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In this study, continuous laser beam welding (CLBW) and tungsten-inert-gas (TIG) welding were employed to weld β-Ti dendrite-toughened metal glass composite with TC4 titanium alloy. The microstructure, element distribution, and mechanical properties of the welded joints were studied. The influence of the welding heat source state and welding speed on the crystallisation of the joints was analysed. The results revealed that at the interface between the fusion zone (FZ) and the Ti alloy, columnar crystals of β-Ti grew positively and extended from the Ti alloy into the FZ. The development of β-Ti grains was more pronounced during TIG welding than during CLBW owing to the lower cooling rate of the liquid pool in TIG welding. The hardness in the FZ of the TIG-welded sample was lower than that of the CLBW sample.

• Propose a novel CHBr 2 F plasma technology for prepare LiBr-LiF-enriched SEI. • Construct New sponge Ni skeleton (SN) supported Li composite anodes. • The composite Li electrode show stabilized interphases with enhanced performance. • LiBr-LiF-enriched interphases are favorable to achieve advanced Li anodes. The electrochemical performance of Li metal anode is closely bound up with the interphase between Li and lithium-loaded skeleton as well as solid electrolyte interphase (SEI) on Li surface. Herein, for the first time, we propose a novel liquid-source CHBr 2 F plasma technology to simultaneously construct dual bromine-fluorine-enriched interphases: NiBr 2 -NiF 2 interphase on sponge Ni (SN) skeleton and LiBr-LiF-enriched SEI on Li anode, respectively. Based on density functional theory (DFT) calculations and COMSOL multiphysics simulation results, SN skeleton with NiBr 2 -NiF 2 interphase can effectively decrease the local current density with good lithiophilicity. And the LiBr-LiF-enriched SEI on Li surface can function to block electron tunneling and hinder side electrochemical reduction of electrolyte components, thus suppressing the growth of dendrite and facilitating the homogeneous transportation of lithium ions. Consequently, the Li/SN electrodes with modified interphases show remarkable stability with a low overpotential of 22.6 mV over 1800 h at 1 mA cm–2/1 mAh cm–2 and an exceptional average Coulombic efficiency of 99.6%. When coupled with LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM811) cathode, the full cells deliver improved cycling stability with a capacity retention of 79.5% even after 350 cycles at 0.5 C. This study provides a facile and new plasma method for the construction of advanced Li anodes for energy storage. [Display omitted] [ABSTRACT FROM AUTHOR]

The strong adsorption between PF6–anions and oxygen vacancies of TiO2−xcan promote the dissociation of lithium salt and significantly improve the electrochemical performance of GPE.

RFID (Radio Frequency Identification) computing devices in practical applications often suffer from their poor computing performance in terms of low task throughput (also known as task rate) due to scarce harvested power. For optimizing the task throughput, the basic idea is to choose an optimal processor clock frequency when executing a specific task ($e.g.$e.g., operate sensor) in order to maximize task execution rate. Existing methods are based on the common sense where the frequency and task throughput are directly proportional to each other, meaning that a higher frequency causes a higher task rate. In RFID-scale devices, however, we observe that the relationship between the frequency and task throughput overturns the common sense, in which if the device rises the frequency, the task throughput will increase first and then decrease due to intermittent task execution pattern on such devices. In this article, we present a systematic task throughput model to explain and formulate the non-monotonic relationship between the frequency and task throughput. Based on the throughput model, we further introduce dynamic optimal frequency scaling (DOFS) to calculate the optimal frequency for task execution and thus optimize the task throughput in the RFID-scale devices. The experimental results show that the task throughput can be improved by 45.8% on average compared to the existing best effort.

Two previous unreported epipolythiodioxopiperazines of the emestrin family, namely, noremestrin A (1) and secoemestrin E (2), were successfully isolated from the fungal source Emericellasp. 1454. Employing comprehensive spectroscopic techniques, such as high-resolution electrospray ionization mass spectrometry, infrared, and nuclear magnetic resonance (NMR), along with NMR and electronic circular dichroism calculations, the chemical structures of compounds 1and 2were elucidated. Particularly noteworthy is the distinctive nature of noremestrin A, representing the inaugural instance of a noremestrin variant incorporating a sulfur-bearing 15-membered macrocyclic lactone moiety. Compounds 1and 2exhibited weak cytotoxic activities against the human chronic myelocytic leukemia cell lines MEG-01 and K562.

