Eric Darve

All Publications

• Hybrid physics-based and data-driven modeling of vascular bifurcation pressure differences. Computers in biology and medicine Rubio, N. L., Pegolotti, L., Pfaller, M. R., Darve, E. F., Marsden, A. L. 2024; 184: 109420

  Abstract

  Reduced-order models allow for the simulation of blood flow in patient-specific vasculatures. They offer a significant reduction in computational cost and wait time compared to traditional computational fluid dynamics models. Unfortunately, due to the simplifications made in their formulations, reduced-order models can suffer from significantly reduced accuracy. One common simplifying assumption is that of continuity of static or total pressure over vascular bifurcations. In many cases, this assumption has been shown to introduce significant errors in pressure predictions. We propose a model to account for this pressure difference, with the ultimate goal of increasing the accuracy of cardiovascular reduced-order models. Our model successfully uses a structure common in existing reduced-order models in conjunction with machine-learning techniques to predict the pressure difference over a vascular bifurcation. We analyze the performance of our model on steady and transient flows, testing it on three bifurcation cohorts representing three different bifurcation geometric types. We find that our model makes significantly more accurate predictions than other models for approximating bifurcation pressure losses commonly used in the reduced-order cardiovascular modeling community. We also compare the efficacy of different machine-learning techniques and observe that a neural network performs most robustly. Additionally, we consider two different model modalities: one in which the model is fit using both steady and transient flows, and one in which it is optimized for performance in transient flows. We discuss the trade-off between the physical interpretability associated with the first option and the improved accuracy in transient flows associated with the latter option. We also demonstrate the model's ability to generalize by testing it on a combined dataset containing two different bifurcation types. This work marks a step towards improving the accuracy of cardiovascular reduced-order models, thereby increasing their utility for cardiovascular flow modeling.

  View details for DOI 10.1016/j.compbiomed.2024.109420

  View details for PubMedID 39608038

• Coincident learning for unsupervised anomaly detection of scientific instruments MACHINE LEARNING-SCIENCE AND TECHNOLOGY Humble, R., Zhang, Z., OShea, F., Darve, E., Ratner, D. 2024; 5 (3)

  View details for DOI 10.1088/2632-2153/ad64a6

  View details for Web of Science ID 001283699200001

• A NUMERICALLY STABLE COMMUNICATION-AVOIDING s- STEP GMRES ALGORITHM SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS Xu, Z., Alonso, J., Darve, E. 2024; 45 (4): 2039-2074

  View details for DOI 10.1137/23M1577109

  View details for Web of Science ID 001343416000013

• Resilient VAE: Unsupervised Anomaly Detection at the SLAC Linac Coherent Light Source Humble, R., Colocho, W., O'Shea, F., Ratner, D., Darve, E., Espinal, DeVita, R., Laycock, P., Shadura, O. E D P SCIENCES. 2024

  View details for DOI 10.1051/epjconf/202429509033

  View details for Web of Science ID 001244151902084

• Learning reduced-order models for cardiovascular simulations with graph neural networks. Computers in biology and medicine Pegolotti, L., Pfaller, M. R., Rubio, N. L., Ding, K., Brugarolas Brufau, R., Darve, E., Marsden, A. L. 2023; 168: 107676

  Abstract

  Reduced-order models based on physics are a popular choice in cardiovascular modeling due to their efficiency, but they may experience loss in accuracy when working with anatomies that contain numerous junctions or pathological conditions. We develop one-dimensional reduced-order models that simulate blood flow dynamics using a graph neural network trained on three-dimensional hemodynamic simulation data. Given the initial condition of the system, the network iteratively predicts the pressure and flow rate at the vessel centerline nodes. Our numerical results demonstrate the accuracy and generalizability of our method in physiological geometries comprising a variety of anatomies and boundary conditions. Our findings demonstrate that our approach can achieve errors below 3% for pressure and flow rate, provided there is adequate training data. As a result, our method exhibits superior performance compared to physics-based one-dimensional models while maintaining high efficiency at inference time.

  View details for DOI 10.1016/j.compbiomed.2023.107676

  View details for PubMedID 38039892

• Temperature field optimization for laser powder bed fusion as a traveling salesperson problem with history INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING Wang, G., Darve, E., Lew, A. J. 2023

  View details for DOI 10.1002/nme.7360

  View details for Web of Science ID 001084235100001

• Probabilistic partition of unity networks for high-dimensional regression problems INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING Fan, T., Trask, N., D'Elia, M., Darve, E. 2023

  View details for DOI 10.1002/nme.7207

  View details for Web of Science ID 000940516600001

• Beam-based rf station fault identification at the SLAC Linac Coherent Light Source PHYSICAL REVIEW ACCELERATORS AND BEAMS Humble, R., O'Shea, F. H., Colocho, W., Gibbs, M., Chaffee, H., Darve, E., Ratner, D. 2022; 25 (12)

  View details for DOI 10.1103/PhysRevAccelBeams.25.122804

  View details for Web of Science ID 000901771100001

• Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry ADVANCES IN WATER RESOURCES Forghani, M., Qian, Y., Lee, J., Farthing, M., Hesser, T., Kitanidis, P. K., Darve, E. F. 2022; 170

