moiré superlattice. Combined with first-principles calculations, it is found that the modulation effect of the moiré superlattice originates from the interfacial orbital hybridization between Bi and Fe atoms. Our work provides a tunable platform for strong electron correlation studies to explore 2D artificial heavy Fermion systems and interface magnetism.

The free-field switching of the perpendicular magnetization by the out-of-plane polarized spin current induced spin-orbit torque makes it a promising technology for developing high-density memory and logic devices. The materials intrinsically with low symmetry are generally utilized to generate the spin current with out-of-plane spin polarization. However, the generation of the out-of-plane polarized spin current by engineering the symmetry of materials has not yet been reported. Here, we demonstrate that paramagnetic CaRuO 3 films are able to generate out-of-plane polarized spin current by engineering the crystal symmetry. The non-uniform oxygen octahedral tilt/rotation along film's normal direction induced by oxygen octahedral coupling near interface breaks the screw-axis and glide-plane symmetries, which gives rise to a significant out-of-plane polarized spin current. This spin current can drive field-free spin-orbit torque switching of perpendicular magnetization with high efficiency. Our results offer a promising strategy based on crystal symmetry design to manipulate spin current and could have potential applications in advanced spintronic devices., (© 2024. The Author(s).)

Mechanical damage of LiMn 2 O 4 active material caused by volume change, phase transition, and lithium diffusion-induced stress is the main degradation mechanism in lithium-ion batteries. Young's modulus is a key parameter of mechanical property, and its variation with lithium content x or state of charge (SOC) at the nanoscale is an important issue because such variation may have influences on the stress level and lithium-ion transport. In this study, we successfully developed bimodal atomic force microscopy (bimodal AFM) and related approaches to carry out surface topography imaging and Young's modulus mapping of Li x Mn 2 O 4 nanosized particles. It was validated that the size of particles decreased with decreasing SOC due to delithiation during the charging cycle. The variation in Young's modulus with SOC was quantitatively determined using the silicon material as a reference, and the trend of the variation is consistent with the reported results of molecular dynamics simulation. Furthermore, spatially nonuniform distribution of Young's modulus on the nanosized particle surface was found even upon completion of charging. This phenomenon could be attributed to the coexistence of two phases during the charging process. Our experimental study reveals the correlation between Young's modulus of LiMn 2 O 4 and SOC at the nanosized particle level, and we believe that the bimodal AFM will be widely used in the nanocharacterization of the electrode materials because lithium content- or SOC-dependent mechanical properties are common in battery electrode materials.

This study aims to evaluate the repeatability of radiomics and dosiomics features via image perturbation of patients with cervical cancer. A total of 304 cervical cancer patients with planning CT images and dose maps were retrospectively included. Random translation, rotation, and contour randomization were applied to CT images and dose maps before radiomics feature extraction. The repeatability of radiomics and dosiomics features was assessed using intra-class correlation of coefficient (ICC). Pearson correlation coefficient (r) was adopted to quantify the correlation between the image characteristics and feature repeatability. In general, the repeatability of dosiomics features was lower compared with CT radiomics features, especially after small-sigma Laplacian-of-Gaussian (LoG) and wavelet filtering. More repeatable features (ICC > 0.9) were observed when extracted from the original, Large-sigma LoG filtered, and LLL-/LLH-wavelet filtered images. Positive correlations were found between image entropy and high-repeatable feature number in both CT and dose (r = 0.56, 0.68). Radiomics features showed higher repeatability compared to dosiomics features. These findings highlight the potential of radiomics features for robust quantitative imaging analysis in cervical cancer patients, while suggesting the need for further refinement of dosiomics approaches to enhance their repeatability.

