Engineering a High-Loading Sub-4 nm Intermetallic Platinum-Cobalt Alloy on Atomically Dispersed Cobalt-Nitrogen-Carbon for Efficient Oxygen Reduction in Fuel Cells.

Developing a high-performance membrane electrode assembly (MEA) poses a formidable challenge for fuel cells, which lies in achieving both high metal loading and efficient catalytic activity concurrently for MEA catalysts. Here, we introduce a porous Co@NC carrier to synthesize sub-4 nm PtCo intermetallic nanocrystals, achieving an impressive Pt loading of 27 wt %. The PtCo-CoNC catalyst demonstrates exceptional catalytic activity and remarkable stability for the oxygen reduction reaction. Advanced characterization techniques and theoretical calculations emphasize the synergistic effect between PtCo alloys and single Co atoms, which enhances the desorption of the OH* intermediate. Furthermore, the PtCo-CoNC-based cathode delivers a high power density of 1.22 W cm-2 in the MEA test owing to the enhanced mass transport, which is verified by the simulation results of the O2 distributions and current density inside the catalyst layer. This study lays the groundwork for the design of efficient catalysts with practical applications in fuel cells.

Leveraging an all-fixed transfer framework to predict the interpretable formation energy of MXenes with hybrid terminals.

MXenes have attracted substantial attention for their various applications in energy storage, sensors, and catalysts. Experimental exploration of MXenes with hybrid terminal surfaces offers a unique means of property tailoring that is crucial for expanding the performance space of MXenes, wherein the formation energy of an MXene with mixed surface terminals plays a key role in determining its relative stability and practical applications. However, the challenge of identifying energetically stable MXenes with multifunctional surfaces persists, primarily due to the absence of precise surface modification during experiments and the vast structural space for DFT calculations. Herein, we use an all-fixed transfer (AFT) framework combined with first-principles calculations to predict the formation energies of MXenes terminated by binary elements from groups VIA and VIIA. The trained model exhibits a high average R2 of 0.99, maintaining transferability and accuracy in predicting larger supercells from smaller-sized MXenes and datasets despite the structural imbalance between the training and prediction sets. The underlying interpretation of the high accuracy is revealed through the capture of main attributes and comparison of node features. Additionally, it is important to mention that the factors influencing the average formation energy include the types of element pairs, the ratio of terminal groups, and the distribution of terminations on two surfaces, with the first one being dominant. Finally, we successfully streamline the diverse structural cardinality of a large hybrid terminated MXene space of over 700 million, thereby facilitating the rapid screening of the top 5 stable MXene classes with binary terminal elements (FO, FCl, FBr, FS, and FSe). Besides, in the scenarios of lithium storage, the TL-predicted MXene can enhance its relative stability by increasing the fluorine ratio where the capacity can be optimized by different surface group combinations. All results indicate that the AFT framework has the advantages of screening functional MXenes with a huge structure space from smaller and imbalanced data sets.

Enhancement of multilayer lithium storage in a ß12-borophene/graphene heterostructure with built-in dipoles.

The combination of borophene with a supporting metallic layer is beneficial in stabilizing its structure and promoting its application in energy storage. Here, through first-principles calculations, we screen a ß12-borophene/graphene (ß12-B/G) heterostructure with superior structural integrity, strong interlayer binding, and high thermodynamic stability among different B/G heterostructures. Besides, it is noteworthy that ß12-B/G has been recently synthesized, further opening the possibility of expanding its use in energy storage. Then the selected target is systematically investigated as an anode material for lithium-ion batteries (LIBs). Compared with each monolayer component, multiple lithium-ion adsorption is achieved in the ß12-B/G heterostructure, resulting in an ultra-high theoretical specific capacity of 2267 mA h g-1. In addition, a lower diffusion energy barrier indicates faster electron transport and lithium-ion diffusion in the ß12-B/G heterostructure. Notably, the multilayer lithium adsorption avoids the formation of dendritic deposits, as evidenced by complete ionization of the cationic layers. Moreover, the disparity in the work functions of the individual layers gives rise to a built-in dipole in ß12-B/G, further enhancing the multilayer lithium storage and ion migration. All these results suggest that the construction of borophene-based heterostructures with built-in dipoles is a feasible way to design high-performance LIB anode materials.

A weakened Fermi level pinning induced adsorption energy non-charge-transfer mechanism during O2 adsorption in silicene/graphene heterojunctions.

