A systematic review of the latest research advances in DED technology was provided， focusing on four key developmental directions： multi-heat source hybridization， material supply innovation， energy field regulation， and AI-driven processes. Regarding multi-heat source hybridization， combined processes， such as laser-arc hybridization， the complementary mechanism between different heat sources were leveraged， effectively balancing processing efficiency and forming accuracy. Regarding material supply innovation， novel feeding approaches， including twisted wire， multi-wire， and wire-powder synergistic feeding， had significantly expanded the capability to fabricate functional gradient materials and multi-principal element alloys. It laid the material foundation for enhancing the performance of components overall. Regarding energy field regulation， several methods such as pulse modulation， path planning， and multi-physical field coupling achieved precise control over molten pool dynamics and microstructural evolution. Regarding AI driving， the integration of machine learning and other data-driven techniques expedited the intelligent evolution of DED technology in areas such as processing parameter optimization， intelligent defect diagnosis， and digital twin system development.

A three-dimensional thermal-fluid-solidification integrated numerical model was established for laser-directed energy deposition（L-DED）. The thermofluidic transports and dynamic solidification behaviors were investigated during continuous wave（CW） and pulsed wave（PW） laser deposition through experimental and numerical methods. The results indicate that the melt pool exhibits stable behavior under CW mode， while PW mode induces periodic oscillation of the melt pool and triggers track remelting. Under the influences of surface-active oxygen and sulfur， both modes exhibit inward Marangoni flow. In CW mode， the melt pool undergoes only constrained solidification， exhibiting relatively stable solidification behaviors； the high temperature gradient（G） and low solidification rate（S） result in the coarsest grains， with average equiaxed grain equivalent diameters 2.6 times and 2 times larger than those in PW-25 and PW-50 modes， respectively. Conversely， the PW-mode melt pool alternately undergoes constrained solidification and free solidification（predominantly free solidification）， demonstrating dynamically evolving solidification behaviors. During free solidification stages， low G and high S promote grain refinement. Additionally， high-frequency PW mode inhibits the constrained solidification zones and columnar-to-equiaxed transition（CET）， forming cross-band epitaxial grains across discrete bands； while low-frequency PW mode enlarges the constrained solidification zones dominated by coarse grains.

Aiming at the existent problems such as local strap debonding and strength degradation of the adhesively bonded steel/lead bimetallic structures in the field of defense equipment， a novel additive manufacturing method was proposed to fabricate 45 steel/lead alloy bimetallic structures by direct metallurgical connection， which was a combination of droplet deposition-based freeform fabrication and tungsten inert gas（TIG） arc processes. Microstructural characterization and mechanics tests were conducted to evaluate the interfacial bonding quality. The results demonstrate that Fe-Sn/Fe-Sb intermetallic compounds（IMC） formed near the molten pool at the steel/lead interfaces， with IMC thickness nonlinearly decreasing from the pool center to the edge. The molten pool exhibites a peak hardness of 746HV. Tensile-shear specimens fractured on the lead alloy side， indicating superior interfacial bonding with a maximum strength of 49.6 MPa， far exceeding the engineering standard（10 MPa）. Shear failure demonstrates a ductile-brittle mixed fracture mode， with cracks likely initiating at micro-void clusters in the IMC layer and residual stress-concentrated regions.

GH5188 alloys were fabricated by LDED， and different heat treatments were subsequently applied to enhance the mechanics performance of LDED-fabricated （LDEDed） samples. The LDEDed GH5188 alloys exhibited a predominantly coarse columnar grain structure， with γ-Co matrix and M₂₃C₆ eutectic carbides distributed at the grain boundaries. The solution treatment promoted the segregation of solute elements， which acted as new nucleation sites and facilitated recrystallization as well as grain refinement. In addition， the initially coarse and irregular γ-Co/M₂₃C₆ eutectic phases enriched at grain boundaries were refined into finely dispersed particle-like precipitates， thereby strengthening the precipitation hardening effects. An excellent strength-ductility balance of LDEDed GH5188 alloys with an ultimate tensile strength of 857 MPa and an elongation of 42% is attained after solution treatment（1180 °C-1 h）. These results demonstrate that solution treatment effectively alleviates the coarse grain structure and uneven distribution of precipitates inherent to the LDEDed GH5188 alloys， thereby enhancing the overall mechanics performances.

