Carrier-envelope phase effects on high-harmonic generation driven by mid-infrared laser field

The influence of the carrier-envelope phase on high-harmonic generation is investigated, both experimentally and theoretically, for three different interaction gas media, driven by mid-infrared, few-cycle and CEP-stabiUzed laser pulses. Different patterns of harmonic spectra with varying CEP for the three interaction gas media are observed. Furthermore, in comparing our experiment results to the previous works driven by near-infrared laser pulses, different phenomena are found. Through numerical simulation, we find that for the two different kinds of driving fields, i.e. mid-infrared and near-infrared laser pulses, different kinds of electron trajectories contribute to the generation of high harmonics.

Exploration of High-Harmonic Generation from the CS2 Molecule by the Lewenstein Method in Two-Color Circularly Polarized Laser Field

The high harmonic generation (HHG) from the CS2 molecule in intense laser fields is investigated using the extended Lewenstein method. The initial state is the highest-occupied molecular orbital of the CS2 molecule, which can be well described by Gaussian wave packet using GAMESS-UK package. Compared with the case of the elliptical laser, the HHG can be extended in two-color circularly polarized laser field. The time-frequency analysis and classical electron trajectory as well as the ionization yield curve are also presented to further explain the underlying mechanism. After adding a static electric field on the z-direction, the single quantum path control is realized and the supercontinuum spectra are obtained. Moreover, an isolated 110 as pulse can be obtained by superposing the harmonics from 130th to 180th order.

Distinguishing high-harmonic generation from surface and bulk states in topological insulator Bi_(2)Se_(3)

We demonstrated a scheme to differentiate the high-harmonic generation[HHG)originating from the surface states and bulk states of the topological insulator Bi_(2)Se_(3).By adopting two-color mid-infrared laser fields on Bi_(2)Se_(3),we found that the nonlinear response sensitively depends on the relative phase of the driving fields.The even harmonics arise from the surface states with a clear signature,whose modulation period equals the cycle of the second-harmonic generation[SHG]field.We reveal that the weak SHG perturbs the nontrivial dipole phase of the electron-hole pair in surface states,and thus leads to the modulation of HHG.It provides a means to manipulate the ultrafast dynamics in surface states through adopting a weak perturbing laser field.

Even-order high-harmonic generation from solids in velocity gauge

We present a velocity-gauge model for the generation of even-order high harmonics, and reveal that the even-order harmonics originate from the multiple-step transitions among the energy bands in momentum space, while the odd-order harmonics are mainly from direct transitions. The lower valence band is found vital for the generation of even harmonics. Relative intensity of even-order harmonics versus the odd orders is calculated and shows a growing trend as the laser field amplitude increases.

Wave mixing and high-harmonic generation enhancement by a two-color field driven dielectric metasurface[Invited]

High-harmonic generation in metasurfaces,driven by strong laser fields,has been widely studied.Compared to plasma,all-dielectric nanoscale metasurfaces possess larger nonlinearity response and higher damage threshold.Additionally,it can strongly localize the driven field,greatly enhancing its peak amplitude.In this work,we adopt a Fano resonant micronano structure with transmission peaks at different wavelengths and explore its nonlinear response by both single and twocolor pump fields.Compared to the high-order harmonics induced by the first resonant wavelength,the intensity of the high-harmonic radiation results is enhanced by one order of magnitude,when the metasurface is driven by various resonant and non-resonant wavelength combinations of a two-color field.

Resonantly enhanced second-and third-harmonic generation in dielectric nonlinear metasurfaces