We propose and demonstrate a novel scheme for generating broadband and high-coherence linear frequency-modulated (LFM) waveforms based on heterodyne beating of two real-time phase-locked tunable lasers. The generation scheme comprises two hybrid integrated self-injection locked lasers in a master-slave configuration. By controlling the integrated high-Q microring resonator (MRR) external cavities through heaters and a piezoelectric transducer (PZT), the lasers can achieve broadband frequency linear sweeping and ultrafast tuning, respectively. Combined with an optical phase-locked loop (OPLL) and a standard intermediate frequency LFM (IF-LFM) reference signal, the slave laser can maintain real-time phase locking with the master laser. In the experiment, multiple coherence beat LFM signals with reconfigurable center frequency, bandwidth, and temporal period are generated, with a time-bandwidth product (TBWP) of up to $2.44 \times 10^{8}$. The performance in terms of the signal linearity and pulse-to-pulse coherence is characterized. Moreover, we conduct a dechirp ranging experiment using the generated signals in different frequency bands (C-, X-, Ku-, and K-bands) and successfully demonstrate the high-precision-ranging capability. Featuring a simple structure, a broad operation bandwidth, high phase coherence, and flexible reconfiguration, the proposed signal generation scheme is expected to play an important role in real-world radar application scenarios.

Random perturbation is a popular method of computing anonymized data for privacy preserving data mining. It is simple to apply, ensures strong privacy protection, and permits effective mining of a large variety of data patterns. However, all the existing studies with good privacy guarantees focus on perturbation at a single privacy level. Namely, a fixeddegree of privacy protection is imposed on allanonymized data released by the data holder. This drawback seriously limits the applicability of random perturbation in scenarios where the holder has numerous recipients to which different privacy levels apply.Motivated by this, we study the problem of multi-level perturbation, whose objective is to release multiple versions of a dataset anonymized at different privacy levels. The challenge is that various recipients may collude by sharing their data to infer privacy beyond their permitted levels. Our solution overcomes this obstacle, and achieves two crucial properties. First, collusion is useless, meaning that the colluding recipients cannot learn anything more than what the most trustable recipient (among the colluding recipients) already knows alone. Second, the data each recipient receives can be regarded (and hence, analyzed in the same way) as the output of conventional uniform perturbation. Besides its solid theoretical foundation, the proposed technique is both space economical and computationally efficient. It requires O (n+m)expected space, and produces a new anonymized version in O(n+ log m) expected time, where nis the cardinality of the original dataset, and mthe number of versions released previously. Both bounds are optimal under the realistic assumption that n» m.

All-solid-state lithium metal batteries (ASSLMBs) have garnered significant interest as a result of their enhanced safety features and higher energy density compared to traditional lithium-ion batteries with liquid electrolytes. Nonetheless, a substantial challenge within ASSLMBs lies in the constrained lithium-ion flux encountered in solid-state polymer electrolytes, resulting in subpar performance during high-current charging and discharging scenarios. This limitation detrimentally affects the electrochemical performance of ASSLMBs. In this present work, we introduce a novel composite solid polymer electrolyte (CSPE) comprising metal–organic frameworks, namely, UiO-66, poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP), and lithium bis(trifluoromethane)-sulfonimide (LiTFSI) (referred to as UPH-SPE). UPH-SPE containing 5 wt % UiO-66 demonstrates exceptional characteristics, including a high ionic conductivity of 4.7 × 10–4S cm–1, an electrochemical stability window of 4.9 V, and a remarkable lithium-ion transference number of 0.58 at 25 °C. Full cell tests unequivocally showcase that these newly developed composite electrolytes exhibit significantly improved performance in terms of the rate capability and cycling stability at room temperature. Specifically, the discharge capacity of ASSLMBs with UPH-SPE remains at 140 mAh g–1when operated at a current density of 0.5 C over 100 cycles. Even after 200 cycles, the capacity is sustained at 94 mAh g–1. This study underscores the potential of our CSPE film to advance the practical application of ASSLMBs, offering promising prospects for future developments in this field.

To identify the discharge features of tungsten inert gas (TIG) welding arc on magnesium alloy workpiece, spectral diagnosing and a self-developed Langmuir probe detection were jointly performed on the welding arc. Results show that during welding, Mg atoms with low ionization energy rush into the burning arc and replace Ar atoms to discharge, which gives influences on arc discharge. The arc plasmas have a normal space potential distribution. Reflected by both of the two diagnosing methods, region near arc anode (magnesium alloy workpiece) has the lowest electron temperature and the highest electron density. The variations of electron temperature and density with the position have similar trends measured by the two diagnosing methods, indicating that the self-developed probe detection system is effective and reliable in diagnosing the welding arc. It is also found that the diagnosing error of probe detection is a little larger than that of spectral diagnosing, especially in the region near cathode. This research gives a new method to diagnose the welding arc, and the results can give experimental indication and support to researchers in arc welding area from another view sight.

A special probe detection system and analyzing method were designed for estimating the ionization region in welding arc. Results showed that ionization region in gas tungsten welding arc is in spindle shape. Arc plasma prefers to contract near anode workpiece. The arc volume increases with the increase of welding arc current accordingly. With the decrease of arc length, the arc expands in radius direction. Electrical equipotential lines nearly parallel the anode surface and tend to bend to the tungsten electrode in the region near cathode. Voltage drop near the cathode dominates the arc voltage when arc current changes.