  View details for DOI 10.1016/j.advwatres.2022.104323

  View details for Web of Science ID 000883792800002

• HyKKT: a hybrid direct-iterative method for solving KKT linear systems OPTIMIZATION METHODS & SOFTWARE Regev, S., Chiang, N., Darve, E., Petra, C. G., Saunders, M. A., Swirydowicz, K., Peles, S. 2022

  View details for DOI 10.1080/10556788.2022.2124990

  View details for Web of Science ID 000860640100001

• Second-order accurate hierarchical approximate factorizations for solving sparse linear systems INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING Klockiewicz, B., Cambier, L., Humble, R., Tchelepi, H., Darve, E. 2022

  View details for DOI 10.1002/nme.7076

  View details for Web of Science ID 000839974000001

• Linear solvers for power grid optimization problems: A review of GPU-accelerated linear solvers PARALLEL COMPUTING Swirydowicz, K., Darve, E., Jones, W., Maack, J., Regev, S., Saunders, M. A., Thomas, S. J., Peles, S. 2022; 111

  View details for DOI 10.1016/j.parco.2021.102870

  View details for Web of Science ID 000800000400004

• Learning generative neural networks with physics knowledge RESEARCH IN THE MATHEMATICAL SCIENCES Xu, K., Zhu, W., Darve, E. 2022; 9 (2)

  View details for DOI 10.1007/s40687-022-00329-z

  View details for Web of Science ID 000796986600001

• Hierarchical Orthogonal Factorization: Sparse Least Squares Problems JOURNAL OF SCIENTIFIC COMPUTING Gnanasekaran, A., Darve, E. 2022; 91 (2)

  View details for DOI 10.1007/s10915-022-01824-9

  View details for Web of Science ID 000777186700002

• Physics constrained learning for data-driven inverse modeling from sparse observations JOURNAL OF COMPUTATIONAL PHYSICS Xu, K., Darve, E. 2022; 453

  View details for DOI 10.1016/j.jcp.2021.110938

  View details for Web of Science ID 000762371600002

• On the fractional Laplacian of variable order FRACTIONAL CALCULUS AND APPLIED ANALYSIS Darve, E., D'Elia, M., Garrappa, R., Giusti, A., Rubio, N. L. 2022; 25 (1): 15-28

  View details for DOI 10.1007/s13540-021-00003-1

  View details for Web of Science ID 000810139800002

• Integrating deep neural networks with full-waveform inversion: Reparameterization, regularization, and uncertainty quantification GEOPHYSICS Zhu, W., Xu, K., Darve, E., Biondi, B., Beroza, G. C. 2022; 87 (1): R93-R109

  View details for DOI 10.1190/GEO2020-0933.1

  View details for Web of Science ID 000744653000004

• Soft Masking for Cost-Constrained Channel Pruning Humble, R., Shen, M., Latorre, J., Darve, E., Alvarez, J., Avidan, S., Brostow, G., Cisse, M., Farinella, G. M., Hassner, T. SPRINGER INTERNATIONAL PUBLISHING AG. 2022: 641-657

  View details for DOI 10.1007/978-3-031-20083-0_38

  View details for Web of Science ID 000897106000038

• HIERARCHICAL ORTHOGONAL FACTORIZATION: SPARSE SQUARE MATRICES SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS Gnanasekaran, A., Darve, E. 2022; 43 (1): 94-123

  View details for DOI 10.1137/20M1373475

  View details for Web of Science ID 000759673100004

• Memory-Augmented Generative Adversarial Networks for Anomaly Detection IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS Yang, Z., Zhang, T., Bozchalooi, I., Darve, E. 2021

  Abstract

  We propose a memory-augmented deep learning model for semisupervised anomaly detection (AD). While many traditional AD methods focus on modeling the distribution of normal data, additional constraints in the modeling process are needed to distinguish between normal and abnormal data. The proposed model, named memory augmented generative adversarial networks (MEMGAN), is coupled with external memory units through attentional operations. One property of MEMGAN in the latent space is such that encoded normal data are expected to reside in the convex hull of the memory units, while the abnormal ones are separated outside. This property makes the AD process of MEMGAN more robust and reliable. Experiments on AD datasets adapted from MVTec, MNIST, CIFAR10, and Arrhythmia demonstrate that MEMGAN notably improves over previous AD models. We also find that the decoded memory units in MEMGAN are more diverse and interpretable than those in previous memory-augmented models.

