Efficient and Stable Perovskite Solar Cells and Modules Enabled by Tailoring Additive Distribution According to the Film Growth Dynamics

Gas quenching and vacuum quenching process are widely applied to accelerate solvent volatilization to induce nucleation of perovskites in blade-coating method.In this work,we found these two pre-crystallization processes lead to different order of crystallization dynamics within the perovskite thin film,resulting in the differences of additive distribution.We then tailor-designed an additive molecule named 1,3-bis(4-methoxyphenyl)thiourea to obtain films with fewer defects and holes at the buried interface,and prepared perovskite solar cells with a certified efficiency of 23.75%.Furthermore,this work also demonstrates an efficiency of 20.18%for the large-area perovskite solar module(PSM)with an aperture area of 60.84 cm^(2).The PSM possesses remarkable continuous operation stability for maximum power point tracking of T_(90)>1000 h in ambient air.

Efficient and Stable Photoassisted Lithium‑Ion Battery Enabled by Photocathode with Synergistically Boosted Carriers Dynamics

Efficient and stable photocathodes with versatility are of significance in photoassisted lithium-ion batteries(PLIBs),while there is always a request on fast carrier transport in electrochemical active photocathodes.Present work proposes a general approach of creating bulk heterojunction to boost the carrier mobility of photocathodes by simply laser assisted embedding of plasmonic nanocrystals.When employed in PLIBs,it was found effective for synchronously enhanced photocharge separation and transport in light charging process.Additionally,experimental photon spectroscopy,finite difference time domain method simulation and theoretical analyses demonstrate that the improved carrier dynamics are driven by the plasmonic-induced hot electron injection from metal to TiO_(2),as well as the enhanced conductivity in TiO2 matrix due to the formation of oxygen vacancies after Schottky contact.Benefiting from these merits,several benchmark values in performance of TiO2-based photocathode applied in PLIBs are set,including the capacity of 276 mAh g^(−1) at 0.2 A g^(−1) under illumination,photoconversion efficiency of 1.276%at 3 A g^(−1),less capacity and Columbic efficiency loss even through 200 cycles.These results exemplify the potential of the bulk heterojunction strategy in developing highly efficient and stable photoassisted energy storage systems.

Molecular dynamics simulations of helium transport through inorganic mineral nanopores

Helium transport through nanoscale inorganic mineral pores and pore throats is essential for its overall migration.To elucidate helium's transport dynamics within nanopores,we employed equilibrium and non-equilibrium molecular dynamics simulations to investigate helium's static self-diffusion and pressure-driven flow in quartz slit-shaped nanopores.We also introduced water and various gases,including hydrogen,methane,ethane,nitrogen,and carbon dioxide,into the nanopores to assess their influence on helium transport.Our findings indicate minimal helium adsorption on quartz pore surfaces.Under conditions where the pore size is less than 5 nm and the pressure under 10 MPa,environmental factors markedly influence helium diffusion.Large pore sizes,high temperatures,and low gas pressures enhance helium desorption and facilitate faster diffusion.We observed a positive correlation between helium flow velocity and factors such as pore size,pressure gradient,and surface smoothness of the pores.Notably,the presence of pore water and carrier gases in quartz nanopores,which diffuse more slowly than helium,tends to reduce helium surface adsorption and slow its diffusion.Among the carrier gases studied,nitrogen showed similar adsorption capacity,diffusivity,and stability to helium,while carbon dioxide displayed the highest adsorption capacity and the slowest diffusion rate,markedly differing from helium.Based on the simulation results,we concluded that water and carrier gases primarily function as transport mediums in helium migration,moving together with helium.Nitrogen,which shares similar properties with helium,effectively assists in this co-migration process.Conversely,carbon dioxide,due to its high adsorption capacity and slow diffusion,tends to be lost during co-migration.As a result,gas reservoirs with high nitrogen levels and low carbon dioxide levels are more likely to have higher helium concentrations.Additionally,the smaller pore sizes and higher gas pressures in caprocks can impede helium's diffusion,favoring its preservation in reservoirs.Moreover,the presence of water and carrier gases significantly obstructs these pores,further hindering helium's escape.

