Hydrogen release of NaBH_(4) below 60 ℃ with binary eutectic mixture of xylitol and erythritol additive

NaBH_(4) was widely regarded as a low-cost hydrogen storage material due to its high-mass hydrogen capacity of approximately 10.8%(mass)and high volumetric hydrogen capacity of around 115 g·L^(–1).However,it exhibits strong stability and requires temperatures above 500℃ for hydrogen release in practical applications.In this study,two polyhydric alcohols,xylitol and erythritol(XE),were prepared as a binary eutectic sugar alcohol through a grinding-melting method.This binary eutectic sugar alcohol was used as a proton-hydrogen carrier to destabilize NaBH_(4).The 19NaBH_(4)-16XE composite material prepared by ball milling could start releasing hydrogen at 57.5℃,and the total hydrogen release can reach over 88.8%(4.45%(mass))of the theoretical capacity.When the 19NaBH_(4)-16XE composite was pressed into solid blocks,the volumetric hydrogen capacity of the block-shaped composite could reach 67.2 g·L^(–1).By controlling the temperature,the hydrogen desorption capacity of the NaBH_(4)-XE composite material was controllable,which has great potential for achieving solid-state hydrogen production from NaBH_(4).

Synthesis and Design of Distillation Columns for Wide-Boiling Binary Mixtures with Vapor Recompression Heat Pumps

The vapor recompression heat pump(VRHP) distillation technology offers significant improvements in energy efficiency for distillation systems with small temperature differences between the top and bottom of the column. However, the separation of wide-boiling binary mixtures leads to substantial temperature differences between the top and bottom of the column. This limits the applicability of conventional VRHP due to high capital costs and strict performance requirements of the compressor. To overcome these challenges and to accommodate compressor operating conditions, a novel synthesis and design method is introduced to integrate VRHPs with wide-boiling binary mixture distillation columns(WBMDCs). This method enables quick determination of an initial configuration for the integrated WBMDC-VRHP system and helps identify the optimum configuration with the minimum total annual cost. Two examples, namely the separation of benzene/toluene and isopropanol/chlorobenzene, are employed to derive optimum configurations of the WBMDC-VRHP and compare them with the WBMDC. A systematic comparison between the WBMDC-VRHP and WBMDC demonstrates the superior steady-state performance and economic efficiency of the WBMDC-VRHP.

Adsorption behavior of CO_(2)/H_(2)S mixtures in calcite slit nanopores for CO_(2) storage:An insight from molecular perspective

It is acknowledged that injecting CO_(2) into oil reservoirs and saline aquifers for storage is a practical and affordable method for CO_(2) sequestration.Most CO_(2) produced from industrial exhaust contains impurity gases such as H_(2)S that might impact CO_(2) sequestration due to competitive adsorption.This study makes a commendable effort to explore the adsorption behavior of CO_(2)/H_(2)S mixtures in calcite slit nanopores.Grand Canonical Monte Carlo(GCMC)simulation is employed to reveal the adsorption of CO_(2),H_(2)S as well as their binary mixtures in calcite nanopores.Results show that the increase in pressure and temperature can promote and inhibit the adsorption capacity of CO_(2) and H_(2)S in calcite nanopores,respectively.CO_(2)exhibits stronger adsorption on calcite surface than H_(2)S.Electrostatic energy plays the dominating role in the adsorption behavior.Electrostatic energy accounts for 97.11%of the CO_(2)-calcite interaction energy and 56.33%of the H_(2)S-calcite interaction energy at 10 MPa and 323.15 K.The presence of H_(2)S inhibits the CO_(2) adsorption in calcite nanopores due to competitive adsorption,and a higher mole fraction of H_(2)S leads to less CO_(2) adsorption.The quantity of CO_(2) adsorbed is lessened by approximately 33%when the mole fraction of H_(2)S reaches 0.25.CO_(2) molecules preferentially occupy the regions near the po re wall and H_(2)S molecules tend to reside at the center of nanopore even when the molar ratio of CO_(2) is low,indicating that CO_(2) has an adsorption priority on the calcite surface over H_(2)S.In addition,moisture can weaken the adsorption of both CO_(2) and H_(2)S,while CO_(2) is more affected.More interestingly,we find that pure CO_(2) is more suitable to be sequestrated in the shallower formations,i.e.,500-1500 m,whereas CO_(2)with H_(2)S impurity should be settled in the deeper reservoirs.

