Simulated Diffusion Coefficients Research Articles

Diffusivities and Atomic Mobilities in BCC Ti-Fe-Cr Alloys.

In this research, the diffusion behaviors within the Ti-Fe-Cr ternary system were examined at the temperatures of 1273 K and 1373 K through the diffusion couple technique. This study led to the determination of both ternary inter-diffusion and impurity diffusion coefficients in the body-centered cubic (bcc) phase for the Ti-Fe-Cr alloy, utilizing the Whittle-Green and Hall methods. The statistics show that the average diffusion coefficients D˜FeFeTi and D˜CrCrTi measured at 1273 K were 1.34 × 10-12 and 3.66 × 10-13, respectively. At 1373 K, the average values of D˜FeFeTi and D˜CrCrTi were 4.89 × 10-12 and 1.43 × 10-12. By adopting the CALPHAD method, a self-consistent database for atomic mobility in the bcc phase of the Ti-Fe-Cr system was established. This database underwent refinement by comparing the newly acquired diffusion coefficients with data from the existing literature. Diffusion simulations for the diffusion couples were performed, drawing on the established database. The error between the simulated diffusion coefficient and the experimental measurement data is within 15%, and the simulated data of the component distance distribution and diffusion path are in good agreement with the experimental data. The simulations generated results that aligned well with the observed experimental diffusion characteristics, thereby affirming the reliability and accuracy of the database.

Robust solid slippery surface for anti-corrosion: Experimental and simulation

Corrosion has long been an enduring obstacle for researchers. It is a challenge to make progress in corrosion protection technology and understanding corrosion mechanisms for quite some time. In recent years, the slippery surface has been applied for anti-corrosion. This novel surface gives new expectation to corrosion protection technicians. Even though some researchers have constructed lots of slippery surfaces for anti-corrosion, the robustness should be improved and the intrinsic anti-corrosion mechanism also needs to be clarified. Therefore, we fabricated a solid slippery surface (SSS) via electrodeposition combined with hydrothermal method followed by solid lubricant infused into a micro-nano “metasequoia” structure. The anti-abrasion performance was enhanced due to the special structure as well as the solid lubricant. Besides, the SSS showed thermal assisted self-healing property even after experienced abrasion. The corrosion resistance was evaluated by electrochemical experimental with the potentiodynamic polarization curve and alternating-current impedance technique. The Ecorr and Icorr of SSS were 0.029 V and 2.121 × 10−9 A·cm−2, respectively. Furthermore, the diffusion behavior and relative concentration of corrosive particles were analyzed by the molecular dynamics simulation method. The simulation results showed that the as-prepared SSS can provide a very superior anti-corrosion property with a simulated diffusion coefficient of 2.2 × 10−9 m2·s−1 for Cl−. This work provides technical guidance and theoretical support for the application of SSS in corrosion protection and can provide a reference for the anti-corrosion mechanism of SSS.

Anisotropy in particle orientation controls water diffusion in clay materials

Clay minerals are used in a wide number of natural or artificial materials for municipal or nuclear waste management in which water diffusion is the principal transfer process. However, a quantitative assessment of the impact of the preferred orientation of lamellar clay particles on water diffusion is still lacking. Using 3D Brownian dynamics simulation on representative virtual clay porous media, a systematic study of water diffusion for single-porosity (illite or kaolinite) and dual-porosity (vermiculite) systems was conducted. The simulated water diffusion coefficients were validated through comparison with experiments and were used to build an Archie model including the degree of anisotropy in particle orientation. The results showed that water diffusion can be predicted based on a correct description of the solid phase organization and that clay particle orientation, such as interparticle porosity, is a primary parameter governing water mobility. Moreover, the anisotropy of water diffusion can be linked to the degree of particle preferred orientation, irrespective of the porosity value. The modified version of the Archie model for water diffusion in clay systems proposed here has many potential applications where decoupling of porosity and preferred orientation is needed, including better prediction of water transfers or improved designs of clay liners with sustainable use of natural mineral resources.