Plastic deformation mechanism of γ-phase U–Mo alloy studied by molecular dynamics simulations

Uranium–molybdenum(U–Mo) alloys are critical for nuclear power generation and propulsion because of their superior thermal conductivity, irradiation stability, and anti-swelling properties. This study explores the plastic deformation mechanisms of γ-phase U–Mo alloys using molecular dynamics(MD) simulations. In the slip model, the generalized stacking fault energy(GSFE) and the modified Peierls–Nabarro(P–N) model are used to determine the competitive relationships among different slip systems. In the twinning model, the generalized plane fault energy(GPFE) is assessed to evaluate the competition between slip and twinning. The findings reveal that among the three slip systems, the {110}<111>slip system is preferentially activated, while in the {112}<111> system, twinning is favored over slip, as confirmed by MD tensile simulations conducted in various directions. Additionally, the impact of Mo content on deformation behavior is emphasized. Insights are provided for optimizing process conditions to avoid γ → α′′ transitions, thereby maintaining a higher proportion of γ-phase U–Mo alloys for practical applications.

Light Use Efficiency Model Based on Chlorophyll Content Better Captures Seasonal Gross Primary Production Dynamics of Deciduous Broadleaf Forests

Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical para-meter leaf area index(LAI),which are not completely synchronized in seasonality with GPP.In this study,we proposed chlorophyll content-based light use efficiency model(CC-LUE)to improve GPP estimates,as chlorophyll is the direct site of photosynthesis,and only the light absorbed by chlorophyll is used in the photosynthetic process.The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content(Chlcanopy)and FPAR.This method was calibrated and validated utiliz-ing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five dif-ferent climate zones.Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions.The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season,outperforming the three widely used LUE models(MODIS-GPP algorithm,Vegetation Photosynthesis Model(VPM),and the eddy covariance-light use efficiency model(EC-LUE)).Additionally,the CC-LUE model(RMSE=0.50 g C/(m^(2)·d))significantly improved the underestimation of GPP during the growing season in semi-arid region,re-markably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%,73.4%,and 37.5%,compared with MOD17(RMSE=2.03 g C/(m^(2)·d)),VPM(RMSE=1.88 g C/(m^(2)·d)),and EC-LUE(RMSE=0.80 g C/(m^(2)·d))model.The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems,thereby provid-ing the possibility of a more precise depiction of forest seasonal carbon uptake.

Study on the coupling calculation method for the launch dynamics of a self-propelled artillery multibody system considering engraving process

The launch dynamics theory for multibody systems emerges as an innovative and efficacious approach for the study of launch dynamics,capable of addressing the challenges of complex modeling,diminished computational efficiency,and imprecise analyses of system dynamic responses found in the dynamics research of intricate multi-rigid-flexible body systems,such as self-propelled artillery.This advancement aims to enhance the firing accuracy and launch safety of self-propelled artillery.Recognizing the shortfall of overlooking the band engraving process in existing theories,this study introduces a novel coupling calculation methodology for the launch dynamics of a self-propelled artillery multibody system.This method leverages the ABAQUS subroutine interface VUAMP to compute the dynamic response of the projectile and barrel during the launch process of large-caliber self-propelled artillery.Additionally,it examines the changes in projectile resistance and band deformation in relation to projectile motion throughout the band engraving process.Comparative analysis of the computational outcomes with experimental data evidences that the proposed method offers a more precise depiction of the launch process of self-propelled artillery,thereby enhancing the accuracy of launch dynamics calculations for self-propelled artillery.