First Light Curve Analysis of NSVS 8294044,V1023 Her,and V1397 Her Contact Binary Systems

The first photometric light curve investigation of the NSVS 8294044,V1023 Her,and V1397 Her binary systems is presented.We used ground-based observations for the NSVS 8294044 system and Transiting Exoplanet Survey Satellite data for V1023 Her and V1397 Her.The primary and secondary times of minima were extracted from al the data,and,by collecting the literature,a new ephemeris was computed for each system.Linear fits for the O-C diagrams were conducted using the Markov Chain Monte Carlo (MCMC) method.Light curve solutions were performed using the PHysics Of Eclipsing BinariEs Python code and the MCMC approach.The systems were found to be contact binary stars based on the fillout factor and mass ratio.V1023 Her showed the O’Connell effect and a cold starspot on the secondary component was required for the light curve solution.The absolute parameters of the system were estimated based on an empirical relationship between orbital period and mass.We presented a new T–M equation based on a sample of 428 contact binary systems and found that our three target systems were in good agreement with the fit.The positions of the systems were also depicted on the M–L,M–R,q–L_(ratio),and M_(tot)–J_(0)diagrams in the logarithmic scales.

Rapid and stable calcium-looping solar thermochemical energy storage via co-doping binary sulfate and Al–Mn–Fe oxides

Solar thermochemical energy storage based on calcium looping(CaL)process is a promising technology for next-generation concentrated solar power(CSP)systems.However,conventional calcium carbonate(CaCO_(3))pellets suffer from slow reaction kinetics,poor stability,and low solar absorptance.Here,we successfully realized high power density and highly stable solar thermochemical energy storage/release by synergistically accelerating energy storage/release via binary sulfate and promoting cycle stability,mechanical strength,and solar absorptance via Al–Mn–Fe oxides.The energy storage density of proposed CaCO_(3)pellets is still as high as 1455 kJ kg^(-1)with only a slight decay rate of 4.91%over 100 cycles,which is higher than that of state-of-the-art pellets in the literature,in stark contrast to 69.9%of pure CaCO_(3)pellets over 35 cycles.Compared with pure CaCO_(3),the energy storage power density or decomposition rate is improved by 120%due to lower activation energy and promotion of Ca^(2+)diffusion by binary sulfate.The energy release or carbonation rate rises by 10%because of high O^(2-)transport ability of molten binary sulfate.Benefiting from fast energy storage/release rate and high solar absorptance,thermochemical energy storage efficiency is enhanced by more than 50%under direct solar irradiation.This work paves the way for application of direct solar thermochemical energy storage techniques via achieving fast energy storage/release rate,high energy density,good cyclic stability,and high solar absorptance simultaneously.

Generating Sets of the Complete Semigroup of Binary Relations Defined by Semilattices of the Class Σ8(X, 5)

In this article, we study generating sets of the complete semigroups of binary relations defined by X-semilattices of unions of the class Σ8(X, 5). Found uniquely irreducible generating set for the given semigroups and when X is finite set formulas for calculating the number of elements in generating sets are derived.

Joint Effects of Multipollutant Mixtures on Mortality in Chengdu,China

Significant epidemiological research has revealed that exposure to air pollution is substantially associated with numerous detrimental health consequences^([1-3]).The negative health effects of individual air pollutants(e.g.,fine particulate matter:PM_(2.5);nitrogen dioxide:NO_(2);carbon monoxide,CO;or ozone:O_(3))have been widely explored^([4]).However,humans are constantly exposed to multipollutant mixtures in real life,and biological responses to inhaled pollutants are likely to depend on the interplay of pollutant mixtures.Therefore,it is critical and imperative to explore the joint effects of multipollutant mixtures on human beings.

Temperature-dependent solubility of Rebaudioside A in methanol/ethanol and ethyl acetate mixtures:Experimental measurements and thermodynamic modeling