We propose $ \mathsf{DeepOPF} $-$ \mathsf{FT}$ as an embedded training approach to design one deep neural network (DNN) for solving multiple AC-OPF problems with flexible topology and line admittances, addressing a critical limitation of learning-based OPF schemes. The idea is to embed the discrete topology representation into the continuous admittance space and train a DNN to learn the mapping from (load, admittance) to the corresponding OPF solution. We then employ the trained DNN to solve AC-OPF problems over any power network with the same bus, generation, and line capacity configurations but different topology and/or line admittances. Simulation results over IEEE 9-/57- bus and a synthetic 2000-bus test cases demonstrate the effectiveness of our design and highlight the training efficiency improvement of $ \mathsf{DeepOPF} $-$ \mathsf{FT}$ over training one DNN for every combination of power network topology and line admittances.

To cope with increasing uncertainty from renewable generation and flexible load, grid operators need to solve alternative current optimal power flow (AC-OPF) problems more frequently for efficient and reliable operation. In this article, we develop a deep neural network (DNN) approach, called DeepOPF, for solving AC-OPF problems in a fraction of the time used by conventional iterative solvers. A key difficulty for applying machine learning techniques for solving AC-OPF problems lies in ensuring that the obtained solutions respect the equality and inequality physical and operational constraints. Generalized a prediction-and-reconstruction procedure in our previous studies, DeepOPF first trains a DNN model to predict a set of independent operating variables and then directly compute the remaining ones by solving the power flow equations. Such an approach not only preserves the power-flow balance equality constraints but also reduces the number of variables to be predicted by the DNN, cutting down the number of neurons and training data needed. DeepOPF then employs a penalty approach with a zero-order gradient estimation technique in the training process toward guaranteeing the inequality constraints. We also drive a condition for tuning the DNN size according to the desired approximation accuracy, which measures its generalization capability. It provides theoretical justification for using DNN to solve AC-OPF problems. Simulation results for IEEE 30/118/300-bus and a synthetic 2000-bus test cases demonstrate the effectiveness of the penalty approach. They also show that DeepOPF speeds up the computing time by up to two orders of magnitude as compared to a state-of-the-art iterative solver, at the expense of $< $0.2% cost difference.

We study a transportation problem where two heavy-duty trucks travel across the national highway from separate origins to destinations, subject to individual deadline constraints. Our objective is to minimize their total fuel consumption by jointly optimizing path planning, speed planning, and platooning configuration. Such a two-truck platooning problem is pervasive in practice yet challenging to solve due to hard deadline constraints and enormous platooning configurations to consider. We first leverage a unique problem structure to significantly simplify platooning optimization and present a novel formulation. We prove that the two-truck platooning problem is weakly NP-hard and admits a Fully Polynomial Time Approximation Scheme (FPTAS). The FPTAS can achieve a fuel consumption within a ratio of $(1+\epsilon)$ to the optimal (for any $\epsilon >0$ ) with a time complexity polynomial in the size of the transportation network and $1/\epsilon $ . These results are in sharp contrast to the general multi-truck platooning problem, which is known to be APX-hard and repels any FPTAS. As the FPTAS still incurs excessive running time for large-scale cases, we design an efficient dual-subgradient algorithm for solving large-/national- scale instances. It is an iterative algorithm that always converges. We prove that each iteration only incurs polynomial-time complexity, albeit it requires solving an integer linear programming problem optimally. We characterize a condition under which the algorithm generates an optimal solution and derive a posterior performance bound when the condition is not met. Extensive simulations based on real-world traces show that our joint solution of path planning, speed planning, and platooning saves up to 24% fuel as compared to baseline alternatives.

We study the problem of minimizing fuel consumption of a heavy-duty truck traveling across the national highway network subject to a hard deadline. We focus on a real-world setting that traversing a road segment is subject to variable speed ranges due to dynamic traffic conditions. The consideration of dynamic traffic conditions not only differentiates our work from existing ones but also allows us to leverage opportunistic driving to improve fuel efficiency. The idea is for the truck to strategically wait (e.g., at highway rest areas) for benign traffic conditions, so as to traverse subsequent road segments at favorable speeds for saving fuel. We observe that traffic conditions and thus speed ranges are mostly stationary within certain duration of the day, and we term them as phases. We formulate the fuel consumption minimization problem under phased speed ranges, considering path planning, speed planning, and opportunistic driving. We prove that the problem is NP-hard, and develop a dual-subgradient algorithm for large-/national- scale instances. We characterize conditions under which the algorithm generates an optimal solution. We carry out simulations based on real-world traces over the US highway system. The results show that our scheme saves up to 20% fuel than a shortest-path based alternative, of which opportunistic driving contributes 13%. Meanwhile, opportunistic driving also reduces driving time by 6% as compared to only optimizing path planning and speed planning. As such, it offers a desirable design option to simultaneously reduce fuel consumption and hours of driving. Last but not least, our results highlight a perhaps surprising observation that dynamic traffic conditions can be exploited to achieve fuel savings even larger than those under stationary traffic conditions.