Community structure and species diversity dynamics of a subtropical evergreen broad-leaved forest in China:2005 to 2020

Here,we characterize the temporal and spatial dynamics of forest community structure and species diversity in a subtropical evergreen broad-leaved forest in China.We found that community structure in this forest changed over a 15-year period.Specifically,renewal and death of common species was large,with the renewal of individuals mainly concentrated within a few populations,especially those of Aidia canthioides and Cryptocarya concinna.The numbers of individual deaths for common species were concentrated in the small and mid-diameter level.The spatial distribution of community species diversity fluctuated in each monitoring period,showing a more dispersed diversity after the 15-year study period,and the coefficient of variation on quadrats increased.In 2010,the death and renewal of the community and the spatial variation of species diversity were different compared to other survey years.Extreme weather may have affected species regeneration and community stability in our subtropical monsoon evergreen broad-leaved forests.Our findings suggest that strengthening the monitoring and management of the forest community will help better understand the long-and short-term causes of dynamic fluctuations of community structure and species diversity,and reveal the factors that drive changes in community structure.

Transient Response and Ionic Dynamics in Organic Electrochemical Transistors

The rapid development of organic electrochemical transistors(OECTs)has ushered in a new era in organic electronics,distinguishing itself through its application in a variety of domains,from high-speed logic circuits to sensitive biosensors,and neuromorphic devices like artificial synapses and organic electrochemical random-access memories.Despite recent strides in enhancing OECT performance,driven by the demand for superior transient response capabilities,a comprehensive understanding of the complex interplay between charge and ion transport,alongside electron–ion interactions,as well as the optimization strategies,remains elusive.This review aims to bridge this gap by providing a systematic overview on the fundamental working principles of OECT transient responses,emphasizing advancements in device physics and optimization approaches.We review the critical aspect of transient ion dynamics in both volatile and non-volatile applications,as well as the impact of materials,morphology,device structure strategies on optimizing transient responses.This paper not only offers a detailed overview of the current state of the art,but also identifies promising avenues for future research,aiming to drive future performance advancements in diversified applications.

Semiclassical approach to spin dynamics of a ferromagnetic S = 1 chain

Motivated by recent experimental progress on the quasi-one-dimensional quantum magnet Ni Nb2O6, we study the spin dynamics of an S = 1 ferromagnetic Heisenberg chain with single-ion anisotropy by using a semiclassical molecular dynamics approach. This system undergoes a quantum phase transition from a ferromagnetic to a paramagnetic state under a transverse magnetic field, and the magnetic response reflecting this transition is well described by our semiclassical method.We show that at low temperature the transverse component of the dynamical structure factor depicts clearly the magnon dispersion, and the longitudinal component exhibits two continua associated with single-and two-magnon excitations,respectively. These spin excitation spectra show interesting temperature dependence as effects of magnon interactions. Our findings shed light on the experimental detection of spin excitations in a large class of quasi-one-dimensional magnets.

Structure-controlled slow dynamics in Al−Mg melts

Molecular dynamics simulation was employed to investigate the dynamical and structural properties of Al−Mg melts with the Al concentration systematically changed.The results show that the viscosity of Al67Mg33 abnormally surpasses that of Al85Mg15 below 550 K,inconsistent with the tendency at high temperatures.The evolution of the icosahedral order population is found to account for this dynamic behavior.Structural analysis shows a preferred bonding between Al and Mg atoms in the nearest neighbor shells,while a repelling tendency between them in the second shells,leading to the prepeak emergence in the partial static structure factors.The formation of icosahedral clusters is constrained in the Al-rich compositions because of the lack of sufficient Mg atoms to stabilize the clusters geometrically.These results demonstrate the structural consequence through the interplay between geometric packing and chemical interaction.These findings are crucial to understanding the structure−dynamic properties in Al−Mg melts.