The equilibrium solubility of Rebaudioside A(Reb A)FormⅡin binary mixtures of methanol/ethanol and ethyl acetate was quantitatively determined within the temperature range of 283.15—328.15 K at ambient pressure.The experimental findings indicate a positive correlation between the solubility of Reb A(FormⅡ)and both the temperature and the methanol/ethanol content in the solvent system.To describe the solubility data,six distinct models were employed:the modified Apelblat equation,theλh model,the combined nearly ideal binary solvent/Redlich—Kister(CNIBS/R—K)model,the van't HoffJouyban-Acree(VJA)model,the Apelblat-Jouyban-Acree(AJA)model,and the non-random two-liquid(NRTL)model.The combined nearly ideal binary solvent/Redlich—Kister model exhibited the most precise fit for solubility in methanol+ethyl acetate mixtures,reflected by an average relative deviation(ARD)of 0.0011 and a root mean square deviation(RMSD)of 12×10^(-7).Conversely,for ethanol+ethyl acetate mixtures,the modified Apelblat equation provided a superior correlation(ARD=0.0014,RMSD=4×10^(-7)).Furthermore,thermodynamic parameters associated with the dissolution of Reb A(FormⅡ),including enthalpy,entropy,and the Gibbs energy change,were inferred from the data.The findings underscore that the dissolution process is predominantly endothermic across the solvent systems examined.Notably,the entropy changes appear to have a significant influence on the Gibbs free energy associated with the dissolution of Reb A(FormⅡ),suggesting that entropic factors may play a pivotal role in the studied systems.

Photometric and Spectroscopic Study of Ten Low Mass Ratio Contact Binary Systems:Orbital Stability,O'Connell Effect and Infrared Calcium Line Filling

Low mass ratio contact binary systems are more likely to have unstable orbits and potentially merge.In addition,such systems exhibit characteristics such as starspots and high energy emissions(UV)suggestive of chromospheric and magnetic activity.Light curve modeling of ten contact binary systems is reported.All were found to be of extreme low mass ratio ranging from 0.122 to 0.24 and three were found to be potentially unstable and possible merger candidates.Filling of the infrared calcium absorption lines is a marker of increased chromospheric activity.We use the available Large Sky Area Multi-Object Fiber Spectroscopic Telescope spectra along with matched standard spectra(broadened for rotation)to measure the excess filling of the central core depression flux of the two main infrared calcium absorption linesλ8542 andλ8662.We find that all reported contact binaries have excess filling of the core flux in the infrared calcium lines.Three of the systems reported were also observed by the Galaxy Evolution Explorer mission and we find that all three have features of excess ultraviolet emissions further adding evidence for increased chromospheric activity in low mass ratio contact binaries.Analysis of both orbital stability and absorption line filling is dependent on the determination of geometric and absolute parameters from light curve modeling.Not an insignificant number of contact binary light curves exhibit the O’Connell effect,usually attributed to starspots.We discuss the inclusion of starspots in light curve solutions and how they influence the geometric and absolute parameters.

Boosting MA-based two-dimensional Ruddlesden-Popper perovskite solar cells by incorporating a binary spacer

Two-dimensional Ruddlesden-Popper(2DRP)perovskite exhibits excellent stability in perovskite solar cells(PSCs)due to introducing hydrophobic long-chain organic spacers.However,the poor charge transporting property of bulky organic cation spacers limits the performance of 2DRP PSCs.Inspired by the Asite cation alloying strategy in 3D perovskites,2DRP perovskites with a binary spacer can promote charge transporting compared to the unary spacer counterparts.Herein,the superior MA-based 2DRP perovskite films with a binary spacer,including 3-guanidinopropanoic acid(GPA)and 4-fluorophenethylamine(FPEA)are realized.These films(GPA_(0.85)FPEA_(0.15))_(2)MA_(4)Pb_5I_(16)show good morphology,large grain size,decreased trap state density,and preferential orientation of the as-prepared film.Accordingly,the present 2DRP-based PSC with the binary spacer achieves a remarkable efficiency of 18.37%with a V_(OC)of1.15 V,a J_(SC)of 20.13 mA cm^(-2),and an FF of 79.23%.To our knowledge,the PCE value should be the highest for binary spacer MA-based 2DRP(n≤5)PSCs to date.Importantly,owing to the hydrophobic fluorine group of FPEA and the enhanced interlayer interaction by FPEA,the unencapsulated 2DRP PSCs based on binary spacers exhibit much excellent humidity stability and thermal stability than the unary spacer counterparts.

Optimization of Biofuel Formulation by Mixture Design

With the full growth of energy needs in the world, several studies are now focused on finding renewable sources. The aim of this work is to optimise biofuel formulation from a mixture design by studying physical properties, such as specific gravity and kinematic viscosity of various formulated mixtures. Optimization from the mixture plan revealed that in the chosen experimental domain, the optimal conditions are: 40% for used frying oil (UFO), 50% for bioethanol and 10% for diesel. These experimental conditions lead to a biofuel with a density of 0.84 and a kinematic viscosity of 2.97 cSt. These parameters are compliant with the diesel quality certificate in tropical areas. These density and viscosity values were determined according to respective desirability values of 0.68 and 0.75.