Understanding the mechanisms of gas adsorption on a solid surface and making this process tunable are of great significance in fundamental science and industrial applications. Bond creation and charge transfer are often used to explain the origin of adsorption energy (Ead). However, in this study, a new mechanism is observed in O2 adsorption on pure silicene (PS) and silicene/graphene heterojunction (SGH) surfaces, in which the charge distribution remains almost unchanged, but Ead still has a significant change in the order of 0.3 eV. The weakened Fermi level pinning effect is found to be responsible for this interesting behavior and the variation of Ead is approximately equal to the change of work function. Furthermore, this effect is independent of the twist angles in the van der Waals SGH. Our results are consistent with experimental observations in overcoming the degradation of silicene in air.

Very high-frequency, gate-tunable CrPS4 nanomechanical resonator with single mode.

Two-dimensional (2D) antiferromagnetic semiconductor chromium thiophosphate (CrPS4) has gradually become a major candidate material for low-dimensional nanoelectromechanical devices due to its remarkable structural, photoelectric characteristics and potentially magnetic properties. Here, we report the experimental study of a new few-layer CrPS4 nanomechanical resonator demonstrating excellent vibration characteristics through the laser interferometry system, including the uniqueness of resonant mode, the ability to work at the very high frequency, and gate tuning. In addition, we demonstrate that the magnetic phase transition of CrPS4 strips can be effectively detected by temperature-regulated resonant frequencies, which proves the coupling between magnetic phase and mechanical vibration. We believe that our findings will promote the further research and applications of the resonator for 2D magnetic materials in the field of optical/mechanical signal sensing and precision measurement.

Gate-tunable bolometer based on strongly coupled graphene mechanical resonators.

Bolometers based on graphene have demonstrated outstanding performance with high sensitivity and short response time. In situ adjustment of bolometers is very important in various applications, but it is still difficult to implement in many systems. Here we propose a gate-tunable bolometer based on two strongly coupled graphene nanomechanical resonators. Both resonators are exposed to the same light field, and we can measure the properties of one bolometer by directly tracking the resonance frequency shifts, and indirectly measure the other bolometer through mechanical coupling. We find that the sensitivity and the response bandwidth of both bolometers can be independently adjusted by tuning the corresponding gate voltages. Moreover, the properties of the indirectly measured bolometer show a dependence on the coupling between the two resonators, with other parameters being fixed. Our method has the potential to optimize the design of large-scale bolometer arrays, and open new horizons in infrared/terahertz astronomy and communication systems.

Machine-learning-assisted discovery of boron-doped graphene with high work function as an anode material for Li/Na/K-ion batteries.

Work function (WF) modulation is a crucial descriptor for carbon-based electrodes in optoelectronic, catalytic, and energy storage applications. Boron-doped graphene is envisioned as a highly promising anode material for alkali metal-ion batteries (MIBs). However, due to the large structural space concerning various doping concentrations, the lack of both datasets and effective methods hinders the discovery of boron-doped graphene with a high WF that generally leads to strong adsorption. Herein, we propose a machine-learning-assisted approach to discover the target, where a Crystal Graph Convolutional Neural Network was developed to efficiently predict the WF for all possible configurations. As a result, the B5C27 structure is found to have the highest WF in the entire space containing 566 211 structures. In addition, it is revealed that the adsorption energy of alkali metals is linearly related to the WF of the substrate. Therefore, the screened B5C27 is investigated as an anode for Li/Na/K-ion batteries, and it possesses a higher theoretical specific capacity of 2262/2546/1131 mA h g-1 for Li/Na/K-ion batteries compared with that of pristine graphene and other boron-doped graphene. Our work provides an effective way to locate possible high-WF structures in heteroatom-doped systems, which may accelerate future screening of promising adsorbents for alkali metals.

Machine learning-aided band gap prediction of semiconductors with low concentration doping.

The important physical quantities of materials, such as band gap, have been predicted efficiently with the help of machine learning (ML), in addition to the widely used experimental or computational methods. Under this scheme, by combining density functional theory (DFT) calculations and ML predictive models, the band gaps of doped semiconductors with normal doping concentrations are predicted successfully. Our present work provides a solution to the problem of how to obtain the band gaps of semiconductors doped with extremely low concentrations, which are important cases for some device designs. The structures were constructed by configuration screening with a symmetric criterion, and three-dimensional spatial structural variation was mapped to one-dimensional features, which are the key steps for the ML predictive model. The biggest error in the predicted band gaps of dilute nitride-doped GaAs by ML models is not more than 10%, compared with values obtained from DFT. Considering the limitation of material data, a few-shot learning method was further adopted to check the performance of the predictive models. The performance of the ML models was validated using data out of training and testing datasets. Our method will efficiently accelerate the prediction of physical properties of semiconductors with extremely low-concentration doping.