Ab initio nonadiabatic molecular dynamics study on spin–orbit coupling induced spin dynamics in ferromagnetic metals

Understanding the photoexcitation induced spin dynamics in ferromagnetic metals is important for the design of photo-controlled ultrafast spintronic device.In this work,by the ab initio nonadiabatic molecular dynamics simulation,we have studied the spin dynamics induced by spin–orbit coupling(SOC)in Co and Fe using both spin-diabatic and spin-adiabatic representations.In Co system,it is found that the Fermi surface(E_(F))is predominantly contributed by the spin-minority states.The SOC induced spin flip will occur for the photo-excited spin-majority electrons as they relax to the E_(F),and the spin-minority electrons tend to relax to the EFwith the same spin through the electron–phonon coupling(EPC).The reduction of spin-majority electrons and the increase of spin-minority electrons lead to demagnetization of Co within100 fs.By contrast,in Fe system,the E_(F) is dominated by the spin-majority states.In this case,the SOC induced spin flip occurs for the photo-excited spin-minority electrons,which leads to a magnetization enhancement.If we move the E_(F) of Fe to higher energy by 0.6eV,the E_(F) will be contributed by the spin-minority states and the demagnetization will be observed again.This work provides a new perspective for understanding the SOC induced spin dynamics mechanism in magnetic metal systems.

Ultrafast magneto-optical dynamics in nickel(111)single crystal studied by the integration of ultrafast reflectivity and polarimetry probes

With the integration of ultrafast reflectivity and polarimetry probes,we observed carrier relaxation and spin dynamics induced by ultrafast laser excitation of Ni(111)single crystals.The carrier relaxation time within the linear excitation range reveals that electron-phonon coupling and dissipation of photon energy into the bulk of the crystal take tens of picoseconds.On the other hand,the observed spin dynamics indicate a longer time of about 120 ps.To further understand how the lattice degree of freedom is coupled with these dynamics may require the integration of an ultrafast diffraction probe.

Simulation of nanofluid natural convection based on single-particle hydrodynamics in energy-conserving dissipative particle dynamics(eDPD)

In the present study,the nanofliud natural convection is investigated by the energy-conserving dissipative particle dynamics(eDPD)method,where the nanoparticles are considered at the single-particle level.The thermal expansion coefficientβand the viscosityμof the simulated system containing nanoparticles are calculated and found to be in close alignment with the previous simulation results.The single-particle hydrodynamics in e DPD enables simulations of nanofluid natural convection with higher Rayleigh numbers and greater nanoparticle volume fractions.Additionally,this approach is utilized to simulate the nanoparticle distribution during the enhanced heat transfer process in the nanofluid natural convection.The localized aggregation of nanoparticles enhances the heat transfer performance of the nanofluid under specific Rayleigh numbers and nanoparticles volume fractions.

A flexible multiscale algorithm based on an improved smoothed particle hydrodynamics method for complex viscoelastic flows

Viscoelastic flows play an important role in numerous engineering fields,and the multiscale algorithms for simulating viscoelastic flows have received significant attention in order to deepen our understanding of the nonlinear dynamic behaviors of viscoelastic fluids.However,traditional grid-based multiscale methods are confined to simple viscoelastic flows with short relaxation time,and there is a lack of uniform multiscale scheme available for coupling different solvers in the simulations of viscoelastic fluids.In this paper,a universal multiscale method coupling an improved smoothed particle hydrodynamics(SPH)and multiscale universal interface(MUI)library is presented for viscoelastic flows.The proposed multiscale method builds on an improved SPH method and leverages the MUI library to facilitate the exchange of information among different solvers in the overlapping domain.We test the capability and flexibility of the presented multiscale method to deal with complex viscoelastic flows by solving different multiscale problems of viscoelastic flows.In the first example,the simulation of a viscoelastic Poiseuille flow is carried out by two coupled improved SPH methods with different spatial resolutions.The effects of exchanging different physical quantities on the numerical results in both the upper and lower domains are also investigated as well as the absolute errors in the overlapping domain.In the second example,the complex Wannier flow with different Weissenberg numbers is further simulated by two improved SPH methods and coupling the improved SPH method and the dissipative particle dynamics(DPD)method.The numerical results show that the physical quantities for viscoelastic flows obtained by the presented multiscale method are in consistence with those obtained by a single solver in the overlapping domain.Moreover,transferring different physical quantities has an important effect on the numerical results.