Relevance of diffuse-layer, Stern-layer and interlayers for diffusion in clays: A new model and its application to Na, Sr, and Cs data in bentonite

The diffusive flux of cations is enhanced and that of anions is decreased compared to that of water tracers in bentonite or other clays, as a result of electrostatic interactions between ions and the charged clay surfaces. Clays are often used or foreseen as barriers in waste disposal in order to protect the environment from hazardous materials. A consistent description of diffusion of various ions and uncharged species is important in this context, especially if long-term interactions between clays and other materials shall be predicted by reactive transport simulations. Here, diffusion of a suite of tracers (HTO, Cl, Na, Sr and Cs) in bentonite was investigated. Experimental through-diffusion data at different bentonite dry densities were described with models of increasing complexity. First, ‘standard’ empirical single ion transport models (uncoupled, simple Fickian diffusion) were applied for each density. These models served as reference cases for comparisons. For sorbing tracers (Na, Sr, Cs), surface diffusion models were used in a next step, where average surface mobilities for the cations were determined based on comparisons with transport parameters from HTO diffusion. Finally, a more complex model was developed in order to describe anion and cation diffusion in a coupled way. This model accounts for locally parallel diffusion in different environments, namely in ‘free’ water unaffected by surface charges, in diffuse (Donnan) layer water, within the Stern layer, and within interlayer water (D-S-I model). This coupled model requires additional parameters related to the bentonite microstructure as well as to cation mobilities in the Stern layer and in the interlayer. The latter were taken from literature. Microstructural parameters were constrained in a manner that overall anion exclusion matches anion accessible porosities found by the simple Fickian diffusion model. This was possible with a reasonable choice of microstructure parameters that are consistent with literature values. A good agreement between the experimental data and the simulated cation diffusion coefficients of the D-S-I model was found, using constraints by the HTO and Cl diffusion data. The interlayer pathway was found to be most important for diffusion of Na, Sr and Cs through bentonite. Stern layer diffusion was significant and more important than diffusion through the diffuse layer for Cs and Sr, while for Na the two pathways were of equal importance.

Molecular Dynamics Study of CO2 Phase Change Transport in the Near-Critical Region: Model Parameter Optimization

The technical development of supercritical CO2, energy systems, CO2 capture, and other applications has become a hot topic in recent years. Therefore, molecular dynamics simulation (MD) of CO2, especially the investigation at the CO2 supercritical region is urgently needed. This study focused on the optimization of common CO2 potential model EPM2 (elementary physical model—2) combined MD forcefield OPLS-AA (optimized potentials for liquid simulations—all atom) and CHARMM (chemistry at Harvard macromolecular mechanics for MD simulation). Through adjusting angle parameters according to EPM2, vapor-liquid equilibrium curve, critical point and supercritical region could be well corresponding with experiments, which can be more accurate than previous approaches. The simulated results using 179.63° in OPLS-AA forcefield can not only correspond to supercritical phase of near-critical region (within ±10% error range under CO2 is at 468 kg/m3, 304.2–320 K, 7.2–10.0 MPa), but also be consistent with actual CO2 properties in gas phase of near-critical region (temperature range can reach 304.2–350 K while the density scope can reach 15–168 kg/m3). Besides, optimized potential model also has a certain reliability on the investigation of CO2 diffusion properties. The values simulated have the same order of magnitude as literature values, especially simulated diffusion coefficient values at gas phase. The CO2 property of heat capacity is also simulated, and the errors are within ±15%. That is to say, the optimized CO2 potential parameter also has a certain accuracy to analyze CO2 heat transfer. The angle value optimized in this study may be useful for the fundamental understanding of the supercritical state and it can well be applied in the further investigation of CO2 systems.