In this article, we present a robust optimization-based framework for day-ahead reliability assessment (RA) and real-time dispatch to ensure power system reliability under multistage renewable uncertainty. Our framework jointly considers fossil-fuel generators and energy storage in the system. To obtain near-optimal performance in grid reliability, we develop robust multistage decisions based on the concept of “safe-dispatch sets” in the literature. Although such safe-dispatch sets directly answer the RA and real-time dispatch problem, their computation often incurs high computational complexity. To develop low-complexity algorithms, we adopt a divide-and-conquer paradigm. First, we derive the conditions to describe the safe-dispatch sets for a pair of energy storage and generator. The results from this simple building block provide us with useful insights on how the grid reliability is related to the parameters, e.g., the generators’ ramp speeds and the storage capacity. To tackle the general multibus scenario, the uncertainty is split among virtual generator-storage pairs (VGSPs), where we can utilize the results from the one-bus building block. Numerical studies on a standard IEEE 30-bus test case illustrate that our proposed solution requires much lower storage capacity to ensure system reliability compared to state-of-the-art approaches, without renewable curtailment.

We consider the scenario where $N$ utilities strategically bid for electricity in the day-ahead market and balance the mismatch between the committed supply and actual demand in the real-time market, with uncertainty in demand and local renewable generation in consideration. We model the interactions among utilities as a noncooperative game, in which each utility aims atminimizing its per-unit electricity cost. We investigate utilities’ optimal bidding strategies and show that all utilities bidding according to (net load) prediction is a unique pure strategy Nash equilibrium with two salient properties. First, it incurs no loss of efficiency; hence, competition among utilities does not increase the social cost. Second, it is robust and (0, $N-1$) fault immune. That is, fault behaviors of irrational utilities only help to reduce other rational utilities’ costs. The expected market supply–demand mismatch is minimized simultaneously, which improves the planning and supply-and-demand matching efficiency of the electricity supply chain. We prove the results hold under the settings of correlated prediction errors and a general class of real-time spot pricing models, which capture the relationship between the spot price, the day-ahead clearing price, and the market-level mismatch. Simulations based on real-world traces corroborate our theoretical findings. Our article adds new insights to market mechanism design. In particular, we derive a set of fairly general sufficient conditions for the market operator to design real-time pricing schemes so that the interactions among utilities admit the desired equilibrium.

The development of structured lithium metal anodes is a key area of focus in the field of lithium battery research, which can significantly improve the energy density, cycle life and safety of lithium metal batteries. In this study, an electrochemical phase field model is used to construct the total free energy of the electrochemical system in conjunction with the effect of the porous electrode scaffold. It investigates the anisotropy of the diffusion coefficient of lithium ions in the electrolyte and the effect of the gradient size of the porous electrode scaffolds on the lithium deposition within the pores. Our numerical results show that increasing the diffusion coefficient of lithium ions in the x-direction cannot improve the lithium deposition within the pores. Instead, it leads to the appearance of lithium dendrites in the top layer of the porous electrode. Appropriately increasing the diffusion coefficient of lithium ions in the y-direction can significantly increase the lithium deposition capacity within the pores. However, excessive increases can lead to a reversal of the lithium deposition capacity within the pores. In addition, adopting the gradient size of the porous electrode scaffold in the y-direction can effectively alleviate the phenomenon that lithium metal is preferentially deposited at the top of the scaffold. These findings provide new ideas for the future design of structured lithium metal anode batteries.

AbstractTo investigate the strengthening effect of fiber nets on the seismic behavior of brick masonry walls, carbon fiber nets (CFN), glass fiber nets (GFN) and basalt fiber nets (BFN) were applied to strengthen masonry walls with an external sticking method. Pseudo-static tests were carried out on eight walls with different strengthening conditions: one was not strengthened; six were strengthened on one side or both sides with CFN, GFN and BFN, respectively; and one was strengthened with CFN on both sides and then riveted with steel plates. The results showed that fiber nets could exchange the failure mode of the walls from shear failure to bending failure. The bearing capacity, energy consumption and ductility of the strengthened walls were improved, and the improvement of double-sided reinforcement was more notable. Epoxy polymer mortar is more suitable for masonry structure strengthened with fiber nets than acrylic polymer mortar because it can ensure the full participation of fiber nets. In addition, a calculation formula for the design value of seismic shear capacity of masonry walls strengthened with fiber nets was deduced, which can effectively predict the shear capacity of walls strengthened with fiber nets.

In this paper, a novelty fiber transmission model consisting of cascaded neural networks with the multi-head attention mechanism has been put forward to solve signal transmission prediction problems in multi-span long-haul fiber link. After appropriately training the model with collected data by the gradient descent method, it can gradually handle the rules of signals’ changes over each span and predict the signal transmission results with notably low time cost compared with traditional split-step Fourier method based long-haul model. Through numerical demonstration, this new model can predict 1000 km fiber link with symbol rate up to 40GBaud in the QAM modulation with extremely low predicting error.