  View details for DOI 10.1109/TNNLS.2021.3132928

  View details for Web of Science ID 000740066200001

  View details for PubMedID 34962884

• Learning viscoelasticity models from indirect data using deep neural networks COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING Xu, K., Tartakovsky, A. M., Burghardt, J., Darve, E. 2021; 387

  View details for DOI 10.1016/j.cma.2021.114124

  View details for Web of Science ID 000702650900001

• Solving inverse problems in stochastic models using deep neural networks and adversarial training COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING Xu, K., Darve, E. 2021; 384

  View details for DOI 10.1016/j.cma.2021.113976

  View details for Web of Science ID 000681089400005

• PBBFMM3D: A parallel black-box algorithm for kernel matrix-vector multiplication JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING Wang, R., Chen, C., Lee, J., Darve, E. 2021; 154: 64-73

  View details for DOI 10.1016/j.jpdc.2021.04.005

  View details for Web of Science ID 000657606800006

• A general approach to seismic inversion with automatic differentiation COMPUTERS & GEOSCIENCES Zhu, W., Xu, K., Darve, E., Beroza, G. C. 2021; 151

  View details for DOI 10.1016/j.cageo.2021.104751

  View details for Web of Science ID 000641463400002

• Learning constitutive relations using symmetric positive definite neural networks JOURNAL OF COMPUTATIONAL PHYSICS Xu, K., Huang, D. Z., Darve, E. 2021; 428

  View details for DOI 10.1016/j.jcp.2020.110072

  View details for Web of Science ID 000612234200001

• Application of deep learning to large scale riverine flow velocity estimation STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT Forghani, M., Qian, Y., Lee, J., Farthing, M. W., Hesser, T., Kitanidis, P. K., Darve, E. F. 2021

  View details for DOI 10.1007/s00477-021-01988-0

  View details for Web of Science ID 000620880500002

• Deep learning technique for fast inference of large-scale riverine bathymetry ADVANCES IN WATER RESOURCES Ghorbanidehno, H., Lee, J., Farthing, M., Hesser, T., Darve, E. F., Kitanidis, P. K. 2021; 147

  View details for DOI 10.1016/j.advwatres.2020.103715

  View details for Web of Science ID 000606420300005

• Universal Sentence Representation Learning with Conditional Masked Language Model Yang, Z., Yang, Y., Cer, D., Law, J., Darve, E., Assoc Computat Linguist ASSOC COMPUTATIONAL LINGUISTICS-ACL. 2021: 6216-6228

  View details for Web of Science ID 000860727000017

• A Task-Based Distributed Parallel Sparsified Nested Dissection Algorithm Cambier, L., Darve, E., ACM ASSOC COMPUTING MACHINERY. 2021

  View details for DOI 10.1145/3468267.3470619

  View details for Web of Science ID 000769991000015

• A Simple and Effective Method To Eliminate the Self Language Bias in Multilingual Representations Yang, Z., Yang, Y., Cer, D., Darve, E., Assoc Computat Linguist ASSOC COMPUTATIONAL LINGUISTICS-ACL. 2021: 5825-5832

  View details for Web of Science ID 000855966305074

• Recent developments in fast and scalable inverse modeling and data assimilation methods in hydrology JOURNAL OF HYDROLOGY Ghorbanidehno, H., Kokkinaki, A., Lee, J., Darve, E. 2020; 591

  View details for DOI 10.1016/j.jhydrol.2020.125266

  View details for Web of Science ID 000599757800006

• Learning constitutive relations from indirect observations using deep neural networks JOURNAL OF COMPUTATIONAL PHYSICS Huang, D. Z., Xu, K., Farhat, C., Darve, E. 2020; 416

  View details for DOI 10.1016/j.jcp.2020.109491

  View details for Web of Science ID 000539999800003

• Coupled Time-Lapse Full-Waveform Inversion for Subsurface Flow Problems Using Intrusive Automatic Differentiation WATER RESOURCES RESEARCH Li, D., Xu, K., Harris, J. M., Darve, E. 2020; 56 (8)

  View details for DOI 10.1029/2019WR027032

  View details for Web of Science ID 000582701700031

• Isogeometric collocation method for the fractional Laplacian in the 2D bounded domain COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING Xu, K., Darve, E. 2020; 364

  View details for DOI 10.1016/j.cma.2020.112936

  View details for Web of Science ID 000527574600027

• Parallelization of the inverse fast multipole method with an application to boundary element method COMPUTER PHYSICS COMMUNICATIONS Takahashi, T., Chen, C., Darve, E. 2020; 247

  View details for DOI 10.1016/j.cpc.2019.106975

  View details for Web of Science ID 000503093400011

• AN ALGEBRAIC SPARSIFIED NESTED DISSECTION ALGORITHM USING LOW-RANK APPROXIMATIONS SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS Cambier, L., Chen, C., Boman, E. G., Rajamanickam, S., Tuminaro, R. S., Darve, E. 2020; 41 (2): 715–46

  View details for DOI 10.1137/19M123806X

  View details for Web of Science ID 000546981500015

• Regularized Cycle Consistent Generative Adversarial Network for Anomaly Detection Yang, Z., Bozchalooi, I., Darve, E., DeGiacomo, G., Catala, A., Dilkina, B., Milano, M., Barro, S., Bugarin, A., Lang, J. IOS PRESS. 2020: 1618-1625

  View details for DOI 10.3233/FAIA200272

  View details for Web of Science ID 000650971301110

• TaskTorrent: a Lightweight Distributed Task-Based Runtime System in C plus Cambier, L., Qian, Y., Darve, E., IEEE Comp Soc IEEE COMPUTER SOC. 2020: 16-26

