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DOE OSTI2018

Prediction of shock initiation thresholds and ignition probability of polymer-bonded explosives using mesoscale simulations

The design of new materials requires establishment of macroscopic measures of material performance as functions of microstructure. Traditionally, this process has been an empirical endeavor. In this paper, an approach to computationally predict the probabilistic ignition thresholds of polymer-bonded explosives (PBXs) using mesoscale simulations is developed. The simulations explicitly account for microstructure, constituent properties, and interfacial responses and capture processes responsible for the development of hotspots and damage. The specific mechanisms tracked include viscoelasticity, viscoplasticity, fracture, post-fracture contact, frictional heating, and heat conduction. The probabilistic analysis uses sets of statistically similar microstructure samples to directly mimic relevant experiments for quantification of statistical variations of material behavior due to inherent material heterogeneities. The particular thresholds and ignition probabilities predicted are expressed in James type and Walker–Wasley type relations, leading to the establishment of explicit analytical expressions for the ignition probability as function of loading. Specifically, the ignition thresholds corresponding to any given level of ignition probability and ignition probability maps are predicted for PBX 9404 for the loading regime of U p = 200–1200 m/s where U p is the particle speed. The predicted results are in good agreement with available experimental measurements. A parametric study also shows that binder properties can significantly affect the macroscopic ignition behavior of PBXs. Finally, the capability to computationally predict the macroscopic engineering material response relations out of material microstructures and basic constituent and interfacial properties lends itself to the design of new materials as well as the analysis of existing materials.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Mapping the body’s battle with Ebola and Zika

The viruses that cause Ebola and Zika, daunting diseases that inspire concern at every outbreak, share a strong similarity in how they first infiltrate a host’s cells. Through the computer modeling capabilities of Los Alamos National Laboratory, the molecular calisthenics involved in invading a cell are visually documented, an essential step toward vaccine and therapeutic medicine development. “The two very different viruses both use a surface protein to initiate a process called ‘membrane fusion,’ which allows the viral entry into the host cell,” said Chang-Shung Tung, the leading and corresponding author of the recent work in the journal Biomolecules. “Before the membrane fusion started, these two proteins went through large conformational changes that was not fully understood, as the proteins would take on the physical shape that would allow them to fuse with the cell and begin the infection. In this work, we modeled the structures of the two proteins in the fusion-initiation state. Then we used the structures to explain how four different antibodies in our bodies can fight the infection and block the viral entry, based on how they bind to these two proteins,” Tung said. The aim of the team’s work was to understand the specific structure-function relationship of the Ebola glycoprotein (EBOV GP) and Zika envelope (ZIKA E) proteins, the ones that are instrumental in the fusion with the host cell. “This computer modeling approach allowed us to generate atomic-level models of EBOV GP and ZIKV E proteins in the fusion state for the first time,” said Anna Lappala, a postdoctoral fellow at the Center for Nonlinear Studies and the Theoretical Biology & Biophysics Group at Los Alamos. “These models, together with the knowledge of the envelope proteins in the pre-fusion state, allowed us to study the function of neutralizing antibodies as they bind to the viral envelope proteins.” Read the published scientific paper here: http://www.mdpi.com/2218-273X/8/2/25/pdf