Prenylemestrins A and B (1and 2, respectively), two unusual epipolythiodioxopiperazines featuring a thioethanothio bridge instead of a polysulfide bridge, were isolated from the fungus Emericellasp. CPCC 400858 guided by genomic analysis. Their structures were determined by extensive spectroscopic data, NMR and ECD calculations, and X-ray diffraction analysis. A plausible biosynthetic pathway for 1and 2was proposed on the basis of gene cluster analysis. Prenylemestrins A and B exhibited cytotoxicities against human chronic myelocytic leukemia cell lines K562 and MEG-01.

β-Ti dendrite toughened metal glass composite and TC4 titanium alloy were butt welded by a pulsed laser. Microstructures and mechanical properties of the welded joint were specially studied. Results show that microstructure in the fusion zone is uneven, and mainly consists of dendritical β-Ti grains (in nanometre or micron scales) and amorphous alloy background. Special chemical compositions of base materials, shocking effect from laser pulses and large cooling speed during welding directly restrain the development of crystal β-Ti grain in the fusion zone. Hardness in the fusion zone ranges from 500 HV to more than 600 HV. During tensile tests, all the welded joints fracture on TC4 titanium alloy base material side.

Graphical abstract: (a) The mechanical properties of AlxCoCrFeNi2.1alloys at room temperature: tensile strain–stress curves of Al0.5–Al1.1 alloys. A novel “coral”-like pseudoeutectic structure was detected in Al1.1CoCrFeNi2.1alloy. This microstructure consists of BCC/B2 and FCC phases with volume ratio close to 1:1, brings both higher elongation (15%) and fracture strength (1371 MPa) than that of AlCoCrFeNi2.1EHEA (13% and 1198 MPa, respectively)

Highly active transition metal nitrides are desirable for electrocatalytic reactions, but their long-term stability is still unsatisfactory and thus limiting commercial applications. Herein, for the first time, we report a unique and universal room-temperature urea plasma method for controllable synthesis of N-doped carbon coated metal (Fe, Co, Ni, etc.) nitrides arrays electrocatalysts. The preformed metal oxides arrays can be successfully converted into metal nitrides arrays with preserved nanostructures and a thin layer of N-doped carbon (NC) viaone-step urea plasma. Typically, as a representative case, NC@CoN nanowire arrays are illustrated and corresponding formation mechanism by plasma is proposed. Notably, the designed NC@CoN catalysts deliver excellent electrocatalytic activity and long-term stability both in oxygen evolution reaction (OER) and urea oxidation reaction (UOR). For OER, a low overpotential (264 mV at 10 mA/cm2) and high stability (>50 h at 20  mA/cm2) are acquired. For UOR, a current density of 100 mA/cm2is achieved at only 1.39 V and maintain over 100 h. Theoretical calculations reveal that the synergetic coupling effect of CoN and NC can significantly facilitate the charge-transfer process, optimize adsorbed intermediates binding strength and further greatly decrease the energy barrier. This strategy provides a novel method for fabrication of NC@ metal nitrides as highly active and stable catalysts.

MS/MS-based molecular networking strain prioritization led to the discovery of a group of cyclic depsipeptides from an endolichenic Xylariasp. The main component, xylaroamide A (1), was obtained by LC-MS-guided isolation. The planar structure of compound 1was elucidated via 1D and 2D NMR, as well as MS/MS data. The configurations were fully determined by the combination of advanced Marfey’s analysis, partial hydrolysis, Mosher’s reaction, and GIAO NMR calculation based on a restricted conformational search. A plausible biosynthetic pathway for xylaroamide A (1) involving a rare trans-acting N-methyltransferase is proposed based on bioinformatics analysis. Xylaroamide A (1) exhibited inhibitory activity against cancer cell lines BT-549 and RKO with IC50values of 2.5 and 9.5 μM, respectively.

PVDF solid electrolytes with excellent electrochemical stability, thermal stability and mechanical properties are promising to replace liquid electrolyte using in high performance and security solid lithium batteries.

Optical random speckle encoding suffers from a contradiction between the generation speed and pattern amount. Spatial light modulators are commonly used for random speckle generation at relatively low speeds. Wavelength scanning combined with a scattering medium has a fast speed, while the pattern amount is limited by the optical bandwidth. To increase the performance of optical random speckle encoding, a novel, to the best of our knowledge, scheme combining wavelength and phase hybrid modulation is proposed and demonstrated. Through optical encoding in the two dimensions of wavelength and phase, the number of speckle patterns can reach one million, which is over 10,000 times that generated by only wavelength scanning. This scheme can be used in ghost imaging systems to increase the resolution of reconstructed images.

The superior surface electron energy levels of WP2NWs facilitate the proton-coupled charge transfer dynamics between the adsorbed N2and WP2, leading to superior NRR catalytic activity.

We propose and demonstrate a hybrid modulation bandwidth enhanced self-injection locking laser by butt coupling a commercial distributed feedback laser with an external high-Q silicon nitride microring reflector (MRR). The MRR keeps the laser in strong self-injection locking state with photon–photon resonance, which can realize direct modulation bandwidth enhanced and stable narrow linewidth single-mode output. With the further optimization of MRR parameters, the 3-dB modulation bandwidth and the linewidth of the hybrid laser are enhanced to 15.28 GHz from 7.70 GHz and narrowed to 4 kHz from 600 kHz, respectively. This work makes full use of the advantages of self-injection and integrated photonic technology, which has potential applications in many fields.