Probabilistic seismic inversion based on physics-guided deep mixture density network

Deterministic inversion based on deep learning has been widely utilized in model parameters estimation.Constrained by logging data,seismic data,wavelet and modeling operator,deterministic inversion based on deep learning can establish nonlinear relationships between seismic data and model parameters.However,seismic data lacks low-frequency and contains noise,which increases the non-uniqueness of the solutions.The conventional inversion method based on deep learning can only establish the deterministic relationship between seismic data and parameters,and cannot quantify the uncertainty of inversion.In order to quickly quantify the uncertainty,a physics-guided deep mixture density network(PG-DMDN)is established by combining the mixture density network(MDN)with the deep neural network(DNN).Compared with Bayesian neural network(BNN)and network dropout,PG-DMDN has lower computing cost and shorter training time.A low-frequency model is introduced in the training process of the network to help the network learn the nonlinear relationship between narrowband seismic data and low-frequency impedance.In addition,the block constraints are added to the PG-DMDN framework to improve the horizontal continuity of the inversion results.To illustrate the benefits of proposed method,the PG-DMDN is compared with existing semi-supervised inversion method.Four synthetic data examples of Marmousi II model are utilized to quantify the influence of forward modeling part,low-frequency model,noise and the pseudo-wells number on inversion results,and prove the feasibility and stability of the proposed method.In addition,the robustness and generality of the proposed method are verified by the field seismic data.

An active learning workflow for predicting hydrogen atom adsorption energies on binary oxides based on local electronic transfer features

Machine learning combined with density functional theory(DFT)enables rapid exploration of catalyst descriptors space such as adsorption energy,facilitating rapid and effective catalyst screening.However,there is still a lack of models for predicting adsorption energies on oxides,due to the complexity of elemental species and the ambiguous coordination environment.This work proposes an active learning workflow(LeNN)founded on local electronic transfer features(e)and the principle of coordinate rotation invariance.By accurately characterizing the electron transfer to adsorption site atoms and their surrounding geometric structures,LeNN mitigates abrupt feature changes due to different element types and clarifies coordination environments.As a result,it enables the prediction of^(*)H adsorption energy on binary oxide surfaces with a mean absolute error(MAE)below 0.18 eV.Moreover,we incorporate local coverage(θ_(l))and leverage neutral network ensemble to establish an active learning workflow,attaining a prediction MAE below 0.2 eV for 5419 multi-^(*)H adsorption structures.These findings validate the universality and capability of the proposed features in predicting^(*)H adsorption energy on binary oxide surfaces.

Micromechanism and mathematical model of stress sensitivity in tight reservoirs of binary granular medium

Research on reservoir rock stress sensitivity has traditionally focused on unary granular structures,neglecting the binary nature of real reservoirs,especially tight reservoirs.Understanding the stresssensitive behavior and mathematical characterization of binary granular media remains a challenging task.In this study,we conducted online-NMR experiments to investigate the permeability and porosity evolution as well as stress-sensitive control mechanisms in tight sandy conglomerate samples.The results revealed stress sensitivity coefficients between 0.042 and 0.098 and permeability damage rates ranging from 65.6%to 90.9%,with an average pore compression coefficient of 0.0168—0.0208 MPa 1.Pore-scale compression occurred in three stages:filling,compression,and compaction,with matrix pores playing a dominant role in pore compression.The stress sensitivity of binary granular media was found to be influenced by the support structure and particle properties.High stress sensitivity was associated with small fine particle size,high fines content,high uniformity coefficient of particle size,high plastic deformation,and low Young's modulus.Matrix-supported samples exhibited a high irreversible permeability damage rate(average=74.2%)and stress sensitivity coefficients(average=0.089),with pore spaces more slit-like.In contrast,grain-supported samples showed low stress sensitivity coefficients(average=0.021)at high stress stages.Based on the experiments,we developed a mathematical model for stress sensitivity in binary granular media,considering binary granular properties and nested interactions using Hertz contact deformation and Poiseuille theory.By describing the change in activity content of fines under stress,we characterized the non-stationary state of compressive deformation in the binary granular structure and classified the reservoir into three categories.The model was applied for production prediction using actual data from the Mahu reservoir in China,showing that the energy retention rates of support-dominated,fill-dominated,and matrix-controlled reservoirs should be higher than 70.1%,88%,and 90.2%,respectively.