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

Status of Mars Retropropulsion Testing in the Langley Unitary Plan Wind Tunnel

Future Mars human landings will be enabled by a powered descent phase starting at supersonic conditions, something which has never been done before on a Mars mission. Significant aerosciences challenges exist due to jet interactions between the retrorocket engine plumes, freestream flow, and vehicle that will affect the aerodynamic behavior during powered descent. Historically, wind tunnel tests have been used to study the interactions with inert gas exhaust simulants in place of rocket engines. On the computational side, flowfield simulations have been completed at full-scale conditions, but the available ground and flight data are not appropriate for calibrating computational uncertainties for aerodynamic interference on proposed Mars descent vehicles, due to insufficient data, dissimilar vehicle geometries, and disparate operating conditions. A wind tunnel test has been designed to begin addressing powered descent aerodynamics risks for large-scale human Mars entry concepts and to identify gaps in computational predictive capabilities. The test will be conducted in the NASA Langley Unitary Plan Wind Tunnel and is designed with improvements in model design and data products over past tests. The test campaign will be run using sub-scale model geometries derived from NASA powered descent reference vehicles: a blunt low lift-to-drag vehicle and a more slender geometry that generates higher unpowered lift. Both models have been fabricated and are ready for testing. The blunt model is equipped with the flexibility to examine the effects of nozzle pointing direction, number, location, size, and area ratio. The main measurements are heatshield aerodynamic interference forces and moments with a custom flow-through balance, discrete and distributed heatshield pressure, and high-speed flowfield visualization. This paper covers the test objectives, facility, models and instrumentation, and planned test matrix.

Supersonic Retropropulsion↗

NASA NTRS2001

Development of an Innovative Algorithm for Aerodynamics-Structure Interaction Using Lattice Boltzmann Method

The lattice Boltzmann equation (LBE) is a kinetic formulation which offers an alternative computational method capable of solving fluid dynamics for various systems. Major advantages of the method are owing to the fact that the solution for the particle distribution functions is explicit, easy to implement, and the algorithm is natural to parallelize. In this final report, we summarize the works accomplished in the past three years. Since most works have been published, the technical details can be found in the literature. Brief summary will be provided in this report. In this project, a second-order accurate treatment of boundary condition in the LBE method is developed for a curved boundary and tested successfully in various 2-D and 3-D configurations. To evaluate the aerodynamic force on a body in the context of LBE method, several force evaluation schemes have been investigated. A simple momentum exchange method is shown to give reliable and accurate values for the force on a body in both 2-D and 3-D cases. Various 3-D LBE models have been assessed in terms of efficiency, accuracy, and robustness. In general, accurate 3-D results can be obtained using LBE methods. The 3-D 19-bit model is found to be the best one among the 15-bit, 19-bit, and 27-bit LBE models. To achieve desired grid resolution and to accommodate the far field boundary conditions in aerodynamics computations, a multi-block LBE method is developed by dividing the flow field into various blocks each having constant lattice spacing. Substantial contribution to the LBE method is also made through the development of a new, generalized lattice Boltzmann equation constructed in the moment space in order to improve the computational stability, detailed theoretical analysis on the stability, dispersion, and dissipation characteristics of the LBE method, and computational studies of high Reynolds number flows with singular gradients. Finally, a finite difference-based lattice Boltzmann method is developed for inviscid compressible flows.

Mei, Ren-Wei↗

DOE OSTI2018

Determining the Concentration of Free Electrons in n-InSb from Far-Infrared Reflectance Spectra with Allowance for Plasmon–Phonon Coupling

Contactless nondestructive testing is a means for determining the concentration of free electrons N in indium antimonide (InSb) samples from far-infrared reflectance spectra recorded at room temperature. A computer program capable of determining the characteristic wave number from the Kramers–Kronig relation is developed. The calculated calibration dependence makes it possible to determine the electron concentration from the known characteristic wave number. It is shown that this dependence is described by a cubic polynomial. In the calculations, the energy dependence of the electron effective mass is taken into account. It is established that, in determining the electron concentration, account must be taken of plasmon–phonon coupling, specifically at N ≤ 5 × 10{sup 17} cm{sup –3}. The systematic error introduced into the determination of N by disregard of plasmon–phonon coupling is estimated. The software elaborated here makes it possible to calculate the electron concentration N from experimental reflectance spectra and to store and process the results. The software is tested by the example of the reflectance spectrum of heavily doped n-InSb.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Enabling Interoperable SCADA Communications for PV Inverters through Embedded Controllers