Study on the dynamics mechanism of methane diffusion in coal under microwave heating

To study the effects of microwave on the methane desorption characteristics of coal, the structural parameters of Pingdingshan coal were obtained through X-ray diffraction (XRD) and mercury intrusion test. Then the coal molecular structure models were established. The adsorption of CH4 was simulated using Materials Studio. Finally, the combination of methane desorption experiments and molecular simulations were adopted to investigate the effects of microwave on the methane desorption characteristics, and the microscopic mechanism was analyzed. The results show that: the effect of microwave on the structure of coal is mainly reflected in the change of crystallite diameter (La). For the macro perspective, the average pore diameter, total pore volume, porosity and permeability of the coal increase and the total specific surface area decreases after microwave heating. Microwave heating leads to the decrease in adsorption pores, the increase in percolation pores and microfractures, and the enhancement of inter-pore connectivity. The simulated transport diffusion coefficients were in good accordance with the methane desorption experimental results, indicating that microwave heating helps methane to diffuse out of the coal.

Simulation Investigation of Bulk and Surface Properties of Liquid Benzonitrile: Ring Stacking-Assessment and Deconvolution.

The content and the molecular dynamics (MD) simulation analysis here are inspired by our recent ab initio calculation on benzonitrile (BZN), whereas the present results are to expand and develop macroscopic documentation involving data verification. MD simulations of the bulk liquid BZN in the range of 293–323 K unravel the hydrogen bond (−C≡N···H) formation with strength in the order of ortho-H ≫ meta-H ∼> para-H. The possibility for ortho-Hs to get involved in the formation of two bonds simultaneously confirms each having σ- and π-bonding features. Accordingly, we used vast efforts for structural analysis particularly based on the deconvolution of the corresponding complex correlation functions. Specific angle-dependent correlation functions led to the recognition of the molecular stacking with a strict anti-parallel orientation. The in-plane dimer and trimer also take part in the structural recognition. A singularity, found in the trend of the simulated temperature-dependent viscosity and diffusion coefficient of liquid BZN, is centered at about 313 K and quite fascinatingly emulates the reported experiment viscosity. An interplay between a small change in the trend of density and a large change in the corresponding viscosity is a key factor in supporting the singularity. Deconvolution of the simulation results allows attributing the singularity to structural alteration involving H-bonding of different types and extent. Approaching the range of 308–313 K, an alteration between hydrogen bond formation involving mostly ortho-Hs and mixed ortho-Hs + meta-H is possible and supports the singularity.

Scale dependence of tortuosity and diffusion: Finite-size scaling analysis

Physical and hydraulic properties of porous media are routinely measured/simulated at smaller scales e.g., pore and core. However, their determination at larger scales e.g., field and reservoir has still been a great challenge. Although understanding the scale dependence of transport modes in rocks and soils is essential, the porous media community still lacks in a solid theoretic framework. In this short communication, we propose finite-size scaling analysis from physics to investigate the scale dependence of tortuosity and diffusion coefficient. By comparing with two- and three-dimensional simulations, we demonstrate that the finite-size scaling analysis is a powerful approach. More specifically, we show that the plot of simulated tortuosity or diffusion coefficient versus scale looks scattered. However, after applying the finite-size scaling analysis, the data collapse together showing a quasi-universal trend.

Study on Li ion diffusion in LixV2O5 using first principle calculations and kinetic Monte Carlo simulations

We study the Li diffusion in Li x V2O5 ()—a potential cathode material for Lithium ion batteries. Different diffusion pathways in this material with dependence on the Li ion concentration are investigated by applying first-principles calculations. The results are used to obtain the corresponding diffusion coefficients by employing two complementary methodologies: Kinetic Monte Carlo (KMC) simulations and a statistical thermodynamics approach. The KMC simulations for two different crystal planes give new evidence that the diffusion occurs mainly along the [010] direction, while the corresponding diffusion coefficients show a temperature dependence obeying Arrhenius’ Law. The necessity of the consideration of concentration-dependent barrier heights in the KMC simulations are demonstrated by looking at the significant changes of the concentration-dependence of the diffusion coefficients. The simulated diffusion coefficients of the combined approach show a good quantitative agreement with experimental data reported previously.