To investigate WAAM trajectory planning， an automotive hub possessing multiple nodes was selected as a representative complex structure fabricated from 316L austenitic stainless steels. Initially， based on predetermined layer overlap ratios and overlap coefficients， the hub specimen model was decomposed into diverse grid structures characterized by thin walls and varying thicknesses； these structures were subsequently simplified at nodes to form an Euler circuit. An optimized deposition path was then derived by applying Fleury's algorithm in conjunction with Euler circuit theory， while a composite path filling strategy was implemented to plan the inter-layer filling patterns. Finally， the rationality of the trajectory planning methodology was validated through comparative analysis involving infrared thermometry across different layers and real-time imaging tracking of the arc and droplet transfer behaviors. The results demonstrate that the 316L austenitic stainless steel WAAM deposit， produced using the Fleury's algorithm-based trajectory plan， exhibits good geometric formation； furthermore， no localized filling defects occurred under the composite filling approach. Notably， the arc-active phase constitutes 70.62% of the total process duration within the planned path， effectively avoiding cross nodes， and the number of arc extinctions is reduced by two instances compared to scenarios lacking trajectory planning. The thermal histories exhibite similarity across layers， and the molten pool transition behavior remaines essentially consistent for each layer， collectively indicating the fundamental soundness of the adopted trajectory planning method.

Ceramic matrix composites applied in the aerospace fields needed to achieve structure-function integration， which posed higher requirements for the complex dimensionality and the efficient production. However， the traditional preparation processes with cumbersome equipment and operations， as well as long molding cycles， limited the further development of ceramic matrix composites in the related fields， additive manufacturing provided them with a solution for low-cost and efficient industrial production.The research progresses of additive manufacturing for ceramic matrix composites were reviewed， where the composition， characteristics， application fields， and development prospects in combination with additive manufacturing were systematically introduced. The applications， processing principles， characteristics， and mechanics properties of ceramic matrix composites prepared by selective laser sintering， stereo lithography appearance， direct ink writing， laminated object manufacturing， and binder jetting were examined. It is emphasized that challenges including raw material production， process optimization， and post-processing still need to be addressed in order to further enhance production efficiency and material performances.

Zirconia was employed as the raw material， and ceramic powder/polymer composite filaments were fabricated by combining a five-component binder system. Green specimens were prepared using the CME technology， and high-precision porous ZrO₂ bio-ceramic scaffolds were formed through a debinding and sintering process. The physical properties， microstructures， mechanics properties and biocompatibility of the scaffolds were experimentally characterized， and the relationships among processing， structure and properties of CME products were revealed. The results show that the densities of the sintered scaffold specimens range from 5.90 to 5.99 g/cm³ （97.44%~98.99% for relative densities）， the porosities are stable and controllable， and isotropic shrinkage effectively avoids the typical dimensional distortions of conventional sintering. The scaffold surfaces exhibit excellent hydrophilicity， their mechanics properties match those of human bone tissues， and they demonstrate good biosafety， with cell viabilities exceeding 60%.

Facing the lightweight manufacturing requirements of ceramic core for aeroengine turbine blade casting， the topology optimization design of lattice structure and the mechanics property regulation mechanism were systematically studied based on the photopolymerization additive manufacturing technology. Through the variable density topology optimization method， 12 kinds of monomer structures were simulated and analyzed. Combined with the actual working load of ceramic core for aeroengine turbine blades， the effects of monomer type， lattice size and filling direction on the performance of lightweight structure were studied. The results show that the triangular honeycomb and hexagonal honeycomb structures have better bearing performance than the curved surface/beam member structure due to the plane connection characteristics and the cooperative stress dispersion mechanism. The triangular honeycomb structure with lattice size of 1.5 mm has better mechanics properties（equivalent stress 15.05 MPa） in the direction of UVW filling. Based on the optimized parameters， the silicon oxide based ceramic core was successfully prepared， with a dimensional error is within ±0.05 mm and a bending strength of 30.7 MPa at room temperature.