The percentage integration of photovoltaic (PV) inverters in the field has increased significantly in the past 5 years. Regardless of the size of the PV plants and the inverters (residential vs. commercial), it is becoming crucial that these devices have the capability to communicate with peers (other smart devices) and with components that are at a hierarchy above the inverters (e.g., supervisory control and data acquisition (SCADA) systems, distributed controllers, and data managers). This project aims to develop a standard SCADA software code for inverters’ embedded controllers that will enable interoperability with other components in the system. To achieve this, the code will be developed using two different protocols: Distributed Network Protocol 3 and International Electrotechnical Commission 61850. The developed code is aimed to be deployed in simple embedded controllers. It will be tested in the National Renewable Energy Laboratory’s (NREL’s) Energy Systems Integration Facility. The tested code will then be made available through Triangle MicroWorks’s (TMW’s) software platform. The primary objectives of this project include training the NREL team with TMW’s embedded controller libraries, developing an interoperable communication code for embedded controllers, successfully testing and deploying the code, and demonstrating the newly developed code in a conference.

14 SOLAR ENERGY↗

NASA NTRS2007

An IEEE 1451.1 Architecture for ISHM Applications

The IEEE 1451.1 Standard for a Smart Transducer Interface defines a common network information model for connecting and managing smart elements in control and data acquisition networks using network-capable application processors (NCAPs). The Standard is a network-neutral design model that is easily ported across operating systems and physical networks for implementing complex acquisition and control applications by simply plugging in the appropriate network level drivers. To simplify configuration and tracking of transducer and actuator details, the family of 1451 standards defines a Transducer Electronic Data Sheet (TEDS) that is associated with each physical element. The TEDS contains all of the pertinent information about the physical operations of a transducer (such as operating regions, calibration tables, and manufacturer information), which the NCAP uses to configure the system to support a specific transducer. The Integrated Systems Health Management (ISHM) group at NASA's John C. Stennis Space Center (SSC) has been developing an ISHM architecture that utilizes IEEE 1451.1 as the primary configuration and data acquisition mechanism for managing and collecting information from a network of distributed intelligent sensing elements. This work has involved collaboration with other NASA centers, universities and aerospace industries to develop IEEE 1451.1 compliant sensors and interfaces tailored to support health assessment of complex systems. This paper and presentation describe the development and implementation of an interface for the configuration, management and communication of data, information and knowledge generated by a distributed system of IEEE 1451.1 intelligent elements monitoring a rocket engine test system. In this context, an intelligent element is defined as one incorporating support for the IEEE 1451.x standards and additional ISHM functions. Our implementation supports real-time collection of both measurement data (raw ADC counts and converted engineering units) and health statistics produced by each intelligent element. The handling of configuration, calibration and health information is automated by using the TEDS in combination with other electronic data sheets extensions to convey health parameters. By integrating the IEEE 1451.1 Standard for a Smart Transducer Interface with ISHM technologies, each element within a complex system becomes a highly flexible computation engine capable of self-validation and performing other measures of the quality of information it is producing.

Morris, Jon A.↗

DOE OSTI2023

Feasibility of a Novel Density Functional Method Outside the Kohn-Sham Framework for Modeling Global Potential Energy Surfaces of Molecular Chemical Reactions (Final Technical Report)

The project aimed towards the construction of computational methods capable of modeling the global potential energy surface (PES) of small molecules, molecular ions, and radicals — including the parts of the PES which correspond to chemical reactions, and the reaction paths connecting reactants, intermediates, and reaction products. This goal may seem humble at first glance, but for chemical systems with more than about six atoms in total, at the time the project was proposed, there were no established theoretical methods capable of simulating such systems reliably, not even for small molecules in the gas phase which are electronically benign. This restriction severely hampers our ability to model and control chemical processes under harsh conditions. With the goal of constructing a method capable of modeling such chemical systems, we proposed to pursue a novel approach towards a Multi-Configuration (MC) DFT outside the traditional frameworks of Kohn-Sham theory and other methods of coupling wave function theory with DFT. Rather than being a complete active space (CAS) method, the proposed DOCI-DFT would employ a special restricted form of the active space wave function, called Doubly-Occupied CI (DOCI)—this wave function form is sufficient to describe not only heterolytic, but also homolytic bond dissociation processes at the zeroth order (i.e., as active space wave function). There are no other standard mean field methods which can do so. In the original proposal, we also outlined strong formal and practical arguments speaking for this method. The project proposal was accepted by the Department of Energy and provided two years of seed funding for one graduate student, as well as two years of two weeks PI summer-salary for the PI. However, ultimately the project could not be effectively pursued due to severe interferences outside the context scientific problems and was cancelled. Apart from two weeks of PI salary (and associated fringe & overhead costs issues by the performing institution), no costs were charged against the award, with the entire rest of funding returned to the Department of Energy. This report reiterates the primary background information regarding the project, its original goals, and outlines the preliminary work performed during the two weeks of DOE funding charged.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