The two-step backward difference formula (BDF) method on variable grids for parabolic equations with self-adjoint elliptic part is considered. Standard stability estimates for adjacent time-step ratios rj:=kj/kj-1⩽1.8685and 1.9104, respectively, have been proved by Becker (BIT 38:644–662, 1998) and Emmrich (J Appl Math Comput 19:33–55, 2005) by the energy technique with a single multiplier. Even slightly improving the ratio is cumbersome. In this paper, we present a novel technique to examine the positive definiteness of banded matrices that are neither Toeplitz nor weakly diagonally dominant; this result can be viewed as a variant of the Grenander–Szegő theorem. Then, utilizing the energy technique with two multipliers, we establish stability for adjacent time-step ratios up to 1.9398.

Dissimilar Ti-based amorphous alloy sheets were butt welded by a pulsed laser and metallurgical joints were obtained. The ß-Ti crystal grains in nanometre scale unevenly distribute on the amorphous background in the fusion zone. With the increase of laser pulse energy and pulse duration, the crystalline ß-Ti grains grow up from spherical to dendritical profile, but the crystalline size reaches its maximum of about 1?µm, which is much smaller than the grains in base metal. The refinement of the grains in fusion zone results from the fast cooling speed during welding. The microhardness in the welded joints ranges from 470 to 525?HV. Average tensile strength of the welded joint is about 1510?MPa (86% of pure Ti-based amorphous alloy BM and 91% of ß-Ti dendrite reinforced Ti-based amorphous alloy BM).

Seven new β-caryophyllene derivatives, pestalotiphains A–G (1–7), along with six known analogues (8–13), were isolated from the plant-associated Pestalotiopsis hainanensis. Compound 1represents the first example of a caryophyllene–adenine hybrid, and 2contains a novel oxatricyclo[4.3.1.0] system. Their structures and absolute configurations were assigned by interpretation of a combination of spectroscopic data and electronic circular dichroism calculations. Compound 8exhibited moderate inhibition of HL-60 and THP-1 cell lines (IC50, 6.2 and 2.0 μM, respectively). A candidate biosynthetic gene cluster responsible for these compounds was uncovered by bioinformatics analyses and confirmed by a biochemical approach.

In this work, the influence of pulse frequency on the corrosion resistance of Cu–Zn binary alloy has been investigated by using electrochemical workstation, scanning electron microscope and X-ray diffraction. The results have shown that after the electric pulse treatment, the average grain size in the microstructure of high-zinc binary brass decreased and the corrosion resistance increased. The thickness of dezincification layer decreased from 49.8 to 30.8 µm. The diameter of capacitive reactance arc increased from 741.1 to 2898.0 µm. The corrosion potential increased from −0.2719 to −0.2378 V, and the corrosion current density decreased from 6.3147 × 10−6to 4.6971 × 10−7A cm−2by one magnitude order.

In this article, we develop online multistage decisions for procuring and dispatching generators with diverse capabilities to provably ensure reliability of power grid operations under high renewable uncertainty. We jointly consider both the day-ahead reliability assessment commitment (RAC) and the real-time dispatch problems. We first focus on the real-time dispatch problem and define “maximally robust algorithms,” in the sense that they are not dominated by any other algorithm in terms of reliability. We characterize a class of maximally robust algorithms using the concept of “safe dispatch set,” which also provides conditions for verifying grid reliability for RAC. However, in general, such safe dispatch sets may be difficult to compute. We then develop efficient computational algorithms for characterizing the safe dispatch sets. Specifically, for a simpler single-bus two-generator case, we show that the safe dispatch sets can be exactly characterized by a polynomial number of convex constraints. Then, based on this two-generator characterization, we develop a new solution for the multibus multigenerator case using the idea of virtual demand splitting (VDS), which can effectively compute a suitable subset of the safe dispatch set. A distinct advantage of our proposed approach is that it intelligently exploits the complementary capabilities of generators with different ramping capabilities, and thus leads to a larger safe dispatch set than existing approaches in the literature based purely on affine policies. Our numerical results on an IEEE 30-bus system demonstrate that a VDS-based solution outperforms the standard approaches in the literature in terms of reliability, without sacrificing economy.

The recently discovered antibiotic burnettramic acid A (1) and three new congeners, burnettramic acids C–E (2–4), were identified from the co-cultures of two marine Aspergillusstrains. The structure of burnettramic acid A was revised on the basis of reinterpretation of the nuclear magnetic resonance (NMR) data and chemical derivatization. The full absolute configurations of burnettramic acids were established using the Mosher ester method and Marfey’s analysis, combined with density functional theory calculation of NMR and electric circular dichroism data.