Objectives: Accurate beam modelling is essential for dose calculation in stereotactic radiation therapy (SRT), such as CyberKnife treatment. However, the present deep learning methods only involve patient anatomical images and delineated masks for training. These studies generally focus on traditional intensity-modulated radiation therapy (RT) plans. Nevertheless, this paper aims to develop a deep CNN-based method for CyberKnife plan dose prediction about brain cancer patients. It utilized modelled beam information, target delineation, and patient anatomical information., Methods: This study proposes a method that adds beam information to predict the dose distribution of CyberKnife in brain cases. A retrospective dataset of 88 brain and abdominal cancer patients treated with the Ray-tracing algorithm was performed. The datasets include patients' anatomical information (planning CT), binary masks for organs at risk (OARs) and targets, and clinical plans (containing beam information). The datasets were randomly split into 68, 6, and 14 brain cases for training, validation, and testing, respectively., Results: Our proposed method performs well in SRT dose prediction. First, for the gamma passing rates in brain cancer cases, with the 2 mm/2% criteria, we got 96.7% ± 2.9% for the body, 98.3% ± 3.0% for the planning target volume, and 100.0% ± 0.0% for the OARs with small volumes referring to the clinical plan dose. Secondly, the model predictions matched the clinical plan's dose-volume histograms reasonably well for those cases. The differences in key metrics at the target area were generally below 1.0 Gy (approximately a 3% difference relative to the prescription dose)., Conclusions: The preliminary results for selected 14 brain cancer cases suggest that accurate 3-dimensional dose prediction for brain cancer in CyberKnife can be accomplished based on accurate beam modelling for homogeneous tumour tissue. More patients and other cancer sites are needed in a further study to validate the proposed method fully., Advances in Knowledge: With accurate beam modelling, the deep learning model can quickly generate the dose distribution for CyberKnife cases. This method accelerates the RT planning process, significantly improves its operational efficiency, and optimizes it., Competing Interests: This is the first submission of this manuscript and no parts of this manuscript are being considered for publication elsewhere. All authors have approved this manuscript. No author has financial or other contractual agreements that might cause conflicts of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology.)

Traditional magnetic sub-Kelvin cooling relies on the nearly free local moments in hydrate paramagnetic salts, whose utility is hampered by the dilute magnetic ions and low thermal conductivity. Here we propose to use instead fractional excitations inherent to quantum spin liquids (QSLs) as an alternative, which are sensitive to external fields and can induce a very distinctive magnetocaloric effect. With state-of-the-art tensor-network approach, we compute low-temperature properties of Kitaev honeycomb model. For the ferromagnetic case, strong demagnetization cooling effect is observed due to the nearly free Z 2 vortices via spin fractionalization, described by a paramagnetic equation of state with a renormalized Curie constant. For the antiferromagnetic Kitaev case, we uncover an intermediate-field gapless QSL phase with very large spin entropy, possibly due to the emergence of spinon Fermi surface and gauge field. Potential realization of topological excitation magnetocalorics in Kitaev materials is also discussed, which may offer a promising pathway to circumvent existing limitations in the paramagnetic hydrates., (© 2024. The Author(s).)

Formamidinium lead iodide (FAPbI 3 ) perovskite has lately surfaced as the preferred contender for highly proficient and robust perovskite solar cells (PSCs), owing to its favorable bandgap and superior thermal stability. Nevertheless, volatilization and migration of iodide ions (I - ) result in non-radiating recombination centers, and the presence of large formamidine (FA) cations tends to cause lattice strain, thereby reducing the power conversion efficiency (PCE) and stability of PSCs. To solve these problems, the lead formate (PbFa) is added into the perovskite solution, which effectively mitigates the halogen vacancy and provides tensile strain outside the perovskite lattice, thereby enhancing its properties. The strong coordination between the C═O of HCOO - and Pb-I backbones effectively immobilizes anions, significantly increases the energy barrier for anion vacancy formation and migration, and reduces the risk of lead ion (Pb 2+ ) leakage, thereby improving the operation and environmental safety of the device. Consequently, the champion PCE of devices with Ag electrodes can be increased from 22.15% to 24.32%. The unencapsulated PSCs can still maintain 90% of the original PCE even be stored in an N 2 atmosphere for 1440 h. Moreover, the target devices have significantly improved performance in terms of light exposure, heat, or humidity., (© 2024 Wiley‐VCH GmbH.)