A hybrid finite element-spectral boundary integral approach: Applications to dynamic rupture modeling in unbounded domains

The finite element method (FEM) and the spectral boundary integral method (SBI) have both been widely used in the study of dynamic rupture simulations along a weak interface. Here, we present a hybrid method that combines FEM and SBI through the consistent exchange of displacement and traction boundary conditions, thereby benefiting from the flexibility of FEM in handling problems with nonlinearities or small-scale heterogeneities and from the superior performance and accuracy of SBI. We validate the hybrid method using a benchmark problem from the Southern California Earthquake Center's dynamic rupture simulation validation exercises.We further demonstrate the capability and computational efficiency of the hybrid scheme for resolving off-fault heterogeneities by studying a 2D in-plane shear crack in two different settings: one where the crack is embedded in a high-velocity zone and another where it is embedded in a low-velocity zone. Finally, we discuss the potential of the hybrid method for addressing a wide range of problems in geophysics and engineering.

58 GEOSCIENCES↗

DOE OSTI2023

Development of a wind turbine model and simulation platform using an acausal approach: Multiphysics modeling, validation, and control

This article presents the development of the Control-oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS). CRAFTS has a modular, hierarchical model architecture that enables rapid and accurate simulation of wind turbines. The architecture facilitates the incorporation of model variants, and its system reconfiguration features help simulate multiple design variants. CRAFTS also supports the integration of models developed on a causality-free platform (e.g., Modelica®) with existing causal models. This article focuses on the validation of a land-based wind turbine models against OpenFAST, an industry-standard platform, for several test cases. Closed-loop scenarios are also tested using the standard ROSCO controller and compared against OpenFAST. In addition, a nonlinear controller developed in our prior work is also evaluated. The test cases demonstrate the user-friendly and computationally efficient capabilities of CRAFTS to facilitate control co-design, assist in incorporating multiphysics models, be adaptable to design variants, and allow for rapid simulations to validate models and evaluate controllers.

17 WIND ENERGY↗

DOE OSTI2025

Mathematical Foundation for Quantum Computing of Electromagnetic Wave Propagation in Dielectric Media

Can quantum computers effectively simulate the propagation and scattering of electromagnetic waves in a classical plasma? This chapter introduces some of the basic concepts in mathematics and physics essential to answering that question. The numerical simulations of Maxwell equations for wave propagation in dielectrics are constrained by technological limitations of the present-day computers. In contrast, there has been ample fanfare around quantum computers and their potential to far exceed the performance of traditional computers. Whether the enhanced capabilities of a quantum computer can be put to use for simulating topics in classical physics is a source of intrigue and curiosity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

A level-of-details framework for representing occupant behavior in agent-based models

We report agent-based modeling is an advanced computational technique capable of representing complex and dynamic processes of human behavior in building performance simulation. Though the agent-based approach supports diverse applications concerning human behavior modeling within the built environment, there is no consensus on the optimal amount of information or level of granularity needed for occupant information representation. This paper attempts to formalize the level of details (LoD) needed for occupant behavior representation in agent-based environments. A novel framework, grounded on the concept of LoD, is proposed to select the required details in representing occupants in agent-based models. Ten attributes related to occupants' presence, movement, behavioral processes, and repertoire are considered to define the LoD. The framework identifies use case parameters as the guiding principle and allows a hybrid approach for selecting varying degrees of occupant attributes to serve the purpose of simulation. A discussion on the pertinence of different occupant behavior LoDs in relation to the desired objective and simulation context is also presented. The study intends to support the occupant behavior research by advancing agent-based occupant modeling in building performance simulation.