Heterogeneous dynamics, correlated time and length scales in ionic deep eutectics: Anion and temperature dependence.

Heterogeneous relaxation dynamics often characterizes deep eutectic solvents. Extensive and molecular dynamics simulations have been carried out in the temperature range, 303 ≤ T/K ≤ 370, for studying the anion and temperature dependencies of heterogeneous dynamics of three different ionic acetamide deep eutectics: acetamide + LiX, X being bromide (Br-), nitrate (NO3 -), and perchlorate (ClO4 -). These systems are chosen because the fractional viscosity dependence of average relaxation rates reported by various measurements has been attributed to the heterogeneous dynamics of these systems. Simulations performed here attempt to characterize the heterogeneous relaxation dynamics in terms of correlated time and length scales and understand the solution inhomogeneity in microscopic terms. Additionally, simulation studies for pure molten acetamide have been performed to understand the impact of ions on motional features of acetamide in these ionic deep eutectic systems. The computed radial distribution functions suggest microheterogeneous solution structure and dependence upon anion identity and temperature. A significant plateau in the simulated time dependent mean squared displacements indicates pronounced cage-rattling and inhomogeneity in relaxation dynamics. Simulated diffusion coefficients for acetamide and ions show decoupling from the simulated viscosities of these deep eutectics. Calculated two- and four-point correlation functions reveal the presence of dynamic heterogeneity even at ∼180 K above the measured thermodynamic glass transition temperature (Tg). Further analyses reveal the existence of multiple timescales that respond strongly to the rise in solution temperature. The simulated dynamic structure factor and overlap function relaxations show strong stretched exponential relaxations. The simulation results support the experimental observation that the bromide system is the most dynamically heterogeneous among these three systems. Correlated length scales show much weaker anion and temperature dependencies with an estimated length of ∼1 nm, suggesting formation of clusters at the local level as the origin for the micro-heterogeneous nature of these ionic deep eutectics.

Improved Parameterization of Protein-DNA Interactions for Molecular Dynamics Simulations of PCNA Diffusion on DNA.

As the field of molecular dynamics simulation utilizing the force fields is moving toward more complex systems, the accuracy of intermolecular interactions has become a central issue of the field. Here, we quantitatively evaluate the accuracy of the protein-DNA interactions in AMBER and CHARMM force fields by comparing experimental and simulated diffusion coefficients of proliferating cell nuclear antigen. We find that both force fields underestimate diffusion coefficients by at least an order of magnitude because the interactions between basic amino acids and DNA phosphate groups are too attractive. Then, we propose Lennard-Jones parameters optimized using the experimental osmotic pressure data of model chemicals, by using which one can reproduce the experimental diffusion coefficients. Newly optimized parameters will have a broad impact on general protein-DNA interactions.

SpinDoctor: A MATLAB toolbox for diffusion MRI simulation

The complex transverse water proton magnetization subject to diffusion-encoding magnetic field gradient pulses in a heterogeneous medium can be modeled by the multiple compartment Bloch-Torrey partial differential equation. Under the assumption of negligible water exchange between compartments, the time-dependent apparent diffusion coefficient can be directly computed from the solution of a diffusion equation subject to a time-dependent Neumann boundary condition.This paper describes a publicly available MATLAB toolbox called SpinDoctor that can be used 1) to solve the Bloch-Torrey partial differential equation in order to simulate the diffusion magnetic resonance imaging signal; 2) to solve a diffusion partial differential equation to obtain directly the apparent diffusion coefficient; 3) to compare the simulated apparent diffusion coefficient with a short-time approximation formula.The partial differential equations are solved by P1 finite elements combined with built-in MATLAB routines for solving ordinary differential equations. The finite element mesh generation is performed using an external package called Tetgen.SpinDoctor provides built-in options of including 1) spherical cells with a nucleus; 2) cylindrical cells with a myelin layer; 3) an extra-cellular space enclosed either a) in a box or b) in a tight wrapping around the cells; 4) deformation of canonical cells by bending and twisting; 5) permeable membranes; Built-in diffusion-encoding pulse sequences include the Pulsed Gradient Spin Echo and the Oscillating Gradient Spin Echo.We describe in detail how to use the SpinDoctor toolbox. We validate SpinDoctor simulations using reference signals computed by the Matrix Formalism method. We compare the accuracy and computational time of SpinDoctor simulations with Monte-Carlo simulations and show significant speed-up of SpinDoctor over Monte-Carlo simulations in complex geometries. We also illustrate several extensions of SpinDoctor functionalities, including the incorporation of T2 relaxation, the simulation of non-standard diffusion-encoding sequences, as well as the use of externally generated geometrical meshes.