  View details for DOI 10.1109/PAWATM51920.2020.00007

  View details for Web of Science ID 000674937700002

• SPARSE HIERARCHICAL PRECONDITIONERS USING PIECEWISE SMOOTH APPROXIMATIONS OF EIGENVECTORS SIAM JOURNAL ON SCIENTIFIC COMPUTING Klockiewicz, B., Darve, E. 2020; 42 (6): A3907–A3931

  View details for DOI 10.1137/20M1315683

  View details for Web of Science ID 000600650400022

• A robust hierarchical solver for ill-conditioned systems with applications to ice sheet modeling JOURNAL OF COMPUTATIONAL PHYSICS Chen, C., Cambier, L., Boman, E. G., Rajamanickam, S., Tuminaro, R. S., Darve, E. 2019; 396: 819–36

  View details for DOI 10.1016/j.jcp.2019.07.024

  View details for Web of Science ID 000481732600041

• Sparse hierarchical solvers with guaranteed convergence INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING Yang, K., Pouransari, H., Darve, E. 2019

  View details for DOI 10.1002/nme.6166

  View details for Web of Science ID 000479563600001

• Erratum: "Investigating the role of non-covalent interactions in conformation and assembly of triazine-based sequence-defined polymers" [J. Chem. Phys. 149, 072330 (2018)]. The Journal of chemical physics Ahn, S., Grate, J. W., Darve, E. F. 2019; 150 (17): 179901

  View details for PubMedID 31067890

• Investigating the role of non-covalent interactions in conformation and assembly of triazine-based sequence-defined polymers (vol 149, 072330, 2018) JOURNAL OF CHEMICAL PHYSICS Ahn, S., Grate, J. W., Darve, E. F. 2019; 150 (17)

  View details for DOI 10.1063/1.5099377

  View details for Web of Science ID 000467255500054

• The multi-dimensional generalized Langevin equation for conformational motion of proteins JOURNAL OF CHEMICAL PHYSICS Lee, H., Ahn, S., Darve, E. F. 2019; 150 (17)

  View details for DOI 10.1063/1.5055573

  View details for Web of Science ID 000467255500013

• Novel Data Assimilation Algorithm for Nearshore Bathymetry JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY Ghorbanidehno, H., Lee, J., Farthing, M., Hesser, T., Kitanidis, P. K., Darve, E. F. 2019; 36 (4): 699–715

  View details for DOI 10.1175/JTECH-D-18-0067.1

  View details for Web of Science ID 000465145300002

• The multi-dimensional generalized Langevin equation for conformational motion of proteins. The Journal of chemical physics Lee, H. S., Ahn, S. H., Darve, E. F. 2019; 150 (17): 174113

  Abstract

  Using the generalized Langevin equation (GLE) is a promising approach to build coarse-grained (CG) models of molecular systems since the GLE model often leads to more accurate thermodynamic and kinetic predictions than Brownian dynamics or Langevin models by including a more sophisticated friction with memory. The GLE approach has been used for CG coordinates such as the center of mass of a group of atoms with pairwise decomposition and for a single CG coordinate. We present a GLE approach when CG coordinates are multiple generalized coordinates, defined, in general, as nonlinear functions of microscopic atomic coordinates. The CG model for multiple generalized coordinates is described by the multidimensional GLE from the Mori-Zwanzig formalism, which includes an exact memory matrix. We first present a method to compute the memory matrix in a multidimensional GLE using trajectories of a full system. Then, in order to reduce the computational cost of computing the multidimensional friction with memory, we introduce a method that maps the GLE to an extended Markovian system. In addition, we study the effect of using a nonconstant mass matrix in the CG model. In particular, we include mass-dependent terms in the mean force. We used the proposed CG model to describe the conformational motion of a solvated alanine dipeptide system, with two dihedral angles as the CG coordinates. We showed that the CG model can accurately reproduce two important kinetic quantities: the velocity autocorrelation function and the distribution of first passage times.

  View details for PubMedID 31067888

• Embedding Imputation with Grounded Language Information Yang, Z., Zhu, C., Sachidananda, V., Darve, E., ACL, Korhonen, A., Traum, D., Marquez, L. ASSOC COMPUTATIONAL LINGUISTICS-ACL. 2019: 3356–61

  View details for Web of Science ID 000493046105039

• BLOCK BASIS FACTORIZATION FOR SCALABLE KERNEL EVALUATION SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS Wang, R., Li, Y., Mahoney, M. W., Darve, E. 2019; 40 (4): 1497–1526

  View details for DOI 10.1137/18M1212586

  View details for Web of Science ID 000546977600012

• FAST LOW-RANK KERNEL MATRIX FACTORIZATION USING SKELETONIZED INTERPOLATION SIAM JOURNAL ON SCIENTIFIC COMPUTING Cambier, L., Darve, E. 2019; 41 (3): A1652–A1680

  View details for DOI 10.1137/17M1133749

  View details for Web of Science ID 000473033300012

• Investigating the role of non-covalent interactions in conformation and assembly of triazine-based sequence-defined polymers. The Journal of chemical physics Ahn, S., Grate, J. W., Darve, E. F. 2018; 149 (7): 072330