The advent of 2D materials has ushered in the exploration of their synthesis, characterization and application. While plenty of 2D materials have been synthesized on various metallic substrates, interfacial interaction significantly affects their intrinsic electronic properties. Additionally, the complex transfer process presents further challenges. In this context, experimental efforts are devoted to the direct growth on technologically important semiconductor/insulator substrates. This review aims to uncover the effects of substrate on the growth of 2D materials. The focus is on non-metallic substrate used for epitaxial growth and how this highlights the necessity for phase engineering and advanced characterization at atomic scale. Special attention is paid to monoelemental 2D structures with topological properties. The conclusion is drawn through a discussion of the requirements for integrating 2D materials with current semiconductor-based technology and the unique properties of heterostructures based on 2D materials. Overall, this review describes how 2D materials can be fabricated directly on non-metallic substrates and the exploration of growth mechanism at atomic scale., (© 2024 Wiley‐VCH GmbH.)

The quantum conductance (QC) behaviors in synaptic devices with stable and tunable conductance states are essential for high-density storage and brain-like neurocomputing (NC). In this work, inspired by the discontinuous transport of fluid in spider silk, a synaptic device composed of a silicon oxide nanowire network embedded with silicon quantum dots (Si-QDs@SiO x ) is designed. The tunable QC behaviors are achieved in both the SET and RESET processes, and the QC states exhibit stable retention time exceeding 10 4 s in the synaptic device and show stable reproducibility after an interval of two months. The synaptic plasticity, including long-term potentiation/depression and Pavlovian conditioning function, is simulated based on the tunable conductance. The mechanism of stable and tunable QC behaviors is analyzed and clarified by beading effect of spider silk in Si-QDs@SiO x nanowires structure. The digit recognition capability of the device is evaluated by simulation using an artificial neural network consisting of the Si-QDs@SiO x -based synaptic device. These results provide insights into the development of neurocomputing systems with high classification accuracy.

Gamma Knife radiosurgery (GKRS) is a well-established technique in radiation therapy (RT) for treating small-size brain tumors. It administers highly concentrated doses during each treatment fraction, with even minor dose errors posing a significant risk of causing severe damage to healthy tissues. It underscores the critical need for precise and meticulous precision in GKRS. However, the planning process for GKRS is complex and time-consuming, heavily reliant on the expertise of medical physicists. Incorporating deep learning approaches for GKRS dose prediction can reduce this dependency, improve planning efficiency and homogeneity, streamline clinical workflows, and reduce patient lagging times. Despite this, precise Gamma Knife plan dose distribution prediction using existing models remains a significant challenge. The complexity stems from the intricate nature of dose distributions, subtle contrasts in CT scans, and the interdependence of dosimetric metrics. To overcome these challenges, we have developed a "Cascaded-Deep-Supervised" Convolutional Neural Network (CDS-CNN) that employs a hybrid-weighted optimization scheme. Our innovative method incorporates multi-level deep supervision and a strategic sequential multi-network training approach. It enables the extraction of intra-slice and inter-slice features, leading to more realistic dose predictions with additional contextual information. CDS-CNN was trained and evaluated using data from 105 brain cancer patients who underwent GKRS treatment, with 85 cases used for training and 20 for testing. Quantitative assessments and statistical analyses demonstrated high consistency between the predicted dose distributions and the reference doses from the treatment planning system (TPS). The 3D overall gamma passing rates (GPRs) reached 97.15% ± 1.36% (3 mm/3%, 10% threshold), surpassing the previous best performance by 2.53% using the 3D Dense U-Net model. When evaluated against more stringent criteria (2 mm/3%, 10% threshold, and 1 mm/3%, 10% threshold), the overall GPRs still achieved 96.53% ± 1.08% and 95.03% ± 1.18%. Furthermore, the average target coverage (TC) was 98.33% ± 1.16%, dose selectivity (DS) was 0.57 ± 0.10, gradient index (GI) was 2.69 ± 0.30, and homogeneity index (HI) was 1.79 ± 0.09. Compared to the 3D Dense U-Net, CDS-CNN predictions demonstrated a 3.5% improvement in TC, and CDS-CNN's dose prediction yielded better outcomes than the 3D Dense U-Net across all evaluation criteria. The experimental results demonstrated that the proposed CDS-CNN model outperformed other models in predicting GKRS dose distributions, with predictions closely matching the TPS doses., (© 2024. Australasian College of Physical Scientists and Engineers in Medicine.)