42 ENGINEERING↗

DOE OSTI2023

A study of adhesive bonding in metal–metal, metal–CFRP, and CFRP–CFRP material combinations under shear deformation: Fracture morphologies and damage mechanisms

Safe design of adhesive joining in multi-materials in engineered structures requires the accumulation of numerous experimental data on the failure behavior of various adhesively-bonded material combinations under different loading conditions. The deep understanding of mechanical performance, fracturing morphologies, and main damage mechanisms is also quintessential for accelerating the development of proper physics-based and multi-scale models for assisting the design. Towards this goal, this work presents a comprehensive characterization of the failure behavior of adhesively-bonded metal–metal, metal–CFRP, and CFRP–CFRP material combinations under global shear deformation via single lap shear testing. Thanks to a synergistic combination of measurement methods by using Digital Imaging Correlation (DIC) and 3D optical profilometry, adhesive features on the adherend after failure were quantified and the main progressive damage mechanisms were identified. The characterization performed in this work provides quantitative data that contributes to a better understanding of shear failure in adhesive bonding across different bi-material combinations. Finally, the obtained results have practical implications, including the potential to enhance adhesive bonding design, identify failure causes in adhesive joints, and develop or validate computational models capable of capturing the observed behavior in various adhesively-bonded materials under global shear deformation.

36 MATERIALS SCIENCE↗

DOE OSTI2019

System thermal-hydraulic modelling of the phénix dissymmetric test benchmark

Phénix is a French pool-type sodium-cooled prototype reactor; before the definitive shutdown, occurred in 2009, a final set of experimental tests are carried out in order to increase the knowledge on the operation and the safety aspect of the pool-type liquid metal-cooled reactors. One of the experiments was the Dissymmetric End-of-Life Test which was selected for the validation benchmark activity in the frame of SESAME project. The computer code validation plays a key role in the safety assessment of the innovative nuclear reactors and the Phénix dissymmetric test provides useful experimental data to verify the computer codes capability in the asymmetric thermal-hydraulic behaviour into a pool-type liquid metal-cooled reactor. This paper shows the comparison of the outcomes obtained with six different System Thermal-Hydraulic (STH) codes: RELAP5-3D©, SPECTRA, ATHLET, SAS4A/SASSYS-1, ASTEC-Na and CATHARE. The nodalization scheme of the reactor was individually achieved by the participants; during the development of the thermal-hydraulic model, the pool nodalization methodology had a special attention in order to investigate the capability of the STH codes to reproduce the dissymmetric effects which occur in each loop and into pools, caused by the azimuthal asymmetry of the boundary conditions. The modelling methodology of the participants is discussed and the main results are compared in this paper to obtain useful guide lines for the future modelling of innovative liquid metal pool-type reactors.

42 ENGINEERING↗

DOE OSTI2025

AutonomieAI: An efficient and deployable vehicle energy consumption estimation toolkit

Here, this paper presents AutonomieAI, a novel toolkit designed for efficient energy estimation of vehicles across diverse trip scenarios, routes, and drive cycles, applicable to a broad range of vehicle powertrain technologies. It leverages state-of-the-art Machine Learning techniques to deliver real-time energy prediction of vehicles, enabling co-simulation with transportation level system tools and opening doors for large-scale optimization at city, network or national level. Benchmark results show that AutonomieAI achieves high accuracy, with an average percentage error below 2% for most powertrain types, and computational efficiency capable of processing over 10,000 trips per second. Applications of AutonomieAI have potential to offer the flexibility to assist in solving eco-routing problems, optimize for vehicle and powertrain selection, study charging decision behavior, and optimize for charging station placement. AutonomieAI is the result of large neural network based model architectures, trained on very large and unique high fidelity vehicle simulation data. It is lightweight, deployable, efficient and has accuracy comparable to specialized and complex physics based simulation softwares.