The Effect of Lateral Offset Distance on the Aerodynamics and Fuel Economy of Vehicle Queues

The vehicle industry is always in search of breakthrough energy-saving and emission-reduction technologies.In recent years,vehicle intelligence has progressed considerably,and researchers are currently trying to take advantage of these developments.Here we consider the case of many vehicles forming a queue,i.e.,vehicles traveling at a predetermined speed and distance apart.While the majority of existing studies on this subject have focused on the influence of the longitudinal vehicle spacing,vehicle speed,and the number of vehicles on aerodynamic drag and fuel economy,this study considers the lateral offset distance of the vehicle queue.The group fuel consumption savings rate is calculated and analyzed.As also demonstrated by experimental results,some aerodynamic benefits exist.Moreover,the fuel consumption saving rate of the vehicle queue decreases as the lateral offset distance increases.

The impact of demographic dynamics on food consumption and its environmental outcomes:Evidence from China

With increasing population and changing demographics,food consumption has experienced a significant transition in quantity and quality.However,a dearth of knowledge remains regarding its environmental impacts and how it responds to demographic dynamics,particularly in emerging economies like China.Using the two-stage Quadratic Almost Demand System(QUAIDS)model,this study empirically examines the impact of demographic dynamics on food consumption and its environmental outcomes based on the provincial data from 2000 to 2020 in China.Under various scenarios,according to changes in demographics,we extend our analysis to project the long-term trend of food consumption and its environmental impacts,including greenhouse gas(GHG)emissions,water footprint(WF),and land appropriation(LA).The results reveal that an increase in the proportion of senior people significantly decreases the consumption of grain and livestock meat and increases the consumption of poultry,egg,and aquatic products,particularly for urban residents.Moreover,an increase in the proportion of males in the population leads to higher consumption of poultry and aquatic products.Correspondingly,in the current scenario of an increased aging population and sex ratio,it is anticipated that GHG emissions,WF,and LA are likely to decrease by 1.37,2.52,and 3.56%,respectively.More importantly,in the scenario adhering to the standards of nutritional intake according to the Dietary Guidelines for Chinese Residents in 2022,GHG emissions,WF,and LA in urban areas would increase by 12.78,20.94,and 18.32%,respectively.Our findings suggest that changing demographics should be considered when designing policies to mitigate the diet-environment-health trilemma and achieve sustainable food consumption.

Millisecond dynamics of colloidal suspension studied by X-ray photon correlation spectroscopy at the Shanghai Synchrotron Radiation Facility

X-ray photon correlation spectroscopy(XPCS)has emerged as a powerful tool for probing the nanoscale dynamics of soft condensed matter and strongly correlated materials owing to its high spatial resolution and penetration capabilities.This technique requires high brilliance and beam coherence,which are not directly available at modern synchrotron beamlines in China.To facilitate future XPCS experiments,we modified the optical setup of the newly commissioned BL10U1 USAXS beamline at the Shanghai Synchrotron Radiation Facility(SSRF).Subsequently,we performed XPCS measurements on silica suspensions in glycerol,which were opaque owing to their high concentrations.Images were collected using a high frame rate area detector.A comprehensive analysis was performed,yielding correlation functions and several key dynamic parameters.All the results were consistent with the theory of Brownian motion and demonstrated the feasibility of XPCS at SSRF.Finally,by carefully optimizing the setup and analyzing the algorithms,we achieved a time resolution of 2 ms,which enabled the characterization of millisecond dynamics in opaque systems.