Nonlinear dielectric metasurfaces provide a promising approach to control and manipulate frequency conversion optical processes at the nanoscale,thus facilitating both advances in fundamental research and the development of new practical applications in photonics,lasing,and sensing.Here,we employ symmetry-broken metasurfaces made of centrosymmetric amorphous silicon for resonantly enhanced second-and third-order nonlinear optical response.Exploiting the rich physics of optical quasi-bound states in the continuum and guided mode resonances,we comprehensively study through rigorous numerical calculations the relative contribution of surface and bulk effects to second-harmonic generation(SHG)and the bulk contribution to third-harmonic generation(THG) from the meta-atoms.Next,we experimentally achieve optical resonances with high quality factors,which greatly boosts light-matter interaction,resulting in about 550 times SHG enhancement and nearly 5000-fold increase of THG.A good agreement between theoretical predictions and experimental measurements is observed.To gain deeper insights into the physics of the investigated nonlinear optical processes,we further numerically study the relation between nonlinear emission and the structural asymmetry of the metasurface and reveal that the generated harmonic signals arising from linear sharp resonances are highly dependent on the asymmetry of the meta-atoms.Our work suggests a fruitful strategy to enhance the harmonic generation and effectively control different orders of harmonics in all-dielectric metasurfaces,enabling the development of efficient active photonic nanodevices.

High-Harmonic Generation and Correlated Electron Emission from Relativistic Plasma Mirrors at 1 kHz Repetition Rate

We report evidence for the first generation of XUV spectra from relativistic surface high-harmonic generation(SHHG)on plasma mirrors at a kilohertz repetition rate,emitted simultaneously with energetic electrons.SHHG spectra and electron angular distributions are measured as a function of the experimentally controlled plasma density gradient scale length Lg for three increasingly short and intense driving pulses:24 fs and a0=1:1,8 fs and a0=1:6,and finally 4 fs and a0≈2:1,where a0 is the peak vector potential normalized by mec/e with the elementary charge e,the electron rest mass me,and the vacuum light velocity c.For all driver pulses,we observe correlated relativistic SHHG and electron emission in the range Lg∈½λ/20,λ/4,with an optimum gradient scale length of Lg≈λ/10.This universal optimal Lg-range is rationalized by deriving a direct intensity-independent link between the scale length Lg and an effective similarity parameter for relativistic laser-plasma interactions.

In vivo label-free measurement of blood flow velocity symmetry based on dual line scanning third-harmonic generation microscopy excited at the 1700 nm window

Measurement of bloodflow velocity is key to understanding physiology and pathology in vivo.While most measurements are performed at the middle of the blood vessel,little research has been done on characterizing the instantaneous bloodflow velocity distribution.This is mainly due to the lack of measurement technology with high spatial and temporal resolution.Here,we tackle this problem with our recently developed dual-wavelength line-scan third-harmonic generation(THG)imaging technology.Simultaneous acquisition of dual-wavelength THG line-scanning signals enables measurement of bloodflow velocities at two radially symmetric positions in both venules and arterioles in mouse brain in vivo.Our results clearly show that the instantaneous bloodflow velocity is not symmetric under general conditions.

Quantitative effect of kerogen type on the hydrocarbon generation potential of Paleogene lacustrine source rocks,Liaohe Western Depression,China

Kerogen types exert a decisive effect on the onset and capacity of hydrocarbon generation of source rocks.Lacustrine source rocks in the Liaohe Western Depression are characterized by thick deposition,high total organic carbon(TOC)content,various kerogen types,and a wide range of thermal maturity.Consequently,their hydrocarbon generation potential and resource estimation can be misinterpreted.In this study,geochemical tests,numerical analysis,hydrocarbon generation kinetics,and basin modeling were integrated to investigate the differential effects of kerogen types on the hydrocarbon generation potential of lacustrine source rocks.Optimized hydrocarbon generation and expulsion(HGE)models of different kerogen types were established quantitatively upon abundant Rock-Eval/TOC/vitrinite reflectance(R_(o))datasets.Three sets of good-excellent source rocks deposited in the fourth(Es4),third(Es3),and first(Es1)members of Paleogene Shahejie Formation,are predominantly types I-II_(1),II_(1)-II_(2),and II-III,respectively.The activation energy of types I-II_(2)kerogen is concentrated(180-230 kcal/mol),whereas that of type III kerogen is widely distributed(150-280 kcal/mol).The original hydrocarbon generation potentials of types I,II_(1),II_(2),and III kerogens are 790,510,270,and 85 mg/g TOC,respectively.The Ro values of the hydrocarbon generation threshold for type I-III source rocks gradually increase from 0.42%to 0.74%,and Ro values of the hydrocarbon expulsion threshold increase from 0.49%to 0.87%.Types I and II_(1)source rocks are characterized by earlier hydrocarbon generation,more rapid hydrocarbon expulsion,and narrower hydrocarbon generation windows than types II_(2)and III source rocks.The kerogen types also affect the HGE history and resource potential.Three types(conventional,tight,and shale oil/gas)and three levels(realistic,expected,and prospective)of hydrocarbon resources of different members in the Liaohe Western Depression are evaluated.Findings suggest that the Es3 member has considerable conventional and unconventional hydrocarbon resources.This study can quantitatively characterize the hydrocarbon generation potential of source rocks with different kerogen types,and facilitate a quick and accurate assessment of hydrocarbon resources,providing strategies for future oil and gas exploration.