Coupling Atomically Dispersed Fe-N5 Sites with Defective N-Doped Carbon Boosts CO2 Electroreduction.

Atomically dispersed iron immobilized on nitrogen-doped carbon catalyst has attracted enormous attention for CO2 electroreduction, but still suffers from low current density and poor selectivity. Herein, atomically dispersed FeN5 active sites supported on defective N-doped carbon successfully formed by a multistep thermal treatment strategy with the aid of dicyandiamide are reported. This dual-functional strategy can not only construct intrinsic carbon defects by selectively etching pyridinic-N and pyrrolic-N, but also introduces an additional N from the neighboring carbon layer coordinating to the commonly observed FeN4 , thus creating an FeN5 active site supported on defective porous carbon nanofibers (FeN5 /DPCF) with a local 3D configuration. The optimized FeN5 /DPCF achieves a high CO Faradaic efficiency (>90%) over a wide potential range of -0.4 to -0.6 V versus RHE with a maximal FECO of 93.1%, a high CO partial current density of 9.4 mA cm-2 at the low overpotential of 490 mV, and a remarkable turnover frequency of 2965 h-1 . Density functional theory calculations reveal that the synergistic effect between the FeN5 sites and carbon defects can enhance electronic localization, thus reducing the energy barrier for the CO2 reduction reaction and suppressing the hydrogen evolution reaction, giving rise to the superior activity and selectivity.

Phonon lasing with an atomic thin membrane resonator at room temperature.

Graphene has been considered as one of the best materials to implement mechanical resonators due to their excellent properties such as low mass, high quality factors and tunable resonant frequencies. Here we report the observation of phonon lasing induced by the photonthermal pressure in a few-layer graphene resonator at room temperature, where the graphene resonator and the silicon substrate form an optical cavity. A marked threshold in the oscillation amplitude and a narrowing linewidth of the vibration mode are observed, which confirms a phonon lasing process in the graphene resonator. Our findings will stimulate the studies on phononic phenomena, help to establish new functional devices based on graphene mechanical resonators, and might find potential applications in classical and quantum sensing fields, as well as in information processing.

Growth of h-BN/graphene heterostructure using proximity catalysis.

In this study, a proximity catalysis route was developed for the fast growth of graphene/h-BN vertical heterostructures on Cu foils, which shows much improved synthesis efficiency (500 times faster than other routes) and good crystalline quality graphene (large single crystalline length up to 10µm). The key advantage of our synthesis route is the introduction of fresh Cu foil (or Cu foam) into the high-temperature zone using a turntable. At high temperatures, Cu vapor acts as a gaseous catalyst, which can reduce the energy barrier of graphene growth and promote the decomposition of carbon sources. Therefore, after the first layer of hexagonal boron nitride is grown on the Cu substrate, another layer of graphene can be grown by introducing a fresh catalyst. Our calculations have revealed the catalytic effect and graphene growth contribution of Cu vapor evaporated by the suspended catalyst. We also investigated the growth sequence of graphene from 1 to 24 carbon atoms on h-BN/Cu and determined the morphology evolution of these carbon clusters. In this regard, multilayer stacked heterogeneous structures can be synthesized, thus increasing their potential applications in high performance electronic devices and energy harvesting/transition directions.

Vacancy engineering of WO3-x nanosheets for electrocatalytic NRR process - a first-principles study.

It has been proved experimentally that tungsten oxide (WO3) in a defective state has a positive effect on nitrogen reduction reactions (NRRs) owing to the surface modification by adding oxygen vacancies and doping. However, the role of different oxygen vacancies in the electrocatalytic NRR is still behind the scenes. In this study, we have carried out first-principles calculations to grapple with its causes and consequences, focusing on the two-dimensional WO3-x surface on an atomic scale. Our study shows that WO3 does not promote nitrogen reduction simply by a dimension reduction without oxygen vacancy. Two NRR processes, which are found to follow the associative mechanism in various pathways, are initiated at relatively lower potentials at two possible vacancies. It is the polarized electrons after being adsorbed over the dangling oxygen vacancy, which weaken the N[triple bond, length as m-dash]N bond and enables N2 reduction with a rate-limiting potential as large as -1.89 V. In contrast, the desorption of NH3 from the planar vacancy is kinetically challenging at a cost of 1.47 eV, in which case the d orbitals of under-coordinated W match the p orbitals of N and form both bonding state and anti-bonding state. It demonstrates that P-VO-WO3 and N2 can bond firmly but NH3 desorption ought to pay a price. Two alternative schemes are accordingly proposed to balance good nitrogen adsorption and desorption. This noble metal-free system, by regulating vacancy sites, demonstrates its potential as an eco-friendly and fine-grained artificial material for electrochemical nitrogen reduction.