  Abstract

  Grate and co-workers at Pacific Northwest National Laboratory recently developed high information content triazine-based sequence-defined polymers that are robust by not having hydrolyzable bonds and can encode structure and functionality by having various side chains. Through molecular dynamics (MD) simulations, the triazine polymers have been shown to form particular sequential stacks, have stable backbone-backbone interactions through hydrogen bonding and pi-pi interactions, and conserve their cis/trans conformations throughout the simulation. However, we do not know the effects of having different side chains and backbone structures on the entire conformation and whether the cis or trans conformation is more stable for the triazine polymers. For this reason, we investigate the role of non-covalent interactions for different side chains and backbone structures on the conformation and assembly of triazine polymers in MD simulations. Since there is a high energy barrier associated with the cis-trans isomerization, we use replica exchange molecular dynamics (REMD) to sample various conformations of triazine hexamers. To obtain rates and intermediate conformations, we use the recently developed concurrent adaptive sampling (CAS) algorithm for dimers of triazine trimers. We found that the hydrogen bonding ability of the backbone structure is critical for the triazine polymers to self-assemble into nanorod-like structures, rather than that of the side chains, which can help researchers design more robust materials.

  View details for PubMedID 30134719

• Sparse supernodal solver using block low-rank compression: Design, performance and analysis JOURNAL OF COMPUTATIONAL SCIENCE Pichon, G., Darve, E., Faverge, M., Ramet, P., Roman, J. 2018; 27: 255–70

  View details for DOI 10.1016/j.jocs.2018.06.007

  View details for Web of Science ID 000443665800022

• A distributed-memory hierarchical solver for general sparse linear systems Chen, C., Pouransari, H., Rajamanickam, S., Boman, E. G., Darve, E. ELSEVIER SCIENCE BV. 2018: 49–64

  View details for DOI 10.1016/j.parco.2017.12.004

  View details for Web of Science ID 000428486900005

• Riverine Bathymetry Imaging With Indirect Observations WATER RESOURCES RESEARCH Lee, J., Ghorbanidehno, H., Farthing, M. W., Hesser, T. J., Darve, E. F., Kitanidis, P. K. 2018; 54 (5): 3704–27

  View details for DOI 10.1029/2017WR021649

  View details for Web of Science ID 000442351300025

• An efficient preconditioner for the fast simulation of a 2D stokes flow in porous media INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING Quaife, B., Coulier, P., Darve, E. 2018; 113 (4): 561–80

  View details for DOI 10.1002/nme.5626

  View details for Web of Science ID 000419121800001

• ON THE NUMERICAL RANK OF RADIAL BASIS FUNCTION KERNELS IN HIGH DIMENSIONS SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS Wang, R., Li, Y., Darve, E. 2018; 39 (4): 1810–35

  View details for DOI 10.1137/17M1135803

  View details for Web of Science ID 000453731100012

• LOW-RANK FACTORIZATIONS IN DATA SPARSE HIERARCHICAL ALGORITHMS FOR PRECONDITIONING SYMMETRIC POSITIVE DEFINITE MATRICES SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS Agullo, E., Darve, E., Giraud, L., Harness, Y. 2018; 39 (4): 1701–25

  View details for DOI 10.1137/17M1151158

  View details for Web of Science ID 000453731100008

• Optimal estimation and scheduling in aquifer management using the rapid feedback control method ADVANCES IN WATER RESOURCES Ghorbanidehno, H., Kokkinaki, A., Kitanidis, P. K., Darve, E. 2017; 110: 310–18

  View details for DOI 10.1016/j.advwatres.2017.10.011

  View details for Web of Science ID 000418262400024

• Efficiently sampling conformations and pathways using the concurrent adaptive sampling (CAS) algorithm. The Journal of chemical physics Ahn, S. H., Grate, J. W., Darve, E. F. 2017; 147 (7): 074115

  Abstract

  Molecular dynamics simulations are useful in obtaining thermodynamic and kinetic properties of bio-molecules, but they are limited by the time scale barrier. That is, we may not obtain properties' efficiently because we need to run microseconds or longer simulations using femtosecond time steps. To overcome this time scale barrier, we can use the weighted ensemble (WE) method, a powerful enhanced sampling method that efficiently samples thermodynamic and kinetic properties. However, the WE method requires an appropriate partitioning of phase space into discrete macrostates, which can be problematic when we have a high-dimensional collective space or when little is known a priori about the molecular system. Hence, we developed a new WE-based method, called the "Concurrent Adaptive Sampling (CAS) algorithm," to tackle these issues. The CAS algorithm is not constrained to use only one or two collective variables, unlike most reaction coordinate-dependent methods. Instead, it can use a large number of collective variables and adaptive macrostates to enhance the sampling in the high-dimensional space. This is especially useful for systems in which we do not know what the right reaction coordinates are, in which case we can use many collective variables to sample conformations and pathways. In addition, a clustering technique based on the committor function is used to accelerate sampling the slowest process in the molecular system. In this paper, we introduce the new method and show results from two-dimensional models and bio-molecules, specifically penta-alanine and a triazine trimer.