Multi-objective optimization and evaluation of supercritical CO_(2) Brayton cycle for nuclear power generation

The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.

Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning

The corrosion rate is a crucial factor that impacts the longevity of materials in different applications.After undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion rate.However,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still lacking.The current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 alloy.The Taguchi L27 design of experiments was used for the experimental analysis.In addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion rate.The shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified factors.This study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.

Harnessing overlapped temperature-salinity gradient in solar-driven interfacial seawater evaporation for efficient steam and electricity generation

Solar-driven interfacial water evaporation(SIWE)offers a superb way to leverage concentrated solar heat to minimize energy dissipation during seawater desalination.It also engenders overlapped temperaturesalinity gradient(TSG)between water-air interface and adjacent seawater,affording opportunities of harnessing electricity.However,the efficiency of conventional SIWE technologies is limited by significant challenges,including salt passivation to hinder evaporation and difficulties in exploiting overlapped TSG simultaneously.Herein,we report self-sustaining hybrid SIWE for not only sustainable seawater desalination but also efficient electricity generation from TSG.It enables spontaneous circulation of salt flux upon seawater evaporation,inducing a self-cleaning evaporative interface without salt passivation for stable steam generation.Meanwhile,this design enables spatial separation and simultaneous utilization of overlapped TSG to enhance electricity generation.These benefits render a remarkable efficiency of90.8%in solar energy utilization,manifesting in co-generation of solar steam at a fast rate of 2.01 kg m^(-2)-h^(-1)and electricity power of 1.91 W m^(-2)with high voltage.Directly interfacing the hybrid SIWE with seawater electrolyzer constructs a system for water-electricity-hydrogen co-generation without external electricity supply.It produces hydrogen at a rapid rate of 1.29 L h^(-1)m^(-2)and freshwater with 22 times lower Na+concentration than the World Health Organization(WHO)threshold.

Identifying multidisciplinary problems from scientific publications based on a text generation method

Purpose:A text generation based multidisciplinary problem identification method is proposed,which does not rely on a large amount of data annotation.Design/methodology/approach:The proposed method first identifies the research objective types and disciplinary labels of papers using a text classification technique;second,it generates abstractive titles for each paper based on abstract and research objective types using a generative pre-trained language model;third,it extracts problem phrases from generated titles according to regular expression rules;fourth,it creates problem relation networks and identifies the same problems by exploiting a weighted community detection algorithm;finally,it identifies multidisciplinary problems based on the disciplinary labels of papers.Findings:Experiments in the“Carbon Peaking and Carbon Neutrality”field show that the proposed method can effectively identify multidisciplinary research problems.The disciplinary distribution of the identified problems is consistent with our understanding of multidisciplinary collaboration in the field.Research limitations:It is necessary to use the proposed method in other multidisciplinary fields to validate its effectiveness.Practical implications:Multidisciplinary problem identification helps to gather multidisciplinary forces to solve complex real-world problems for the governments,fund valuable multidisciplinary problems for research management authorities,and borrow ideas from other disciplines for researchers.Originality/value:This approach proposes a novel multidisciplinary problem identification method based on text generation,which identifies multidisciplinary problems based on generative abstractive titles of papers without data annotation required by standard sequence labeling techniques.

