This package contains the data presented in the following publication: F.P. van der Meer, S. Raijmaekers and I.B.C.M. Rocha, "Interpreting the single fiber fragmentation test with numerical simulations", Composites Pt. A, 2019. All data have been generated with simulations with in house finite element code as described in the paper. Simulation results have been processed to generate the relevant plots for the paper. The data stored here is the processed data as used for generating the plots.

Reinforced concrete is one of the most critical composite materials in the modern civil engineering and can improve the tensile resistance of concrete. Its passivation film plays an important role in the durability of concrete and the steel corrosion. But, due to the size limitations, the destruction of micro-scale steel bars has not been well studied. In this work, the reactive molecular dynamics simulation was employed to studying the mechanical properties of the steel and its passivation film. The uniaxial stretching of different compounds of γ-FeOOH, γ-Fe2O3 and Fe was performed. We found that the oxidation can reduce the tensile strength of steel. For the three compounds of γ-FeOOH, γ-Fe2O3 and Fe, the order of tensile strength from high to low is Fe > γ-Fe2O3 > γ-FeOOH. But, the ductility of γ-FeOOH under x direction is increased. The detail microstructure analysis shown that the difference of tensile strength is origin from the coordination in the materials. The two kinds of stretching processes of whole system stretching (in the Fe phase and x direction of γ-FeOOH phase) and partly area stretching (in the Fe2O3 phase and z direction of γ-FeOOH phase) were clarified. The external force is dispersed in whole system stretching but opposite in partly area stretching. This investigation leads to possible new direction for studying the tensile strength of materials, and the strategy of evaluating materials tensile strength can supply valuable information in evaluating and improving the mechanical properties of reinforced concrete.

While silicon anodes offer transformative energy density for lithium-ion batteries, their large volume changes during cycling critically challenge binder systems. Current dynamic hydrogen-bonding binders suffer from compromised mechanical robustness and limited stress dissipation in high-power applications. We present an alginate-tannic acid (Alg-TA) hybrid binder that synergistically integrates dynamic H-bonding reversibility with multidimensional network reinforcement. The Alg-TA system establishes adaptive interfacial interactions with micron-sized silicon dendrites (SD-OH, ~15 µm), creating a self-healing matrix that redistributes mechanical stress through its hierarchical hydrogen-bonded architecture. Finite element simulations quantitatively demonstrate the binder's exceptional stress dissipation capability. The optimized electrode delivers remarkable cycling stability (retained a capacity of 1484.76 mA h g⁻¹ after 400 cycles at 4 A g⁻¹, with 80.2% capacity retention). This work provides fundamental insights into designing dynamic binder networks that reconcile mechanical integrity with electrochemical resilience, establishing a practical pathway for silicon anode implementation in next-generation high-energy batteries.Characterization X-ray diffraction (XRD) analysis of the phase composition and crystal structure was performed using a Bruker D8 Advance instrument. Fourier transform infrared (FTIR) spectroscopy was conducted on a Thermo Scientific Nicolet iS20 instrument to analyze the chemical bonds and functional groups of the samples. X-ray photoelectron spectroscopy (XPS) measurements were carried out using a Thermo Scientific K-Alpha instrument. The mechanical properties of the polymer binders and anodes were evaluated by tensile and 180° peel tests using an electronic universal testing machine. The viscosity of the binder samples was measured using an SNB-2 digital viscometer. Thermogravimetric analysis (TGA) was performed on a STA-8000 instrument, with a heating rate of 10 °C/min in the temperature range of 30-800 °C. The glass transition temperature (Tg) of the binder was measured using a Differential Scanning Calorimeter (DSC), and the testing conditions were the same as those used in the TGA analysis. Scanning electron microscopy (SEM) imaging of the samples and anodes was conducted on a ZEISS Sigma 300 instrument. Transmission electron microscopy (TEM) was performed using a JEOL JEM-F200 instrument. The specific surface area and pore size of the samples were measured using a Micromeritics ASAP2460 nitrogen adsorption-desorption instrument. The wettability of anodes was evaluated by contact angle measurements using a Contec TX500 TM rotational drop interfacial tensiometer.Electrochemical Measurements The button cell was assembled in a glove box filled with a high-purity argon atmosphere. For the half-cell, the positive electrode consisted of the prepared silicon electrode, and the negative electrode was a 16 mm diameter lithium metal disc. Celgard 2325 served as the separator, while the electrolyte was composed of 1 M LiPF6 in a 1:1 volume ratio of ethylene carbonate (EC) and diethyl carbonate (DEC), incorporating 10 vol% fluoroethylene carbonate (FEC) as an additive. Before all tests, the batteries are left to rest at 30 °C for 24 h. The galvanostatic charge-discharge (GCD) and cyclic voltammetry (CV) tests were conducted at 30 °C within a voltage range of 0.01 V to 2.00 V using the Neware CT-4008 battery testing system and CHI760E electrochemical workstation, respectively. Electrochemical impedance spectroscopy (EIS) was also performed on the CHI760E, with a frequency range of 10⁻² to 10⁵ Hz and an amplitude of 5 mV. Galvanostatic intermittent titration technique (GITT) tests were carried out using the Neware CT-4008 system after three activation cycles at 0.2 A g⁻¹, starting with a current pulse time of 10 minutes, followed by a 1-hour relaxation period.Simulation The finite element simulation was conducted using COMSOL Multiphysics 6.2 establishing an electrochemical-solid mechanics multiphysics model. To simulate the distribution of silicon particles in the conductive agent and binder composite material, a random distribution model was adopted. In this model, active silicon particles are randomly distributed in the carbon gel phase composed of the conductive agent and binder, forming a typical two-phase composite material structure. This model is used to evaluate the stress effects between silicon particles and the conductive polymer network during the lithiation process, thus predicting the mechanical behavior of the anodes. Additionally, representative volume elements (RVEs) were designed to simulate typical micro-regions within the anodes. Also, a random sequential adsorption algorithm was employed, where silicon particles were adsorbed into the volume element in a specific order, thereby constructing the composite material structure. Finally, simulation analysis was conducted based on physical parameters of silicon and its various alloy states, which were obtained from first-principles calculations.

This Phase I Small Business Innovative Research project proposes to develop a multiscale computational methodology capable of accurate prediction of the properties and performance of insulating ablative materials that are used to protect the re-entry of vehicles from excessive thermal loads. In particular, this effort will focus on multi-million atom, reactive molecular dynamics (MD) simulations of pyrolysis of phenolic resins enhanced with carbon nanotubes (CNT). The results will reveal the role of CNT interface on the reaction and the thermo-mechanical properties. The derived interfacial strength characteristics will then be incorporated into continuum-level simulations. The outcome of Phase I will provide a benchmark to perform MD simulations on pyrolysis of resin composites and methodology development to link atomistic-level with continuum-level simulations. Phase II will involve MD simulations on multi-walled, functionalized CNTs in cross-linked resin, optimization of the multi-scale modeling methodology and experimental validation. The outcome of the multiscale computational program will involve a detailed parametric study to find optimal parameters at multiple scales including: nanofiller diameter size, volume fraction and functionalization of nanotubes and μm-sized carbon fibers. These parameters will be optimized to best meet Orion vehicle¡¦s TPS challenges. The team involves engineers from ACT and researchers from Rensselaer Polytechnic Institute.