Three-dimensional (3D) cell culture models capable of emulating the biological functions of natural tissues are pivotal in tissue engineering and regenerative medicine. Despite progress, the fabrication of in vitro heterocellular models that mimic the intricate structures of natural tissues remains a significant challenge. In this study, we introduce a novel, scaffold-free approach leveraging the inertial focusing effect in rotating hanging droplets for the reliable production of heterocellular spheroids with controllable core-shell structures. Our method offers precise control over the core-shell spheroid's size and geometry by adjusting the cell suspension density and droplet morphology. We successfully applied this technique to create hair follicle organoids, integrating dermal papilla cells within the core and epidermal cells in the shell, thereby achieving markedly enhanced hair inducibility compared to mixed-structure models. Furthermore, we have developed melanoma tumor spheroids that accurately mimic the dynamic interactions between tumor and stromal cells, showing increased invasion capabilities and altered expressions of cellular adhesion molecules and proteolytic enzymes. These findings underscore the critical role of cellular spatial organization in replicating tissue functionality in vitro . Our method represents a significant advancement towards generating heterocellular spheroids with well-defined architectures, offering broad implications for biological research and applications in tissue engineering., (© 2024 IOP Publishing Ltd.)

In this article, we propose two methods for designing higher Chern number models from the topological defect perspective. Based on the fact that the Chern number is equal to a summation of the charges of meron defects, we show that the higher Chern number structures can be realized by either moving the positions of merons or increasing the amount of them. The combination of the two methods is also verified to be a viable approach. We shall construct several models and investigate their energy spectrum. More than one gapless state can be observed on the edges of these models. Expectedly, our theory promises to provide not only a simple approach to obtain the Chern number without computing any integrals, but also a practical technique for new material design., (© 2024 IOP Publishing Ltd.)

Oxygen vacancies are generally considered to play a crucial role in the oxygen evolution reaction (OER). However, the generation of active sites created by oxygen vacancies is inevitably restricted by their condensation and elimination reactions. To overcome this limitation, here, we demonstrate a novel photoelectric reconstruction strategy to incorporate atomically dispersed Cu into ultrathin (about 2-3 molecular) amorphous oxyhydroxide (a-CuM, M = Co, Ni, Fe, or Zn), facilitating deprotonation of the reconstructed oxyhydroxide to generate high-valence Cu. The in situ XAFS results and first-principles calculations reveal that Cu atoms are stabilized at high valence during the OER process due to Jahn-Teller distortion, resulting in para-type double oxygen vacancies as dynamically stable catalytic sites. The optimal a-CuCo catalyst exhibits a record-high mass activity of 3404.7 A g -1 at an overpotential of 300 mV, superior to the benchmarking hydroxide and oxide catalysts. The developed photoelectric reconstruction strategy opens up a new pathway to construct in situ stable oxygen vacancies by high-valence Cu single sites, which extends the design rules for creating dynamically stable active sites.