  View details for DOI 10.1063/1.4999097

  View details for PubMedID 28830168

• Smoothing-based compressed state Kalman filter for joint state-parameter estimation: Applications in reservoir characterization and CO2 storage monitoring WATER RESOURCES RESEARCH Li, Y. J., Kokkinaki, A., Darve, E. F., Kitanidis, P. K. 2017; 53 (8): 7190–7207

  View details for DOI 10.1002/2016WR020168

  View details for Web of Science ID 000411202000044

• A numerical study of super-resolution through fast 3D wideband algorithm for scattering in highly-heterogeneous media WAVE MOTION Letourneau, P., Wu, Y., Papanicolaou, G., Garnier, J., Darve, E. 2017; 70: 113-134

  View details for DOI 10.1016/j.wavemoti.2016.08.012

  View details for Web of Science ID 000397375900009

• Computing the non-Markovian coarse-grained interactions derived from the Mori-Zwanzig formalism in molecular systems: Application to polymer melts JOURNAL OF CHEMICAL PHYSICS Li, Z., Lee, H. S., Darve, E., Karniadakis, G. E. 2017; 146 (1)

  Abstract

  Memory effects are often introduced during coarse-graining of a complex dynamical system. In particular, a generalized Langevin equation (GLE) for the coarse-grained (CG) system arises in the context of Mori-Zwanzig formalism. Upon a pairwise decomposition, GLE can be reformulated into its pairwise version, i.e., non-Markovian dissipative particle dynamics (DPD). GLE models the dynamics of a single coarse particle, while DPD considers the dynamics of many interacting CG particles, with both CG systems governed by non-Markovian interactions. We compare two different methods for the practical implementation of the non-Markovian interactions in GLE and DPD systems. More specifically, a direct evaluation of the non-Markovian (NM) terms is performed in LE-NM and DPD-NM models, which requires the storage of historical information that significantly increases computational complexity. Alternatively, we use a few auxiliary variables in LE-AUX and DPD-AUX models to replace the non-Markovian dynamics with a Markovian dynamics in a higher dimensional space, leading to a much reduced memory footprint and computational cost. In our numerical benchmarks, the GLE and non-Markovian DPD models are constructed from molecular dynamics (MD) simulations of star-polymer melts. Results show that a Markovian dynamics with auxiliary variables successfully generates equivalent non-Markovian dynamics consistent with the reference MD system, while maintaining a tractable computational cost. Also, transient subdiffusion of the star-polymers observed in the MD system can be reproduced by the coarse-grained models. The non-interacting particle models, LE-NM/AUX, are computationally much cheaper than the interacting particle models, DPD-NM/AUX. However, the pairwise models with momentum conservation are more appropriate for correctly reproducing the long-time hydrodynamics characterised by an algebraic decay in the velocity autocorrelation function.

  View details for DOI 10.1063/1.4973347

  View details for Web of Science ID 000393431000007

  View details for PubMedID 28063444

• Sparse Supernodal Solver Using Block Low-Rank Compression Pichon, G., Darve, E., Faverge, M., Ramet, P., Roman, J., IEEE IEEE. 2017: 1138–47

  View details for DOI 10.1109/IPDPSW.2017.86

  View details for Web of Science ID 000417418900123

• Efficient mesh deformation based on radial basis function interpolation by means of the inverse fast multipole method COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING Coulier, P., Darve, E. 2016; 308: 286-309

  View details for DOI 10.1016/j.cma.2016.05.029

  View details for Web of Science ID 000380512800013

• A fast, memory efficient and robust sparse preconditioner based on a multifrontal approach with applications to finite-element matrices INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING Aminfar, A., Darve, E. 2016; 107 (6): 520-540

  View details for DOI 10.1002/nme.5196

  View details for Web of Science ID 000380035600004

• Task-based FMM for heterogeneous architectures CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE Agullo, E., Bramas, B., Coulaud, O., Darve, E., Messner, M., Takahashi, T. 2016; 28 (9): 2608-2629

  View details for DOI 10.1002/cpe.3723

  View details for Web of Science ID 000378743500003

• A fast block low-rank dense solver with applications to finite-element matrices JOURNAL OF COMPUTATIONAL PHYSICS Aminfar, A., Ambikasaran, S., Darve, E. 2016; 304: 170-188

  View details for DOI 10.1016/j.jcp.2015.10.012

  View details for Web of Science ID 000365041900008

• Real-time data assimilation for large-scale systems: The spectral Kalman filter ADVANCES IN WATER RESOURCES Ghorbanidehno, H., Kokkinaki, A., Li, J. Y., Darve, E., Kitanidis, P. K. 2015; 86: 260-272

  View details for DOI 10.1016/j.advwatres.2015.07.017

  View details for Web of Science ID 000365623500002

• The compressed state Kalman filter for nonlinear state estimation: Application to large-scale reservoir monitoring WATER RESOURCES RESEARCH Li, J. Y., Kokkinaki, A., Ghorbanidehno, H., Darve, E. F., Kitanidis, P. K. 2015; 51 (12): 9942-9963

  View details for DOI 10.1002/2015WR017203

  View details for Web of Science ID 000368421500031

• A new sparse matrix vector multiplication graphics processing unit algorithm designed for finite element problems INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING Wong, J., Kuhl, E., Darve, E. 2015; 102 (12): 1784-1814