Timing and Spectral Analysis of the Black Hole X-Ray Binary MAXI J1803-298 with Insight-HXMT Data

We present a comprehensive analysis of the 2021 outburst of MAXI J1803–298 utilizing observations of the Insight-Hard X-ray Modulation Telescope(Insight-HXMT)spanning from the low hard state to the high soft state.Within the Insight-HXMT data set,compared to the previous work,we identify a more prolonged presence of typeC quasi-periodic oscillations(QPOs)with centroid frequencies ranging from~0.16 to 6.3 Hz,which present correlations with the hardness ratio and the photon index of the Comptonized component.For QPO frequencies less than~2 Hz,the QPO phase lags are hard(photons of 10–19 keV arrive later than those of 1–4 keV),while at higher frequencies,the lags become soft at and above~4 Hz.Furthermore,the spectra in all Insight-HXMT observations consist of a multi-color blackbody component and a Comptonized component,as commonly observed in classical black hole X-ray binaries.We analyze state transitions and the evolution of accretion geometry in this work.The fitted inner disk radius increases abnormally during the low hard state,hypothesized to result from the corona condensing onto the inner disk.Additionally,two significant drops in flux are observed during the soft intermediate state,maybe implying changes in the corona/jet and the disk,respectively.

Molecular packing tuning via chlorinated end group enables efficient binary organic solar cells over 18.5%

Designing novel nonfullerene acceptors(NFAs)is of vital importance for the development of organic solar cells(OSC).Modification on the side chain and end group are two powerful tools to construct efficient NFAs.Here,based on the high-performance L8BO,we selected 3-ethylheptyl to substitute the inner chain of 2-ethylhexyl,obtaining the backbone of BON3.Then we introduced different halogen atoms of fluorine and chlorine on 2-(3-oxo-2,3-dihydro-1Hinden-1-ylidene)malononitrile end group(EG)to construct efficient NFAs named BON3-F and BON3-Cl,respectively.Polymer donor D18 was chosen to combine with two novel NFAs to construct OSC devices.Impressively,D18:BON3-Cl-based device shows a remarkable power conversion efficiency(PCE)of 18.57%,with a high open-circuit voltage(V_(OC))of 0.907 V and an excellent fill factor(FF)of 80.44%,which is one of the highest binary PCE of devices based on D18 as the donor.However,BON3-F-based device shows a relatively lower PCE of 17.79%with a decreased FF of 79.05%.The better photovoltaic performance is mainly attributed to the red-shifted absorption,higher electron and hole mobilities,reduced charge recombination,and enhanced molecular packing in the D18:BON3-Cl films.Also,we performed stability tests on two binary systems;the D18:BON3-Cl and D18:BON3-F devices maintain 88.1%and 85.5%of their initial efficiencies after 169 h of storage at 85°C in an N2-filled glove box,respectively.Our work demonstrates the importance of selecting halogen atoms on EG and provides an efficient binary system of D18:BON3-Cl for further improvement of PCE.

V0405 Dra:A New Deep and Low Mass Ratio Contact Binary with Extremely Fast Decrease in the Orbital Period

V0405 Dra is a W UMa-type binary star.Based on the TESS data,we have conducted an orbital period study and performed a light curve analysis for the system.The orbital period study reveals that the O-C curve for V0405 Dra exhibits secular decrease at an extremely high rate of d P/dt=-2.71×10^(-6)day year^(-1),along with periodic variations characterized by an amplitude of A_(3)=0.0032 day and a period of P_(3)=1.413 years.The orbital periodic change is possibly due to the light-travel time effect resulting from an additional third body in the system,for which we estimate a minimum mass of M_(3)=0.77M_(⊙).By employing the 2013 version of the Wilson-Devinney(W-D)method to synthesize a light curve,we derived photometric solutions indicating that V0405 Dra is a new deep(f=68.7%)and low-mass ratio(q=0.175)contact binary.The fast decrease in its orbital period is likely caused by mass transfer from the more massive primary star to the less massive secondary star,or due to angular momentum loss.With further mass transfer and loss of angular momentum,the binary will gradually evolve into a tighter contact configuration,eventually leading to a merger into a single star,following the evolutionary paths suggested for such deep and low mass ratio contact binaries.