Two-dimensional materials with layered structures, appropriate band gaps, and high carrier mobility have attracted tremendous interest for their potential applications. Here we report the growth of monolayer SnP 3 on Au(111) surfaces by molecular beam epitaxy. The kinetic processes for the growth and the crystalline properties are studied by scanning tunneling microscopy. The weak interaction between SnP 3 and its Au(111) substrate is signified by the random crystal orientation distributions of SnP 3 nanosheets. The electronic structures exhibit a band gap of ∼0.25 eV and high charge carrier mobility comparable to that of black phosphorus engineered by compressive strain. Additionally, domain boundary junctions with opposite chirality are observed, resulting from the strained film in the epitaxial growth process. Our work provides a method to fabricate high-quality monolayer SnP 3 and suggests that the monolayer SnP 3 is a promising candidate for applications in nanoelectronics and optoelectronics.

Suffering from the susceptibility to decomposition, the potential electrochemical application of FeOCl has greatly been hindered. The rational design of the soft-hard material interface can effectively address the challenge of stress concentration and thus decomposition that may occur in the electrodes during charging and discharging. Herein, interlayer structure manipulation of FeOCl/MXene using soft-hard interface design method were conducted for electrochemical dechlorination. FeOCl was encapsulated in Ti 3 C 2 T x MXene nanosheets by electrostatic self-assembly layer by layer to form a soft-hard mechanical hierarchical structure, in which Ti 3 C 2 T x was used as flexible buffer layers to relieve the huge volume change of FeOCl during Cl - intercalation/deintercalation and constructed a conductive network for fast charge transfer. The CDI dechlorination system of FeOCl/Ti 3 C 2 T x delivered outstanding Cl - adsorption capacity (158.47 ± 6.98 mg g -1 ), rate (6.07 ± 0.35 mg g -1 min -1 ), and stability (over 94.49 % in 30 cycles), and achieved considerable energy recovery (21.14 ± 0.25 %). The superior dechlorination performance was proved to originate from the Fe 2+ /Fe 3+ topochemical transformation and the deformation constraint effect of Ti 3 C 2 T x on FeOCl. Our interfacial design strategy enables a hard-to-soft integration capacity, which can serve as a universal technology for solving the traditional problem of electrode volume expansion., (© 2024 Wiley-VCH GmbH.)

The complex interrelationships among thermoelectric parameters mean that a priori design of high-performing materials is difficult. However, band engineering can allow the power factor to be optimized through enhancement of the Seebeck coefficient. Herein, using layered Sb 2 Si 2 Te 6 and Sc 2 Si 2 Te 6 as model systems, we comprehensively investigate and compare their thermoelectric properties by employing density functional theory combined with semiclassical Boltzmann transport theory. Our simulations reveal that Sb 2 Si 2 Te 6 exhibits superior electrical conductivity compared to Sc 2 Si 2 Te 6 due to lower scattering rates and more pronounced band dispersion. Remarkably, despite Sb 2 Si 2 Te 6 exhibiting a lower lattice thermal conductivity and superior electrical conductivity, Sc 2 Si 2 Te 6 is predicted to achieve an extraordinary dimensionless figure of merit ( ZT ) of 3.51 at 1000 K, which significantly surpasses the predicted maximum ZT of 2.76 for Sb 2 Si 2 Te 6 at 900 K. We find the origin of this behavior to be a combined increase in band (valley) degeneracy and anisotropy upon switching the conduction band orbital character from Sb p to Sc d, yielding a significantly improved Seebeck coefficient. This work suggests that enhancing band degeneracy and anisotropy (complexity) through compositional variation is an effective strategy for improving the thermoelectric performance of layered materials.