Circular RNA profiling facilitates the diagnosis and prognostic monitoring of breast cancer: A pair-wise meta-analysis.

BACKGROUND: As circular RNAs (circRNAs) have been found to significantly involve in the onset and progression of multiple malignant tumors including breast cancer (BC), this study aims at evaluating the diagnostic and prognostic values of circRNAs in this malady. METHODS: Available databases were thoroughly searched to collect studies on the diagnosis and/or prognosis of BC using circRNA profiling. The updated Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool and the Newcastle Ottawa Scale (NOS) were used to assess the underlying bias of included studies. Clinical characteristics of the studies were merged by the quantitative-weighted integral method to obtain the combined effects. RESULTS: Sixteen studies were included, comprising 2438 BC cases and 271 noncancerous controls. The expression signature covered 24 circRNAs (down-regulated: circ-VRK1, hsa_circ_0068033, hsa_circ_103110, hsa_circ_104689, and hsa_circ_104821; up-regulated: circAGFG1, hsa_circ_0001785, hsa_circ_0108942, hsa_circ_0001785, hsa_circ_006054, hsa_circ_100219, hsa_circ_406697, circEPSTI1, circANKS1B, circGFRA1, circ_0103552, CDR1-AS, has_circ_001569, hsa_circ_001783, circFBXL5, circ_0005230, circAGFG1, circ-UBAP2, and circ_0006528). The sensitivity and specificity of circRNAs in distinguishing BC patients from noncancerous controls were 0.65 and 0.68, and the corresponding area under the curve was 0.66. Survival analysis revealed that patients showing highly expressed oncogenic circRNAs were associated with increased mortality risks of BC in overall survival (univariate analysis: hazard ratio [HR] = 3.30, P = .000; multivariate analysis: HR = 3.07, P = .000), and disease-free survival (HR = 8.26, P = .000). Stratified analysis based on circRNA expression status and control type also showed robust results. CONCLUSIONS: Circular RNA profiling presents prominent diagnostic and prognostic values in BC, and can be rated as a promising tool facilitating its early diagnosis and survival.

Defects and impurities induced structural and electronic changes in pyrite CoS2: first principles studies.

Cobalt pyrite (CoS2) and related materials are attracting much attention due to their potential use in renewable energy applications. In this work, first-principles studies were performed to investigate the effects of various neutral defects and ion dopants on the structural, energetic, magnetic and electronic properties of the bulk CoS2. Our theoretical results show that the concentrations of single cobalt (VCo) and sulfur (VS) vacancies in CoS2 samples can be high under S-rich and S-poor conditions, respectively. Although the single vacancies induce defect states near the gap edge, they are still half-metallic. We find that the substitution of one S with the O atom does not obviously change the structural, magnetic and electronic features near the Fermi level of the system. Most transition metal impurities (MnCo, FeCo, and MoCo) and Group IV and V anion impurities (CS, SiS, NS, PS, and AsS) create impurity states that are deep and/or near the gap edge. However, NiCo and Group VII elements (FS, ClS, and BrS) cause very localized gap states close to the Fermi level in the minority spin channel, which may modify their electrochemical performances. Our extensive calculations provide instructive information for the design and optimization of CoS2-related energy materials.

Remarkable negative differential resistance and perfect spin-filtering effects of the indium triphosphide (InP3) monolayer tuned by electric and optical ways.

Fully spin-polarized current and negative differential resistance (NDR) are two important electronic transport properties for spintronic nanodevices based on two-dimensional materials. Here, we describe both the electric and optical tuning of the spin-polarized electronic transport properties of the indium triphosphide (InP3) monolayer, which is doped with Ge atoms, by using quantum transport calculations. The spin degeneration of the InP3 monolayer is lifted due to the doping of Ge atoms. By applying a small bias voltage, a fully spin-polarized current can be obtained along both the armchair and zigzag directions. Moreover, a remarkable NDR is observed for the current along the zigzag direction, which shows a huge peak-to-valley ratio of 3.1 × 103, while in the armchair direction, a lower peak-to-valley ratio of 5.5 is obtained. Alternatively, a fully spin-polarized photocurrent can also be generated under the illumination of linearly-polarized light by tuning either the photon energy or the polarization angle.