In this article, hybrid functional B3LYP method is used to construct the reactant structure of energetic components in propellant at the bhandhlyp/6-31g(d) level, and to calculate the closed-shell layer of the system. At the bhandhlyp/6-31g(d) level, the energy difference (activation energy) between the transition state and the reactant was calculated and the reaction mechanism between energetic components was analyzed. It is found that the O30atom of RDX first breaks off from the nitro group and is easier to break away from RDX and interact with the vertex atom Al1of the Al13cluster. With the further separation of O30, it also acts with Al11until it completely breaks away from N26atom. The activation energy of this reaction is 56.448 × 103J mol−1. The oxygen dioxide atom in ammonium perchlorate is more likely to interact with the Al11atom of the Al13cluster. With the reaction proceeding, the O22atom will not completely separate from the Cl19atom. The activation energy of the reaction is 27.830 × 103J mol−1.

As an emerging paradigm in distributed power systems, microgrids provide promising solutions to local renewable energy generation and load demand satisfaction. However, the intermittency of renewables and temporal uncertainty in electrical load create great challenges to energy scheduling, especially for small-scale microgrids. Instead of deploying stochastic models to cope with such challenges, this paper presents a retroactive approach to real-time energy scheduling, which is prediction-independent and computationally efficient. Extensive case studies were conducted using 3-year-long real-life system data, and the results of simulations show that the cost difference between the proposed retroactive approach and perfect dispatch is less than 11% on average, which suggests better performance than model predictive control with the cost difference at 30% compared to the perfect dispatch.

Flexible batteries with large energy densities, lightweight nature, and high mechanical strength are considered as an eager goal for portable electronics. Herein, we first propose free-standing graphene fiber electrodes containing roller-like orientated spore carbon spheres via rheological engineering. With the help of the orientated microfluidic cospinning technology and the plasma reduction method, spore carbon spheres are self-assembled and orientedly dispersed into numerous graphene flakes, forming graphene fiber electrodes enriched with internal rolling woven structures, which cannot only enhance the electrical contact between active materials but also effectively improve the mechanical strength and structure stability of graphene fiber electrodes. When the designed graphene fibers are combined with the active sulfur cathode and lithium metal anode, the assembled flexible lithium sulfur batteries possess superior electrochemical performance with high capacity (>1000 mA h g–1) and excellent cycling life as well as good mechanical properties. According to density functional theory and COMSOL simulations, the roller-like spore carbon sphere-orientated graphene fiber hosts provide reinforced trapping-catalytic-conversion behavior to soluble polysulfides and nucleation active sites to lithium metal, thus synergistically suppressing the shuttle effect of polysulfides at the cathode side and lithium dendrite growth at the anode side, thereby boosting the whole electrochemical properties of lithium sulfur batteries.

Raistrickindole A (1), a new indole diketopiperazine alkaloid containing an unusual pyrazino[1′,2′:2,3][1,2]oxazino[6,5-b]indole tetraheterocyclic ring system, a new benzodiazepine derivative, raistrickin (2), and the known haenamindole (3) and sclerotigenin (4) were isolated from the marine-derived fungus Penicillium raistrickiiIMB17-034. Their structures were elucidated by extensive spectroscopic analyses and TDDFT calculations of the NMR and ECD data. Compounds 1and 2showed inhibitory activities against the hepatitis C virus.

Lithium (Li) metal batteries (LMBs) have garnered significant research attention due to their high energy density. However, uncontrolled Li dendrite growth and the continuous accumulation of “dead Li” directly lead to poor electrochemical performance in LMBs, along with serious safety hazards. These issues have severely hindered their commercialization. In this study, a lithiophilic layer of Sn-Cu2O is constructed on the surface of copper foam (CF) grown with Cu nanowire arrays (SCCF) through a combination of electrodeposition and plasma reduction. Sn-Cu2O, with excellent lithiophilicity, reduces the Li nucleation barrier and promotes uniform Li deposition. Simultaneously, the high surface area of the nanowires reduces the local current density, further suppressing the Li dendrite growth. Therefore, at 1 mA cm–2, the half cells and symmetric cells achieve high Coulombic efficiency (CE) and stable operation for over 410 cycles and run smoothly for more than 1350 h. The full cells using an LFP cathode demonstrate a capacity retention rate of 90.6% after 1000 cycles at 5 C, with a CE as high as 99.79%, suggesting excellent prospects for rapid charging and discharging and long-term cyclability. This study provides a strategy for modifying three-dimensional current collectors for Li metal anodes, offering insights into the construction of stable, safe, and fast-charging LMBs.

Silicon (Si) is considered as one of the most promising anode materials for advanced lithium-ion batteries due to its high theoretical capacity, environmental friendliness, and widespread availability. However, great challenges such as volumetric expansion, limited ionic/electronic conductivity properties and complex manufacturing processes hinder its practical applications. Herein, a novel plasma-enhanced reduced graphene oxide fibers/Si (PrGOFs/Si) composite anode is first proposed by using wet-spinning technology followed by plasma-enhanced reduction method. The PrGOFs provide large space to accommodate the volume expansion of Si nanoparticles (SiNPs) by forming a flexible 3D conductive network. Compared to the conventional thermally reduced graphene oxide fibers/Si (TrGOFs/Si) sample, the PrGOFs/Si anodes demonstrate higher conductivity, specific surface area, and superior fabrication efficiency. Accordingly, the PrGOFs/Si anodes exhibit a reversible capacity of 698.3 mAh/g, and maintain a specific capacity of 602.5 mAh/g at a current density of 200 mA/g after 100 cycles, superior to conventional TrGOFs/Si counterparts. This research presents a novel strategy for the preparation of high-performance Si/carbon anodes for energy storage applications.