The static mechanics experimental green specimens built with different processing parameters （i.e. layer thickness， ceramic powder content or filling angle） were formed using the material extrusion （ME） equipment to verify the formability of the self-made zirconia powder/polymer composite filament.The green specimens were then subjected to degreasing and sintering processes to obtain densified pure ceramic sintered specimens. Experimental studies on the physical and static mechanics properties of the sintered specimens were conducted respectively， exploring the influencing laws of different processing parameters on the static mechanics properties of the specimens. The results show that the two-step degreasing method has a good effectiveness， with the degreasing rate and density being 99% and 6.02 g/cm³， respectively. Increasing the content of ceramic powder may significantly reduce the dimensional shrinkage of sintered specimens. The layer thickness has a significant influence on their compression and bending properties， when the layer thickness increases to 0.3 mm， the compressive and bending strengths are dropped to 213.40 and 293.12 MPa， respectively.When the filling angle increases from 0° to 90°， the bending strength is decreased from 456.01 to 120.08 MPa.

Electronic 3D printing technology， leveraging its high-resolution manufacturing features， heterogeneous material integration capability， and customized design advantages， provided a revolutionary solution for advanced fabrication paradigms of organic thin-film transistors. The characteristics of three mainstream technologies—inkjet printing， aerosol jet printing， and direct ink writing were analyzed from the perspective of processing principles. Quantitative comparisons were conducted on their forming accuracy limits， multiphase material compatibility， and process robustness variations， followed by an exploration of the key challenges constraining their development. Furthermore， based on innovative application scenarios such as flexible displays， biomedical sensing， and wearable electronics， the research progresses in structure-performance relationships of 3D-printed OTFT devices for large-scale production were comprehensively reviewed. The paper highlights that future research priorities will focus on innovations in material formulation， optimization of printing processes， and reliability assessment of printing equipment， which are critical for advancing next-generation printed electronics.

An orthogonal experimental scheme for conductive line inkjet printing was designed， and a regression model of wire resistance and line width were established using RSM. The influences of different printing parameters on resistance and line width were analyzed. A multi-objective optimization model was established with printing speed， substrate temperature， and printing layers as optimization variables， and minimizing resistance and line width as optimization objectives. The IGWO algorithm was used to solve the model and determine the optimal process parameters. The accuracy and printing effectiveness of the regression model were verified through experiments. The results show that under the optimal printing parameters of a printing speed of 39 mm/s， a substrate temperature of 120 ℃， and 8 printing layers， the wire resistance is as 5.8 Ω and the line width is as 128.804 µm. Compared with the average resistance values and the line width values of the verification test line， the resistance and line width of the conductive lines under the optimal parameters are reduced by 66.8% and 61.3%， respectively. The average relative errors between the actual and predicted values of resistance and linewidth are 3.88% and 2.91%， respectively. Finally， three functional components including microstrip antennas， spiral circuits， and RFID tags are designed and printed， verifying the feasibility of the method.

To explore the dynamic behaviors of droplet impact and spreading and to further improve the efficiency of designing process parameters for droplet spreading， a dataset for an intelligent optimization algorithm was established based on a finite element model， and a prediction model based on extreme learning machine optimized by improved grey wolf optimizer（ELM-IGWO） was proposed. Using the initial droplet diameters， velocities， heights， and material contact angles as inputs， and maximum spreading diameters and central thicknesses of droplets as outputs， the dynamic behaviors of droplet impact and spreading were predicted. By comparing with the back propagation neural network（BP）， back propagation neural network optimized by genetic algorithm（BP-GA）， extreme learning machine（ELM）， and extreme learning machine optimized by grey wolf optimizer（ELM-GWO）models， it is found that the proposed algorithm has the greater accuracy in predicting the dynamic behaviors of droplet impact and spreading. In addition， the processing parameters of droplet impact and spreading were optimized by using an improved multi-objective non-dominant sorting genetic algorithm based on artificial neural networks（ANN-IMNSGA-Ⅱ），the experimental results show that the average relative error between the predicted maximum spreading diameters and the experimental data is as 3.54%， and the prediction error for the central thicknesses is as 5.71%.