Compressive sensing (CS) can reconstruct the rest information almost without distortion by advanced computational algorithm, which significantly simplifies the process of atomic force microscope (AFM) scanning with high imaging quality. In common CS-AFM, the partial measurements randomly come from the whole region to be measured, which easily leads to detail loss and poor image quality in regions of interest (ROIs). Consequently, important microscopic phenomena are missed probably. In this paper, we developed an adaptive under-sampling strategy for CS-AFM to optimize the process of sampling. Under a certain under-sampling ratio, the weight coefficient of ROIs and regions of base (ROBs) were set to control the distribution of under-sampling points and corresponding measurement matrix. A series of simulations were completed to demonstrate the relationship between the weight coefficient of ROIs and image quality. After that, we verified the effectiveness of the method on our homemade AFM. Through a lot of simulations and experiments, we demonstrated how the proposed method optimized the sampling process of CS-AFM, which speeded up the process of AFM imaging with high quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Multifrequency atomic force microscopy (AFM) utilizes the multimode operation of cantilevers to achieve rapid high-resolution imaging and extract multiple properties. However, the higher-order modal response of traditional rectangular cantilever is weaker in air, which affects the sensitivity of multifrequency AFM detection. To address this issue, we previously proposed a bridge/cantilever coupled system model to enhance the higher-order modal response of the cantilever. This model is simpler and less costly than other enhancement methods, making it easier to be widely used. However, previous studies were limited to theoretical analysis and preliminary simulations regarding ideal conditions. In this paper, we undertake a more comprehensive investigation of the coupled system, taking into account the influence of probe and excitation surface sizes on the modal response. To facilitate the exploration of the effectiveness and optimal conditions for the coupled system in practical applications, a macroscale experimental platform is established. By conducting finite element analysis and experiments, we compare the performance of the coupled system with that of traditional cantilevers and quantify the enhancement in higher-order modal response. Also, the optimal conditions for the enhancement of macroscale cantilever modal response are explored. Additionally, we also supplement the characteristics of this model, including increasing the modal frequency of the original cantilever and generating additional resonance peaks, demonstrating the significant potential of the coupled system in various fields of AFM., (Copyright © 2024, Sun et al.)

We report the charge-changing cross sections (σ cc ) of 24 p-shell nuclides on both hydrogen and carbon at about 900A MeV, of which 8,9 Li, 10-12 Be, 10,14,15 B, 14,15,17-22 N and 16 O on hydrogen and 8,9 Li on carbon are for the first time. Benefiting from the data set, we found a new and robust relationship between the scaling factor of the Glauber model calculations and the separation energies of the nuclei of interest on both targets. This allows us to deduce proton radii (R p ) for the first time from the cross sections on hydrogen. Nearly identical R p values are deduced from both target data for the neutron-rich carbon isotopes; however, the R p from the hydrogen target is systematically smaller in the neutron-rich nitrogen isotopes. This calls for further experimental and theoretical investigations., (Copyright © 2024 Science China Press. Published by Elsevier B.V. All rights reserved.)

Subsurface detection capability of bimodal atomic force microscopy (AFM) was investigated using the buried microcavity as a reference sample, prepared by partially covering a piece of highly oriented pyrolytic graphite (HOPG) flake with different thickness on a piece of a cleaned CD-R disk substrate. This capability can be manifested as the image contrast between the locations with and without the buried microcavities. The theoretical and experimental results demonstrated that the image contrast is significantly affected by the critical parameters, including the second eigenmode amplitude and frequency as well as local structural and mechanical properties of the sample itself. Specifically, improper parameter settings generally lead to incorrect identification of the buried microcavity due to the contrast reduction, contrast reversal and even disappearance. For accurate detection, the second eigenmode amplitude should be as small as possible on the premise of satisfying the signal-to-noise ratio and second eigenmode frequency should be close to the resonance frequency of the cantilever. In addition, the detectable depth is closely related to microcavity dimension (thickness and width) of the HOPG flake and local stiffness of the sample. These results would be helpful for further understanding of the detection mechanism of bimodal AFM and facilitating its application in nano-characterization of subsurface structures, such as the micro-/nano- channels to direct the flow of liquids in lab-on-a-chip devices., (© 2024 IOP Publishing Ltd.)