The application of cellulosic-based materials on interfacial solar steam generation for highly efficient wastewater purification: A review

The world's population is growing,leading to an increasing demand for freshwater resources for drinking,sanitation,agriculture,and industry.Interfacial solar steam generation(ISSG)can solve many problems,such as mitigating the power crisis,minimizing water pollution,and improving the purification and desalination of seawater,rivers/lakes,and wastewater.Cellulosic materials are a viable and ecologically sound technique for capturing solar energy that is adaptable to a range of applications.This review paper aims to provide an overview of current advancements in the field of cellulose-based materials ISSG devices,specifically focusing on their applications in water purification and desalination.This paper examines the cellulose-based materials ISSG system and evaluates the effectiveness of various cellulosic materials,such as cellulose nanofibers derived from different sources,carbonized wood materials,and two-dimensional(2D)and 3D cellulosic-based materials from various sources,as well as advanced cellulosic materials,including bacterial cellulose and cellulose membranes obtained from agricultural and industrial cellulose wastes.The focus is on exploring the potential applications of these materials in ISSG devices for water desalination,purification,and treatment.The function,advantages,and disadvantages of cellulosic materials in the performance of ISSG devices were also deliberated throughout our discussion.In addition,the potential and suggested methods for enhancing the utilization of cellulose-based materials in the field of ISSG systems for water desalination,purification,and treatment were also emphasized.

Amphipathic Janus Nanofibers Aerogel for Efficient Solar Steam Generation

Solar steam generation is a promising water purification technology due to its low-cost and environmentally friendly applications in water purification and desalination.However,hydrophilic or hydrophobic materials alone are insufficient in achieving necessary characteristics for constructing highquality solar steam generators with good comprehensive properties.Herein,novel hydrophile/hydrophobe amphipathic Janus nanofibers aerogel is designed and used as a host material for preparing solar steam generators.The product consists of an internal cubic aerogel and an external layer of photothermal materials.The internal aerogel is composed of electrospun amphipathic Janus nanofibers.Owing to the unique composition and structure,the prepared solar steam generator integrates the features of high water evaporation rate(2.944 kg m^(-2)h^(-1)under 1 kW m^(-2)irradiation),selffloating,salt-resisting,and fast performance recovery after flipping.Moreover,the product also exhibits excellent properties on desalination and removal of organic pollutants.Compared with traditional hydrophilic aerogel host material,the amphipathic Janus nanofibers aerogel brings much higher water evaporation rate and salt resistance.

A Railway Fastener Inspection Method Based on Abnormal Sample Generation

Regular fastener detection is necessary to ensure the safety of railways.However,the number of abnormal fasteners is significantly lower than the number of normal fasteners in real railways.Existing supervised inspectionmethods have insufficient detection ability in cases of imbalanced samples.To solve this problem,we propose an approach based on deep convolutional neural networks(DCNNs),which consists of three stages:fastener localization,abnormal fastener sample generation based on saliency detection,and fastener state inspection.First,a lightweight YOLOv5s is designed to achieve fast and precise localization of fastener regions.Then,the foreground clip region of a fastener image is extracted by the designed fastener saliency detection network(F-SDNet),combined with data augmentation to generate a large number of abnormal fastener samples and balance the number of abnormal and normal samples.Finally,a fastener inspection model called Fastener ResNet-8 is constructed by being trained with the augmented fastener dataset.Results show the effectiveness of our proposed method in solving the problem of sample imbalance in fastener detection.Qualitative and quantitative comparisons show that the proposed F-SDNet outperforms other state-of-the-art methods in clip region extraction,reaching MAE and max F-measure of 0.0215 and 0.9635,respectively.In addition,the FPS of the fastener state inspection model reached 86.2,and the average accuracy reached 98.7%on 614 augmented fastener test sets and 99.9%on 7505 real fastener datasets.