To address the challenges of balancing low-frequency broadband noise reduction and lightweight design in aircraft cabin noise control within the aviation field， a design method for a multi-directional folded honeycomb structure （MFHS） acoustic metamaterial was proposed. The sound absorption unit of the MFHS was composed of a honeycomb cavity and a square insert tube. A theoretical sound absorption model was established based on the resonance principle， and the influence laws of three key structural parameters（the side length and height of the insert tube， and the length of the cavity） on the sound absorption performance were systematically investigated. The coupled performance of multiple units in parallel was analyzed to achieve broadband sound absorption. To better achieve the lightweight objective， a design method of multi-directional folding was adopted， and samples were fabricated using lightweight materials. Experimental results show that the fabricated MFHS sample achieves an average sound absorption coefficient of 0.85 in the frequency range of 400~1200 Hz， and the thickness of structure is only 35 mm， the areal density is as low as 7.04 kg/m². This realizes the synergistic design of low-frequency broadband efficient sound absorption and lightweight， offering a new idea for low-frequency noise control in the aviation field.

A vision-sensing-based dual-tracking continuous mobile 3D printing strategy was proposed to effectively improve the forming accuracy of mobile robotic 3D printing. Optical motion capture technology and blue-light laser triangulation scanning were employed to obtain the interlayer deviations among the mobile chassis， the end-effector of the printing manipulator， and the extruded filament under two printing modes： single-chassis tracking and chassis-manipulator collaborative tracking. Furthermore， the portability of the dual-tracking strategy was tested by printing models of different geometries. The results demonstrate that， compared with the semi-open-loop single-chassis tracking approach， the dual-tracking mobile 3D printing strategy with chassis-manipulator collaboration reduces the root mean square error（RMSE） of filament interlayer deviation from 5.3~13.0 mm to 1.4~2.3 mm， representing an improvement of 73.6%~88.0%. These findings verify the effectiveness and portability of the dual-tracking printing strategy in optimizing interlayer deviation.

To address the challenges of high complexity and computational costs in simulating satellite structures with body-centered cubic（BCC） lattice fills，an equivalent modeling approach was proposed. A mechanics equivalent model for lattice core sandwich panels was established using Timoshenko beam theory and sandwich theory， and a strut length correction parameter was introduced to improve the accuracy. Simulation and experimental results show that under constrained modal conditions， the equivalent model reduces the number of mesh elements to 0.48% of the original， with a maximum error in the first six natural frequencies of no more than 5.60%， while maintaining consistent mode shapes. Satellite dynamic analysis further confirmed the effectiveness of the equivalent model in global modal analysis and harmonic response analysis. The method significantly reduces modeling difficulty and computational costs， and provides reliable technical support for the design of batch-produced satellite lattice structures.

Key technologies and research advancements concerning machine vision for tool wear condition monitoring were systematically reviewed. Starting from detection objects， correlations between wear features and conditions， as well as extraction methods， were discussed. Typical monitoring systems， including offline， on-machine static， and dynamic monitoring systems were outlined. At the level of detection methods， detection processes and key methods based on traditional image processing were systematically summarized， and applications of artificial intelligence technologies in these detection fields were elaborated. Advantages and limitations of various visual detection technologies were summarized， and future key research directions were projected. Leaps from two-dimensional to high-precision three-dimensional dynamic detections， upgrades from single-vision to multi-sensor fusion anti-interference systems， and implementations of generalized algorithms and edge deployments from laboratories to production lines were proposed to be achieved， aiming to provide systematic references for related researches and applications.

Motion analysis in working scenarios of mobile robots might assist in promptly identifying and resolving dynamic issues during operations， and played a significant role in ensuring the reliable functioning of the robots. A mobile robot motion monitoring and interaction system was designed based on augmented reality technology. By adopting the method of integrating natural features and data communication， the dynamic tracking and registration of mobile robots with relative motion among internal structures components were achieved. Based on the motion analysis strategy， mechanical failure prediction， stability prediction， workspace safety guarantee of robots， motion preview， and teaching were carried out. The prototype system verified the feasibility and effectiveness of the proposed motion analysis strategy.

Multi-objective control method of slipping， friction torque and cage-roller collision force of cylindrical roller bearings was specially studied. An U-pocket cylindrical roller bearings was proposed.The conformal dynamic contact lubrication model of the U-pocket-roller was established based on the dynamic Reynolds equation and the Winkler elastic foundation model， and by use of the Newton-Euler dynamics theory， the dynamics model of the bearing was set up， and by use of the finite difference， multi-grid， and Runge-Kutta integration methods， the coupling solution of the pocket lubrication and bearing dynamics models were implemented. Multi-objective control capability of the novel bearing and the ordinary bearing on cage slip， friction torque， cage-roller collision force and cage whirl under high-speed conditions were compared and analyzed， and influence laws of geometric parameters such as roller groove depth， pocket clearances and cage guide clearances on cage slip rate， friction torque and cage-roller collision force of the novel bearings were researched. The results show that control ability of the novel bearings on cage slip rate， friction torque， cage-roller collision force and cage whirl is significantly better than that of the ordinary bearings； increase of roller groove depth will reduce cage slip rate， friction torque and cage-roller collision force； increase of pocket clearances will increase the cage slip rate， but will reduce friction torque and cage-roller collision force； increase of guide clearances will increase cage slip rate， friction torque and cage-roller collision force.