Optimal preparation of Bose and Fermi atomic gas mixtures of ^(87)Rb and ^(40)K in a crossed optical dipole trap

We report on the optimal production of the Bose and Fermi mixtures with ^(87) Rb and ^(40)K in a crossed optical dipole trap(ODT).We measure the atomic number and lifetime of the mixtures in combination of the spin state |F=9/2,m_(F)=9/2> of^(40)K and |1,1>of ^(87) Rb in the ODT,which is larger and longer compared with the combination of the spin state |9/2,9/2> of^(40)K and 12,2) of ^(87)Rb in the ODT.We observe the atomic numbers of ^(87)Rb and ^(40)K shown in each stage of the sympathetic cooling process while gradually reducing the depth of the optical trap.By optimizing the relative loading time of atomic mixtures in the MOT,we obtain the large atomic number of ^(40)K(~6 ×10^(6)) or the mixtures of atoms with an equal number(~1.6 × 10^(6)) at the end of evaporative cooling in the ODT.We experimentally investigate the evaporative cooling in an enlarged volume of the ODT via adding a third laser beam to the crossed ODT and found that more atoms(8 × 10^(6)) and higher degeneracy(T/T_(F)=0.25) of Fermi gases are obtained.The ultracold atomic gas mixtures pave the way to explore phenomena such as few-body collisions and the Bose-Fermi Hubbard model,as well as for creating ground-state molecules of ^(87)Rb^(40)K.

The Completeness of Accreting Neutron Star Binary Candidates from the Chinese Space Station Telescope

A neutron star(NS)has many extreme physical conditions,and one may obtain some important information about an NS via accreting neutron star binary(ANSB)systems.The upcoming Chinese Space Station Telescope(CSST)provides an opportunity to search for a large sample of ANSB candidates.Our goal is to check the completeness of the potential ANSB samples from CSST data.In this paper,we generate some ANSBs and normal binaries under the CSST photometric system by binary evolution and binary population synthesis method and use a machine learning method to train a classification model.Although the Precision(94.56%)of our machine learning model is as high as before study,the Recall is only about 63.29%.The Precision/Recall is mainly determined by the mass transfer rate between the NSs and their companions.In addition,we also find that the completeness of ANSB samples from CSST photometric data by the machine learning method also depends on the companion mass and the age of the system.ANSB candidates with a low initial mass companion star(0.1 M_(⊙)to 1 M_(⊙))have a relatively high Precision(94.94%)and high Recall(86.32%),whereas ANSB candidates with a higher initial mass companion star(1.1 M_(⊙)to 3 M_(⊙))have similar Precision(93.88%)and quite low Recall(42.67%).Our results indicate that although the machine learning method may obtain a relatively pure sample of ANSBs,a completeness correction is necessary for one to obtain a complete sample.

Predicting carbon storage of mixed broadleaf forests based on the finite mixture model incorporating stand factors,site quality,and aridity index

The diameter distribution function(DDF)is a crucial tool for accurately predicting stand carbon storage(CS).The current key issue,however,is how to construct a high-precision DDF based on stand factors,site quality,and aridity index to predict stand CS in multi-species mixed forests with complex structures.This study used data from70 survey plots for mixed broadleaf Populus davidiana and Betula platyphylla forests in the Mulan Rangeland State Forest,Hebei Province,China,to construct the DDF based on maximum likelihood estimation and finite mixture model(FMM).Ordinary least squares(OLS),linear seemingly unrelated regression(LSUR),and back propagation neural network(BPNN)were used to investigate the influences of stand factors,site quality,and aridity index on the shape and scale parameters of DDF and predicted stand CS of mixed broadleaf forests.The results showed that FMM accurately described the stand-level diameter distribution of the mixed P.davidiana and B.platyphylla forests;whereas the Weibull function constructed by MLE was more accurate in describing species-level diameter distribution.The combined variable of quadratic mean diameter(Dq),stand basal area(BA),and site quality improved the accuracy of the shape parameter models of FMM;the combined variable of Dq,BA,and De Martonne aridity index improved the accuracy of the scale parameter models.Compared to OLS and LSUR,the BPNN had higher accuracy in the re-parameterization process of FMM.OLS,LSUR,and BPNN overestimated the CS of P.davidiana but underestimated the CS of B.platyphylla in the large diameter classes(DBH≥18 cm).BPNN accurately estimated stand-and species-level CS,but it was more suitable for estimating stand-level CS compared to species-level CS,thereby providing a scientific basis for the optimization of stand structure and assessment of carbon sequestration capacity in mixed broadleaf forests.