The microstructure and tensile properties of Fe x CoCrNiMn high-entropy alloys (HEAs) were investigated. It was found that the Fe x CoCrNiMn HEA has a single face-centered cubic (fcc) structure in a wide range of Fe content. Further increasing the Fe content endowed the Fe x CoCrNiMn alloys with an fcc/body-centered cubic (bcc) dual-phase structure. The yield strength of the Fe x CoCrNiMn HEAs slightly decreased with the increase of Fe content. An excellent combination of strength and ductility was achieved in the Fe x CoCrNiMn HEA with higher Fe content, which can be attributed to the outstanding deformation coordination capability of the fcc/bcc dual phase structure. [ABSTRACT FROM AUTHOR]

Single-shot ultrafast photography is a powerful tool for science research and industry applications. In this Letter, a novel strategy for ultrafast imaging of two-dimensional complex (amplitude and phase) objects, which is termed single-shot ultrafast phase retrieval photography (SUP), is proposed and demonstrated. The key component of SUP is a silicon photonic integrated chip, which not only has the function of multi-angle illumination, but also provides ultra-short delays for each illumination source. Combined with an ultra-short pulse source and coherent diffraction imaging, SUP can realize ultrafast single-shot imaging. As a proof of concept, the self-developed multiplexed time delay illumination chip was used for experiments, and we demonstrated the reconstructing of a static complex-valued object with a frame sequence depth of 16 frames from single-shot ptychographic data.

Isocoumarindole A (1), a novel polyketide synthetase–nonribosomal peptide synthetase (PKS–NRPS) hybrid metabolite, was isolated from the endolichenic fungus Aspergillussp. CPCC 400810. The structure of isocoumarindole A (1) was featured by an unprecedented skeleton containing chlorinated isocoumarin and indole diketopiperazine alkaloid moieties linked by a carbon–carbon bond, which was determined by a combination of spectroscopic analyses, Marfey’s method, and calculations of NMR chemical shifts, ECD spectra, and optical rotation values. Isocoumarindole A showed significant cytotoxicity and mild antifungal activities.

Resolving the structure–property relationships of two-dimensional (2D) organic–inorganic hybrid perovskites is essential for the development of photovoltaic and photoelectronic devices. Here, pressure (0–10 GPa) was applied to 2D hybrid perovskite flakes mechanically exfoliated from butylammonium lead halide single crystals, (C4H9NH3)2PbI4, from which we observed a series of changes of the strong excitonic emissions in the photoluminescence spectra. By correlating with in situ high-pressure X-ray diffraction results, we examine successfully the relationship between structural modifications in the inorganic PbI42–layer and their excitonic properties. During the transition between Pbca(1b) phase and Pbca(1a) phase at around 0.1 GPa, the decrease in ⟨Pb–I–Pb⟩ bond angle and increase in Pb–I bond length lead to an abrupt blue shift of the excitonic bandgap. The presence of the P21/aphase above 1.4 GPa increases the ⟨Pb–I–Pb⟩ bond angle and decreases the Pb–I bond length, leading to a deep red shift of the excitonic bandgap. The total band gap narrowing of ∼350 meV to 2.03 eV at 5.3 GPa before amorphization, facilitates (C4H9NH3)2PbI4as a much better solar absorber. Moreover, phase transitions inevitably modify the carrier lifetime of (C4H9NH3)2PbI4, where an initial 150 ps at ambient phase is prolongated to 190 ps in the Pbca(1a) phase along with enhanced photoluminescence (PL), originating from pressure-induced strong radiative recombination of trapped excitons.The onset of P21/aphase shortens significantly the carrier lifetime to 53 ps along with a weak PL emission due to pressure-induced severe lattice distortion and amorphization. High-pressure study on (C4H9NH3)2PbI4nm-thin flakes may provide insights into the mechanisms for synthetically designing novel 2D hybrid perovskite based photoelectronic devices and solar cells.

An opto-electronic oscillator based on guided acoustic wave Brillouin scattering in a photonic crystal fiber (PCF) stimulated by a light wave in 1 μm band is proposed and demonstrated. A short length of a homemade PCF stimulated by relatively low pump power leads to strong coupling between the pump and probe waves. The oscillation is realized in a feedback loop, in which the acoustic wave bridges the pump and probe. Oscillation is achieved at 1.237 GHz, which matches the resonance of the acoustic mode, in a single-longitudinal-mode operation of the hybrid cavity. It has a high side mode suppression ratio of over 60 dB.