Horseshoe-shaped microstructures possessed excellent characteristics such as high stretchability， high air permeability， and topological programmability， and were widely used in important fields including biomedical devices， flexible displays， and tissue engineering. Based on the BCT2000 test principle and GB/T 24218.5-2016 steel ball bursting test method， a test method for out-of-plane deformations of horseshoe-shaped microstructures was established herein， and the out-of-plane deformation behaviors of three types of bionic horseshoe-shaped microstructures （triangular， Kagome， and honeycomb-shaped） were systematically studied. The bursting load-displacement curves of the three types of horseshoe-shaped microstructures were studied through numerical simulations and experimental analyses， the stress distribution and the out-of-plane deformations of the structures were analyzed， and triangular linear structures were used as the control group. Flexible-elastic performance evaluation criteria were established from four aspects， and the effects of four factors on flexible-elastic performances were initially analyzed. Triangular microstructures exhibit the most excellent comprehensive flexible-elastic performance and have obvious flexible-elastic advantages compared with traditional linear structures. Specifically， their maximum out-of-plane displacements are increased by 88.9%， the low-load bearing displacements are increased by 428.1%， the out-of-plane stiffness is reduced by 59.3%， and the energy absorption capacity is increased by 31.5%.

Aiming at the lifespan bottlenecks of the bionic flapping-wing aircraft drive mechanisms caused by hinge wear， a dynamic reliability assessment method was proposed considering clearance hinges. Based on the working principle of the flapping-wing aircraft drive mechanisms， the failure modes of the mechanisms were analyzed， and wear and motion asymmetry were established as the key failure modes. A non-uniform wear dynamics model was developed by integrating the Hertz contact force model and the Archard wear theory. The wear profile was reconstructed by drawing spline curves through discrete control points， enabling dynamic update simulation for multiple cycles of wear. Building upon the active learning method combining Kriging and Monte Carlo simulation（AK-MCS） and considering competitive failure modes， improved-AKMCS was used to quantify the competitive failure mechanism between hinge wear and rocker motion asymmetry. The results indicate that wear failure dominates the first 65 000 operation cycles of the mechanisms； until 68 000 cycles， the failure due to motion asymmetry intensifies， and the overall reliability drops from 0.9989 to 0.0165. Sensitivity analysis confirms that the elastic modulus， wear coefficient， and initial hinge clearance have significant correlations with reliability.

Several sheet metal forming experiments were conducted on the ship three-dimensional computational numerical control bending machine， and corresponding numerical method was validated by these experimental results. Considering actual production needs and processing accuracy， the Latin hypercube sampling method was employed to generate sampling points by intervals for model training， with the corresponding dataset obtained through numerical simulations and experimental validations. A constitutive equation-embedded deep learning neural network（CE-DNN） model was developed by optimizing the visual geometry group（VGG） network architecture through the integration of material-informed convolutional layers， thereby establishing a multi-parameter coupled learning system that synthesized material properties， thickness， and geometric features. The performance of the proposed model under data-constrained scenarios was quantitatively evaluated through data extrapolation and training set reduction strategies. Results demonstrate that the proposed model exhibites certain robustness when the training data for material， thickness， and shape parameters are reduced， while maintaining generalization capability in springback extrapolation prediction.