Autonomie↗

DOE OSTI2024

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Integrated Quantum-Classical Protocol for the Realistic Description of Solvated Multinuclear Mixed-Valence Transition-Metal Complexes and Their Solvatochromic Properties

Linear cyanide-bridged polymetallic complexes, which undergo photoinduced metal-to-metal charge transfer, represent prototypical systems for studying long-range electron-transfer reactions and understanding the role played by specific solute–solvent interactions in modulating the excited-state dynamics. Here, to tackle this problem, while achieving a statistically meaningful description of the solvent and of its relaxation, one needs a computational approach capable of handling large polynuclear transition-metal complexes, both in their ground and excited states, as well as the ability to follow their dynamics in several environments up to nanosecond time scales. Here, we present a mixed quantum classical approach, which combines large-scale molecular dynamics (MD) simulations based on an accurate quantum mechanically derived force field (QMD-FF) and self-consistent QMD polarized point charges, with IR and UV–vis spectral calculations to model the solvation dynamics and optical properties of a cyano-bridged trinuclear mixed-valence compound (trans-[(NC) 5 Fe III (μ-CN)Ru II (pyridine) 4 (μ-NC)Fe III (CN) 5 ] 4– ). We demonstrate the reliability of the QMD-FF/MD approach in sampling the solute conformational space and capturing the local solute–solvent interactions by comparing the results with higher-level quantum mechanics/molecular mechanics (QM/MM) MD reference data. The IR spectra calculated along the classical MD trajectories in different solvents correctly predict the red shift of the CN stretching band in the aprotic medium (acetonitrile) and the subtle differences measured in water and methanol, respectively. By explicitly including the solvent molecules around the cyanide ligands and calculating the thermal averaged absorption spectra using time-dependent density functional theory calculations within the Tamm–Dancoff approximation, the experimental solvatochromic shift is quantitatively reproduced going from water to methanol, while it is overestimated for acetonitrile. This discrepancy can likely be traced back to the lack of important dispersion interactions between the solvent cyano groups and the pyridine substituents in our micro solvation model. The proposed protocol is applied to the ground state in water, methanol, and acetonitrile and can be flexibly generalized to study excited-state nonequilibrium solvation dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Molecular Dynamics Simulations of the Adsorption of Phthalate Esters on Smectite Clay Surfaces

The partitioning of organic contaminants between water and solid surfaces is a key process controlling their fate and transport in natural environments. A novel methodology was developed to predict the adsorption of organic contaminants by smectite clay minerals (high specific surface area adsorbents abundant in natural soils) using molecular dynamics (MD) simulations. The methodology models a stack of flexible Ca- montmorillonite lamellae in direct contact with a bulk aqueous reservoir and uses the metadynamics technique to facilitate the exploration of the free energy landscape. The methodology was tested and validated in the case of six phthalate esters, widely used chemical plasticizers with endocrine disrupting properties. Simulation predictions reveal strong phthalate adsorption, especially for the larger and more hydrophobic phthalates. Predicted partition coefficients (K d values) are consistent with collected batch experimental data. Adsorption was observed on both the exterior basal surfaces and within the interlayer nanopore, with phthalate molecules predominately adopting a flat orientation on the clay surface. Intercalation was also detected in complementary X-ray diffraction (XRD) experiments. A strong inverse relationship between extent of adsorption and clay surface charge density was observed, as phthalate molecules preferentially occupied the more hydrophobic uncharged patches on each surface. Detailed analysis of the free energy of adsorption revealed that phthalate affinity for the clay surface results from a small favorable van der Waals contribution and a large favorable entropic contribution. Overall, this research demonstrates the substantial affinity of smectite clays for phthalate esters and establishes a computational methodology capable of predicting the water-clay partition coefficients of organic contaminants, a key parameter in environmental fate and transport models.

36 MATERIALS SCIENCE↗