Quantification of Ostwald Ripening in Emulsions via Coarse-Grained Simulations.

Ostwald ripening is a diffusional mass transfer process that occurs in polydisperse emulsions, often with the result of threatening the emulsion stability. In this work, we design a simulation protocol that is capable of quantifying the process of Ostwald ripening at the molecular level. To achieve experimentally relevant time scales, the dissipative particle dynamics (DPD) simulation protocol is implemented. The simulation parameters are tuned to represent two benzene droplets dispersed in water. The coalescence between the two droplets is prevented via the introduction of membranes, which allow diffusion of benzene from one droplet to the other. The simulation results are quantified in terms of the changes in the droplet volume as a function of time. The results are in qualitative agreement with experiments. The agreement with the Lifshitz-Slyozov-Wagner theory becomes quantitative when the simulated solubility and diffusion coefficient of benzene-in-water are considered. The effect of two different surfactants was also investigated. In agreement with both experimental observations and theory, the addition of surfactants at moderate concentrations decreased the Ostwald ripening rate because of the reduction in the interfacial tension between benzene and water; as the surfactant film becomes dense, other phenomena are likely to further delay the Ostwald ripening. In fact, the results suggest that the surfactant that yields higher density at the benzene-water interface delayed more effectively Ostwald ripening. The formation of micelles can also affect the ripening rate, in qualitative agreement with experiments, although our simulations are not conclusive on such effects. Our simulations show that the coarse-grained DPD formalism is able to capture the molecular phenomena related to Ostwald ripening and reveal molecular level features that could help to understand experimental observations. The results could be useful for predicting and eventually controlling the long-term stability of emulsions.

Translation from murine to human lung imaging using x-ray dark field radiography: A simulation study.

Recent studies on murine models have demonstrated the potential of dark field (DF) x-ray imaging for lung diseases. The alveolar microstructure causes small angle scattering, which is visualised in DF images. Whether DF imaging works for human lungs is not a priori guaranteed as human alveoli are larger and system settings for murine imaging will probably have to be adapted. This work examines the potential of translating DF imaging to human lungs. The DF contrast due to murine and human lung models was studied using numerical wave propagation simulations, where the lungs were modelled as a volume filled with spheres. Three sphere diameters were used: 39, 60 and 80 μm for the murine model and 200, 300 and 400 μm spheres for the human model. System settings applied for murine lung response modelling were taken from a prototype grating interferometry scanner used in murine lung experiments. The settings simulated for human lung imaging simulations combine the requirements for grating interferometry and conventional chest RX in terms of x-ray energy and pixel size. The DF signal in the simulated murine model was consistent with results from experimental DF data. The simulated linear diffusion coefficient for medium alveoli diameters was found to be (1.31±0.01)⋅10−11 mm-1, 120 times larger than those of human lung tissue ((1.09±0.01)⋅10−13 mm-1). However, as the human thorax is typically a factor 15 times larger than that of murine animals, the overall DF effect in human lungs remains substantial. At the largest lung thickness and for the DF setup simulated, human lungs have an estimated DF response of around 0.31 and murine lungs of 0.23. Dark field imaging can therefore be considered a promising modality for use in human lung imaging.