  View details for DOI 10.1002/nme.4865

  View details for Web of Science ID 000354625300002

• A comparison of weighted ensemble and Markov state model methodologies JOURNAL OF CHEMICAL PHYSICS Feng, H., Costaouec, R., Darve, E., Izaguirre, J. A. 2015; 142 (21)

  Abstract

  Computation of reaction rates and elucidation of reaction mechanisms are two of the main goals of molecular dynamics (MD) and related simulation methods. Since it is time consuming to study reaction mechanisms over long time scales using brute force MD simulations, two ensemble methods, Markov State Models (MSMs) and Weighted Ensemble (WE), have been proposed to accelerate the procedure. Both approaches require clustering of microscopic configurations into networks of "macro-states" for different purposes. MSMs model a discretization of the original dynamics on the macro-states. Accuracy of the model significantly relies on the boundaries of macro-states. On the other hand, WE uses macro-states to formulate a resampling procedure that kills and splits MD simulations for achieving better efficiency of sampling. Comparing to MSMs, accuracy of WE rate predictions is less sensitive to the definition of macro-states. Rigorous numerical experiments using alanine dipeptide and penta-alanine support our analyses. It is shown that MSMs introduce significant biases in the computation of reaction rates, which depend on the boundaries of macro-states, and Accelerated Weighted Ensemble (AWE), a formulation of weighted ensemble that uses the notion of colors to compute fluxes, has reliable flux estimation on varying definitions of macro-states. Our results suggest that whereas MSMs provide a good idea of the metastable sets and visualization of overall dynamics, AWE provides reliable rate estimations requiring less efforts on defining macro-states on the high dimensional conformational space.

  View details for DOI 10.1063/1.4921890

  View details for Web of Science ID 000355931800069

  View details for PubMedID 26049485

  View details for PubMedCentralID PMC4457661

• OPTIMIZING THE ADAPTIVE FAST MULTIPOLE METHOD FOR FRACTAL SETS SIAM JOURNAL ON SCIENTIFIC COMPUTING Pouransari, H., Darve, E. 2015; 37 (2): A1040-A1066

  View details for DOI 10.1137/140962681

  View details for Web of Science ID 000353838400020

• AWE-WQ: Fast-Forwarding Molecular Dynamics Using the Accelerated Weighted Ensemble JOURNAL OF CHEMICAL INFORMATION AND MODELING Abdul-Wahid, B., Feng, H., Rajan, D., Costaouec, R., Darve, E., Thain, D., Izaguirre, J. A. 2014; 54 (10): 3033-3043

  Abstract

  A limitation of traditional molecular dynamics (MD) is that reaction rates are difficult to compute. This is due to the rarity of observing transitions between metastable states since high energy barriers trap the system in these states. Recently the weighted ensemble (WE) family of methods have emerged which can flexibly and efficiently sample conformational space without being trapped and allow calculation of unbiased rates. However, while WE can sample correctly and efficiently, a scalable implementation applicable to interesting biomolecular systems is not available. We provide here a GPLv2 implementation called AWE-WQ of a WE algorithm using the master/worker distributed computing WorkQueue (WQ) framework. AWE-WQ is scalable to thousands of nodes and supports dynamic allocation of computer resources, heterogeneous resource usage (such as central processing units (CPU) and graphical processing units (GPUs) concurrently), seamless heterogeneous cluster usage (i.e., campus grids and cloud providers), and support for arbitrary MD codes such as GROMACS, while ensuring that all statistics are unbiased. We applied AWE-WQ to a 34 residue protein which simulated 1.5 ms over 8 months with peak aggregate performance of 1000 ns/h. Comparison was done with a 200 μs simulation collected on a GPU over a similar timespan. The folding and unfolded rates were of comparable accuracy.

  View details for DOI 10.1021/ci500321g

  View details for Web of Science ID 000343849600036

  View details for PubMedID 25207854

• A Kalman filter powered by H-2-matrices for quasi-continuous data assimilation problems WATER RESOURCES RESEARCH Li, J. Y., Ambikasaran, S., Darve, E. F., Kitanidis, P. K. 2014; 50 (5): 3734-3749

  View details for DOI 10.1002/2013WR014607

  View details for Web of Science ID 000337672900008

• Method and advantages of genetic algorithms in parameterization of interatomic potentials: Metal oxides COMPUTATIONAL MATERIALS SCIENCE Solomon, J., Chung, P., Srivastava, D., Darve, E. 2014; 81: 453-465

  View details for DOI 10.1016/j.commatsci.2013.08.054

  View details for Web of Science ID 000326940300064

• CAUCHY FAST MULTIPOLE METHOD FOR GENERAL ANALYTIC KERNELS SIAM JOURNAL ON SCIENTIFIC COMPUTING Letourneau, P., Cecka, C., Darve, E. 2014; 36 (2): A396-A426

  View details for DOI 10.1137/120891617

  View details for Web of Science ID 000335817600005

• TASK-BASED FMM FOR MULTICORE ARCHITECTURES SIAM JOURNAL ON SCIENTIFIC COMPUTING Agullo, E., Bramas, B., Coulaud, O., Darve, E., Messner, M., Takahashi, T. 2014; 36 (1): C66-C93