Quantifying glacier surging and associated lake dynamics in Amu Darya river basin using UAV and remote sensing data

Glaciers in the Pamir region are experiencing rapid melting and receding due to climate change,which has a significant implication for the Amu Darya river basin.Predominantly,surging glaciers,which undergo unpredictable advances,are potentially leading to the obstruction of high-altitude river channels and also glacial lake outburst floods.decrease of-703.5±30.0 m.There is a substantial increase in the number(from 19 to 75)and area(from 4889.7±0.6 m2 to 15345.5±0.6 m2)of RGS lakes along with supra-glacier ponds based on a comparison of ArcGIS base map in 2011 and high-resolution UAV data in 2023.For M glacier,number of lakes increased from 4 to 22 but the lake area declined from 10715.2±0.6 to 365.6±0.6 m2.It was noted that the largest lake in 2011 with an area of 10406.4±0.6 m2 at the southeastern portion of the glacier was not observed in 2023 due to outburst.Both the glaciers have substantially impacted the river flow(Abdukahor river)by obstructing a significant proportion of river channel in recent years and might cause outburst floods.These findings enhance the understanding of glacier dynamics and their impacts on the surrounding areas,emphasizing the urgent need for continued monitoring and appropriate management strategies,with a specific focus on surging glaciers and the associated risks.

Effect of cognitive training on brain dynamics

The human brain is highly plastic.Cognitive training is usually used to modify functional connectivity of brain networks.Moreover,the structures of brain networks may determine its dynamic behavior which is related to human cognitive abilities.To study the effect of functional connectivity on the brain dynamics,the dynamic model based on functional connections of the brain and the Hindmarsh–Rose model is utilized in this work.The resting-state fMRI data from the experimental group undergoing abacus-based mental calculation(AMC)training and from the control group are used to construct the functional brain networks.The dynamic behavior of brain at the resting and task states for the AMC group and the control group are simulated with the above-mentioned dynamic model.In the resting state,there are the differences of brain activation between the AMC group and the control group,and more brain regions are inspired in the AMC group.A stimulus with sinusoidal signals to brain networks is introduced to simulate the brain dynamics in the task states.The dynamic characteristics are extracted by the excitation rates,the response intensities and the state distributions.The change in the functional connectivity of brain networks with the AMC training would in turn improve the brain response to external stimulus,and make the brain more efficient in processing tasks.

Scenario analysis of the Indonesia carbon tax impact on carbon emissions using system dynamics modeling and STIRPAT model

This study aims to develop a system dynamic(SD)forecasting model based on the STIRPAT model to forecast the effect of an IDR 30 per kg CO_(2)e carbon tax on carbon emissions,estimate future carbon emissions under ten scenarios,without and with the carbon tax,and estimate the environmental Kuznets curve(EKC)to predict Indonesia’s carbon emission peak.Carbon emission drivers in this study are decomposed into several factors,namely energy structure,energy intensity,industrial structure,GDP per capita,population,and fixed-asset investment.This study included nuclear power utilization starting in 2038.The research gaps addressed by this study compared to previous research are(1)use of the ex-ante approach,(2)inclusion of nuclear power plants,(3)testing the EKC hypothesis,and(4)contribution to government policy.The simulation results show that under the carbon tax,carbon emissions can be reduced by improving renewable energy structures,adjusting industrial structures to green businesses,and emphasizing fixed asset investment more environmentally friendly.Moreover,the result approved the EKC hypothesis.It shows an inverse U-shaped curve between GDP per capita and CO_(2)emissions in Indonesia.Indonesia’s fastest carbon emission peak is under scenario seven and is expected in 2040.Although an IDR 30 per kg CO_(2)e carbon tax and nuclear power will take decades to reduce carbon emissions,the carbon tax can still be a reference and has advantages to implement.This result can be a good beginning step for Indonesia,which has yet to gain experience with a carbon tax that can be implemented immediately and is helpful to decision-makers in putting into practice sensible measures to attain Indonesia’s carbon emission peaking.This research provides actionable insights internationally on carbon tax policies,nuclear energy adoption,EKC dynamics,global policy implications,and fostering international cooperation for carbon emission reductions.