To improve the nosing forming accuracy of the ellipsoid rings with large diameter-thickness ratio， the springback deformation and the die optimization design were studied. The springback distribution of the nosed rings was analyzed by the finite element model. The influences of forming parameters on the springback of the nosed rings were investigated by the orthogonal design. Based on the displacement adjustment method， the springback compensation of the nosed rings was studied. The nosing die with reinforced ribs was proposed based on the equal-thickness bowl structure. The sensitive structure parameters were obtained by Plackett-Burman Design screening method. The response surface model was established by Box-Behnken Design response surface method， and the optimized structural parameters were obtained by the automatic optimization algorithm. The results show that the springback of the nosed rings at the mouth region is obvious， and the springback in the middle and bottom regions is small. The maximum springback of the nosed rings with the diameter-thickness ratio of 127.66 is 0.92 mm. The degree of influences of forming parameters on the springback of ellipsoid rings was ranked as follows： nosing die ellipticity，rings diameter-thickness ratio，friction coefficient，nosing speed. The maximum springback of the nosed rings is reduced from 0.92 mm to 0.05 mm after two springback compensations. The peak stress of the nosing die is reduced by about 27.5% by adjusting the structure layout and optimizing the structure parameters， resulting in effectively reducing the stress concentration. Finally， the verification of the nosing process was conducted for the ring part with large diameter-thickness ratio. The nosed ellipsoid rings exhibite a smooth surface without wrinkling， and the errors of the mouth diameter are much less than 5%. The maximum deviations between different contours are less than 0.25 mm， which clearly demonstrates the feasibility of the design method of the nosing dies.

Aiming at the challenges in ship narrow-space welding， such as the restricted workspace， multiple constraints on torch posture， high risk of trajectory interference， and poor welding accessibility， a time-optimization scheme was proposed for welding trajectory optimization based on an improved IGA-PSO， to achieve welding with the robotic arm in the shortest time. Three-dimensional models of the portable robots， workpiece， and working scene were constructed， the motion logic of the robots was clarified， and the welding trajectory model and processes were established. A multi-objective constrained fitness function was designed by comprehensively considering both welding time and accessibility， and the objective functions for time optimization and accessibility rate were formulated. By integrating the genetic and particle swarm algorithms， improvements were introduced： a linearly decreasing and exponentially decreasing mechanism for the inertia weight was adopted； the learning factors were designed for exploration， exploitation， and convergence stages； and the mutation operation was adjusted nonlinearly， thereby enhancing the algorithm's performance. Algorithm testing， simulation verification， and on-site validation were carried out through a case study to verify the proposed method. The results show that the optimized robotic arms exhibit smooth displacement， velocity， and acceleration curves without abrupt changes， and the welding accessibility reaches 90%， which verifies the effectiveness of the IGA-PSO.

To reveal the cutting and sliding dynamics behaviors and the influence law of cantilever roadheader systems， an improved D-H parameter method was adopted to construct the kinematics model of roadheader sliding motions， and the mechanism of pose parameters on the spatial morphology of cutting cross-section was clarified. A dynamics model of roadheader pose sliding was established based on the Lagrange equation， and combined with Simulink theoretical calculation and ADAMS multi-body dynamics simulation， the dynamic response characteristics of cutting poses were systematically analyzed under various working conditions such as different working slopes and coal-rock hardness. Finally， an industrial experimental platform for roadheader pose sliding was constructed. The results show that the established dynamics model of roadheader pose sliding may well reveal the pose sliding characteristics during cross-section cutting processes， where the displacement offset deviation is approximately 15%~30%， and the attitude offset errors are controlled within 10%. Through multi-dimensional analysis methods， the dynamic evolution law of cantilever roadheader cutting sliding was systematically elucidated， and a complete theoretical framework covering kinematics modeling， load calculation， and dynamic response analysis was established.

Through the mechanics property calibration tests of magnesium alloy materials， the Johnson-Cook constitutive and fracture failure models were constructed， and a simulation model of the solid self-piercing riveting processes was established to analyze the plastic deformations and stress distribution of the materials in the mechanics interlock areas. A three-factor and three-level response surface experiment was carried out to reveal the main effects and interaction laws of the processing parameters， and to explore the optimization path of processing parameters. Simulation analysis and experimental results show that， the established regression model has high reliability for engineering applications and compared with the traditional self- piercing riveting， the use of solid self-piercing riveting and the optimization of riveting parameters may suppress the appearance of macroscopic cracks on the surfaces and inside the mechanics interlock deformation areas， and achieve efficient and reliable connection of magnesium/aluminum dissimilar thin- sheet materials. The maximum failure load under the optimal parameter combination obtained from the regression model is 3359 N， and the maximum energy absorption value is 5.59 J.