Efficient C-N coupling in electrocatalytic urea generation on copper carbonate hydroxide electrocatalysts

Urea generation through electrochemical CO_(2) and NO_(3)~-co-reduction reaction(CO_(2)NO_(3)RR)is still limited by either the low selectivity or yield rate of urea.Herein,we report copper carbonate hydroxide(Cu_2(OH)_2CO_(3))as an efficient CO_(2)NO_(3)RR electrocatalyst with an impressive urea Faradaic efficiency of45.2%±2.1%and a high yield rate of 1564.5±145.2μg h~(-1)mg_(cat)~(-1).More importantly,H_(2) evolution is fully inhibited on this electrocatalyst over a wide potential range between-0.3 and-0.8 V versus reversible hydrogen electrode.Our thermodynamic simulation reveals that the first C-N coupling follows a unique pathway on Cu_2(OH)_2CO_(3) by combining the two intermediates,~*COOH and~*NHO.This work demonstrates that high selectivity and yield rate of urea can be simultaneously achieved on simple Cu-based electrocatalysts in CO_(2)NO_(3)RR,and provide guidance for rational design of more advanced catalysts.

Enhanced picosecond terahertz wave generation based on cascade effects in a terahertz parametric generator

Enhanced terahertz wave generation via a Stokes cascade process has been demonstrated using picosecond pulse pumped terahertz parametric generation at 1 kHz repetition rate.Clear cascade saturation of terahertz output was observed,and the corresponding cascade-Stokes spectra were analyzed.The maximum terahertz wave average power was 22μW under a pump power of 30 W,whereas the maximum power conversion efficiency was 8×10^(-7)under a pump power of 21 W.The THz power fluctuation was measured to be about 1%in 20 min.This THz parametric source with a relatively stable output is suitable for a variety of practical applications.

Automatic Generation of Attribute-Based Access Control Policies from Natural Language Documents

In response to the challenges of generating Attribute-Based Access Control(ABAC)policies,this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents.This method is aimed at organizations such as companies and schools that are transitioning from traditional access control models to the ABAC model.The manual retrieval and analysis involved in this transition are inefficient,prone to errors,and costly.Most organizations have high-level specifications defined for security policies that include a set of access control policies,which often exist in the form of natural language documents.Utilizing this rich source of information,our method effectively identifies and extracts the necessary attributes and rules for access control from natural language documents,thereby constructing and optimizing access control policies.This work transforms the problem of policy automation generation into two tasks:extraction of access control statements andmining of access control attributes.First,the Chat General Language Model(ChatGLM)isemployed to extract access control-related statements from a wide range of natural language documents by constructing unique prompts and leveraging the model’s In-Context Learning to contextualize the statements.Then,the Iterated Dilated-Convolutions-Conditional Random Field(ID-CNN-CRF)model is used to annotate access control attributes within these extracted statements,including subject attributes,object attributes,and action attributes,thus reassembling new access control policies.Experimental results show that our method,compared to baseline methods,achieved the highest F1 score of 0.961,confirming the model’s effectiveness and accuracy.

Automatic Generation of Artificial Space Weather Forecast Product Based on Sequence-to-sequence Model

Both analyzing a large amount of space weather observed data and alleviating personal experience bias are significant challenges in generating artificial space weather forecast products.With the use of natural language generation methods based on the sequence-to-sequence model,space weather forecast texts can be automatically generated.To conduct our generation tasks at a fine-grained level,a taxonomy of space weather phenomena based on descriptions is presented.Then,our MDH(Multi-Domain Hybrid)model is proposed for generating space weather summaries in two stages.This model is composed of three sequence-to-sequence-based deep neural network sub-models(one Bidirectional Auto-Regressive Transformers pre-trained model and two Transformer models).Then,to evaluate how well MDH performs,quality evaluation metrics based on two prevalent automatic metrics and our innovative human metric are presented.The comprehensive scores of the three summaries generating tasks on testing datasets are 70.87,93.50,and 92.69,respectively.The results suggest that MDH can generate space weather summaries with high accuracy and coherence,as well as suitable length,which can assist forecasters in generating high-quality space weather forecast products,despite the data being starved.