CHARMM force field for protonated polyethyleneimine.

We present a revised version of our previously published atomistic Chemistry at Harvard Macromolecular Mechanics (CHARMM) force field for polyethyleneimine (PEI). It is based on new residue types (with symmetric CNC backbone), whose integer charges and bonded parameters are derived from ab initio calculations on an enlarged set of model polymers. The force field is validated by extensive molecular dynamics simulations on solvated PEI chains of various lengths and protonation patterns. The profiles of the gyration radius, end-to-end distance, and diffusion coefficient fine-tune our previous results, while the simulated diffusion coefficients excellently reproduce experimental findings. The developed CHARMM force field is suitable for realistic atomistic simulations of size/protonation-dependent behavior of PEI chains, either individually or composing polyplexes, but also provides reliable all-atom distributions for deriving coarse-grained force fields for PEI. © 2018 Wiley Periodicals, Inc.

Stokes-Einstein relation of the liquid metal rubidium and its relationship to changes in the microscopic dynamics with increasing temperature.

For liquid rubidium the Stokes-Einstein (SE) relation is well fulfilled near the melting point with an effective hydrodynamic diameter, which agrees well with a value from structural investigations. A wealth of thermodynamic and microscopic data exists for a wide range of temperatures for liquid rubidium and hence it represents a good test bed to challenge the SE relation with rising temperature from an experimental point of view. We performed classical molecular dynamics simulations to complement the existing experimental data using a pseudopotential, which describes perfectly the structure and dynamics of liquid rubidium. The derived SE relation from combining experimental shear viscosity data with simulated diffusion coefficients reveals a weak violation at about 1.3T_{melting}≈400 K. The microscopic relaxation dynamics on nearest neighbor distances from neutron spectroscopy demonstrate distinct changes in the amplitude with rising temperature. The derived average relaxation time for density fluctuations on this length scale shows a non-Arrhenius behavior, with a slope change around 1.5T_{melting}≈450 K. Combining the simulated macroscopic self-diffusion coefficient with that microscopic average relaxation time, a distinct violation of the SE relation in the same temperature range can be demonstrated. One can conclude that the changes in the collective dynamics, a mirror of the correlated movements of the particles, are at the origin for the violation of the SE relation. The changes in the dynamics can be understood as a transition from a more viscous liquid metal to a more fluid-like liquid above the crossover temperature range of 1.3-1.5 T_{melting}. The decay of the amplitude of density fluctuations in liquid aluminium, lead, and rubidium demonstrates a remarkable agreement and points to a universal thermal crossover in the dynamics of liquid metals.

Time-dependent transport of energetic particles in magnetic turbulence: computer simulations versus analytical theory

We explore numerically the transport of energetic particles in a turbulent magnetic field configuration. A test-particle code is employed to compute running diffusion coefficients as well as particle distribution functions in the different directions of space. Our numerical findings are compared with models commonly used in diffusion theory such as Gaussian distribution functions and solutions of the cosmic ray Fokker–Planck equation. Furthermore, we compare the running diffusion coefficients across the mean magnetic field with solutions obtained from the time-dependent version of the unified non-linear transport theory. In most cases we find that particle distribution functions are indeed of Gaussian form as long as a two-component turbulence model is employed. For turbulence setups with reduced dimensionality, however, the Gaussian distribution can no longer be obtained. It is also shown that the unified non-linear transport theory agrees with simulated perpendicular diffusion coefficients as long as the pure two-dimensional model is excluded.

Calculation of Diffusion Coefficients through Coarse-Grained Simulations Using the Automated-Fragmentation-Parametrization Method and the Recovery of Wilke-Chang Statistical Correlation.