Thermodynamic Self-Limiting Growth of Heteroepitaxial Islands Induced by Nonlinear Elastic Effect.

We investigate nonlinear elastic effect (NLEF) on the growth of heteroepitaxial islands, a topic of both scientific and technological significance for their applications as quantum dots. We show that the NLEF induces a thermodynamic self-limiting growth mechanism that hinders the strain relaxation of coherent island beyond a maximum size, which is in contrast to indefinite strain relaxation with increasing island size in the linear elastic regime. This self-limiting growth effect shows a strong dependence on the island facet angle, which applies also to islands inside pits patterned in a substrate surface with an additional dependence on the pit inclination angle. Consequently, primary islands nucleate and grow first in the pits and then secondary islands nucleate at the rim around the pits after the primary islands reach the self-limited maximum size. Our theory sheds new lights on understanding the heteroepitaxial island growth and explains a number of past and recent experimental observations.

Wedding Cake Growth Mechanism in One-Dimensional and Two-Dimensional Nanostructure Evolution.

The kinetic processes and atomistic mechanisms in nanostructure growth are of fundamental interest to nanomaterial syntheses with precisely controlled morphology and functionality. By programming deposition conditions at time domain, we observed the wedding cake growth mechanism in the formation of 1D and 2D ZnO nanostructures. Within a narrow growth window, the surfaces of the 1D and 2D structures were covered with a unique concentric terrace feature. This mechanism was further validated by comparing the characteristic growth rates to the screw dislocation-driven model. An interesting 1D to 2D morphology transition was also found during the wedding cake growth, when the adatoms overcome the Ehrlich-Schwoebel (ES) barrier along the edge of the top crystal facet triggered by lowering the supersaturation. The wedding cake model might be a general growth mechanism for flat-tipped nanowires that do not possess any dislocations. This study enriches our understanding on the fundamental kinetics of nanostructured crystal growth and provides a transformative strategy to achieve rational design and control of nanoscale geometry.

[A locking type drill protector].

A drill protector which can lock the drilling depth was designed, which is easy and safe.

Dual-salt strategy tuning the solvation structure to achieve high cycling stability for FeS2 cathodes.

Pyrite FeS2, as a promising conversion-type cathode material, faces rapid capacity degradation due to challenges such as polysulfide shuttle and massive volume changes. Herein, a localized high-concentration electrolyte (LHCE) based on dual-salt lithium bis(fluorosulfonyl)imide (LiFSI) and lithium bis(trifluoromethanesulphonyl)imide (LiTFSI) is designed to address the challenges. By the dual-salt strategy, we tailor a more desirable solvation structure than that in the single-salt system. Specifically, the solvation structure involving FSI- and TFSI- enables milder electrolyte decomposition, which reduces initial capacity loss. Meanwhile, it facilitates the formation of a stable and flexible cathode/electrolyte interphase (CEI), effectively mitigating side effects and accommodating volume changes. Consequently, the micro-sized FeS2 realizes a capacity of 641 mAh g-1 after 600 cycles with a retention rate of 90%, significantly improving the cycling stability of the FeS2 cathode. This work underscores the pivotal role of solvation structure in modulating electrochemical performances and provides a simple and effective electrolyte design concept for conversion-type cathodes.

APbI3-A2AgBiI6 Double-Layer Perovskite Film for a Self-Powered and High-Stability X-ray Detector.

The development of lead halide perovskite X-ray detectors has promising applications in medical imaging and security inspection but is hindered by poor long-term stability and drift of the dark current and photocurrent. Herein, we design a (Cs0.05MA0.65FA0.3)PbI3-(Cs0.1MA1.3FA0.6)AgBiI6 double-layer perovskite film to assemble a self-powered flat-panel X-ray detector. The demonstrated X-ray detector achieves an outstanding self-powered sensitivity of 80 µC Gyair-1 cm-2 under a 0 V bias. More importantly, owing to the inhibition of the phase transition process and ion migration of (Cs0.05MA0.65FA0.3)PbI3 by the (Cs0.1MA1.3FA0.6)AgBiI6 layer, the device exhibits excellent continuous operating stability with a retention rate of 99% dark current and photocurrent over X-ray pulses of up to 4000 s and excellent long-term stability without a loss of the original response current after 150 days in an air environment. The strategy of double-layer perovskites improves the stability and sensitivity of devices, which paves a path for the industrial application of lead halide perovskite X-ray detectors.