We introduce a model for the calculation of diffusion coefficients using dissipative particle dynamics coarse-grained molecular simulations. We validate the model on experimental diffusion data of small organics and drug-like molecules in water. The new model relies on our automated-fragmentation-parametrization protocol for cutting molecules into fragments, which are calibrated using the COSMO-RS thermodynamic model (J. Chem. Inf. Model.2016, 56 ( (12), ), 2361−2377, DOI: 10.1021/acs.jcim.6b0000327806564). By simulations over the entire CULGI database of more than 11000 molecules, we recover the decades-old empirical Wilke–Chang correlation between diffusion coefficient and molar volume. We believe this is the first demonstration of the correlation by simulation or theory. From a comparison of simulated and experimental diffusion coefficients, we find that one full time unit of coarse-grained simulation equals 64 ± 13 ps real time.

An improved model for prostate diffusion incorporating the results of Monte Carlo simulations of diffusion in the cellular compartment.

The purpose of this work was to refine a previously published model of prostate diffusion by incorporating improved estimates of cellular diffusivity obtained by Monte Carlo simulation. Stromal and epithelial cell size and intracellular volume fraction in different grades of cancer were determined from histological images. Diffusion in different mixtures of cells, corresponding to different tumor grades, was simulated and cellular apparent diffusion coefficient and kurtosis values determined. These values were incorporated into the previously published model of prostate diffusion and model predictions compared with values found in the literature. Stromal cell radius and intracellular volume fraction were 3.74±0.96μm and 13±3% respectively in normal peripheral zone (PZ), and were similar in all grades of cancer. Epithelial cell radius and intracellular volume fraction were 3.40±0.15μm and 45±5% respectively in normal PZ, rising to 4.75±0.20μm and 70±8% in high grade cancer. Cellular apparent diffusion coefficient and kurtosis were 1.02 μm2 ms-1 and 0.58 respectively in normal PZ, and 0.61 μm2 ms-1 and 1.15 in high grade cancer (variation in simulation values are less than 0.1%). Agreement between model predictions and measurements were good, with a mean square error of 0.22 μm2 ms-1 . Incorporation of cellular diffusion coefficient and kurtosis values obtained by Monte Carlo simulation into a model of prostate diffusion gives good agreement with published results.

Adsorption-Coupled Diffusion of Gold Nanoclusters within a Large-Pore Protein Crystal Scaffold.

Large-pore protein crystals (LPCs) are ordered biologically derived nanoporous materials exhibiting pore diameters greater than 8 nm. These substantial pores distinguish LPCs from typical nanoporous scaffolds, enabling engineered LPC materials to readily uptake, immobilize, and release macromolecular guests. In this study, macromolecular transport within an LPC environment was experimentally and computationally investigated by studying adsorption-coupled diffusion of Au25(glutathione)18 nanoclusters within a cross-linked LPC scaffold via time-lapse confocal microscopy, bulk equilibrium adsorption, and hindered diffusion simulation. Equilibrium adsorption data is congruent with a Langmuir adsorption model, exhibiting strong binding behavior between nanoclusters and the scaffold. The standard Gibbs free energy of binding is equivalent to -37.2 kJ/mol, and the maximum binding capacity of 1.25 × 103 mg/g corresponds to approximately 29 nanoclusters per LPC unit cell. The hindered diffusion model showed good agreement with experimental data, revealing a pore diffusion coefficient of 3.7 × 10-7 cm2/s under low nanocluster concentration. Furthermore, the model was sufficient to determine adsorption and desorption kinetic values for ka and kd equal to 13 cm3/mol·s and 1.7 × 10-7 s-1, respectively. At higher nanocluster concentrations, the simulated pore diffusion coefficient could be reduced by 3 orders of magnitude to 3.4 × 10-10 cm2/s due to the effects of pore occlusion. This study demonstrates a strategy to analyze adsorption-coupled diffusion data to better understand complex transport of fluorescent macromolecules into LPCs. This approach fits the observable fluorescence data to the key molecular details and will benefit downstream efforts to engineer LPC-based nanoporous materials.