  View details for DOI 10.1137/130915662

  View details for Web of Science ID 000333415500024

• An Fast Direct Solver for Partial Hierarchically Semi-Separable Matrices JOURNAL OF SCIENTIFIC COMPUTING Ambikasaran, S., Darve, E. 2013; 57 (3): 477-501

  View details for DOI 10.1007/s10915-013-9714-z

  View details for Web of Science ID 000326401200003

• Large-scale stochastic linear inversion using hierarchical matrices COMPUTATIONAL GEOSCIENCES Ambikasaran, S., Li, J. Y., Kitanidis, P. K., Darve, E. 2013; 17 (6): 913-927

  View details for DOI 10.1007/s10596-013-9364-0

  View details for Web of Science ID 000328319900004

• ANALYSIS OF THE ACCELERATED WEIGHTED ENSEMBLE METHODOLOGY DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS Costaouec, R., Feng, H., Izaguirre, J., Darve, E. 2013: 171-181

  View details for Web of Science ID 000328571500019

• The accuracy of the CHARMM22/CMAP and AMBER ff99SB force fields for modelling the antimicrobial peptide cecropin P1 MOLECULAR SIMULATION Kia, A., Darve, E. 2013; 39 (11): 922-936

  View details for DOI 10.1080/08927022.2013.781599

  View details for Web of Science ID 000323634200009

• A fast algorithm for sparse matrix computations related to inversion JOURNAL OF COMPUTATIONAL PHYSICS Li, S., Wu, W., Darve, E. 2013; 242: 915-945

  View details for DOI 10.1016/j.jcp.2013.01.036

  View details for Web of Science ID 000319049800046

• FOURIER-BASED FAST MULTIPOLE METHOD FOR THE HELMHOLTZ EQUATION SIAM JOURNAL ON SCIENTIFIC COMPUTING Cecka, C., Darve, E. 2013; 35 (1): A79-A103

  View details for DOI 10.1137/11085774X

  View details for Web of Science ID 000315575000004

• Accuracy in One-way and Two-way Algorithms for Computing Desired Entries in the Inverse of Sparse Matrices 11th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM) Li, S., Darve, E. AMER INST PHYSICS. 2013: 1501–1504

  View details for DOI 10.1063/1.4825806

  View details for Web of Science ID 000331472800355

• Task-based FMM for multicore architectures Agullo, E., Bramas, B., Coulaud, O., Darve, E., Messner, M., Takahashi, T. 2013
• An\ mathcal O (N\ log N) Fast Direct Solver for Partial Hierarchically Semi-Separable Matrices Journal of Scientific Computing Ambikasaran, S., Darve, E. 2013; 57 (3): 477-501

  View details for DOI 10.1007/s10915-013-9714-z

• Fast Algorithms for Bayesian Inversion Computational Challenges in the Geosciences Ambikasaran, S., Saibaba, A. K., Darve, E. F., Kitanidis, Peter, K. 2013; 156: 101-142

  View details for DOI 10.1007/978-1-4614-7434-0_5

• Task-based Parallelization of the Fast Multipole Method on NVIDIA GPUs and Multicore Processors Agullo, E., Bramas, B., Coulaud, O., Darve, E., Messner, M., Takahashi, T. 2013
• Optimizing the Black-box FMM for Smooth and Oscillatory Kernels Darve, E., Messner, M., Schanz, M., Coulaud, O. 2013
• Composition and reuse with compiled domain-specific languages Darve, E., Sujeeth, Arvind, K., Rompf, T., Brown, Kevin, J., Lee, H., Chafi, H. 2013
• Folding Proteins at 500 ns/hour with Work Queue. Proceedings ... IEEE International Conference on eScience. IEEE International Conference on eScience Abdul-Wahid, B., Yu, L., Rajan, D., Feng, H., Darve, E., Thain, D., Izaguirre, J. A. 2012; 2012: 1-8

  Abstract

  Molecular modeling is a field that traditionally has large computational costs. Until recently, most simulation techniques relied on long trajectories, which inherently have poor scalability. A new class of methods is proposed that requires only a large number of short calculations, and for which minimal communication between computer nodes is required. We considered one of the more accurate variants called Accelerated Weighted Ensemble Dynamics (AWE) and for which distributed computing can be made efficient. We implemented AWE using the Work Queue framework for task management and applied it to an all atom protein model (Fip35 WW domain). We can run with excellent scalability by simultaneously utilizing heterogeneous resources from multiple computing platforms such as clouds (Amazon EC2, Microsoft Azure), dedicated clusters, grids, on multiple architectures (CPU/GPU, 32/64bit), and in a dynamic environment in which processes are regularly added or removed from the pool. This has allowed us to achieve an aggregate sampling rate of over 500 ns/hour. As a comparison, a single process typically achieves 0.1 ns/hour.

  View details for DOI 10.1109/eScience.2012.6404429

  View details for PubMedID 25540799

  View details for PubMedCentralID PMC4273313

• Application of Hierarchical Matrices to Linear Inverse Problems in Geostatistics OIL & GAS SCIENCE AND TECHNOLOGY-REVUE D IFP ENERGIES NOUVELLES Saibaba, A. K., Ambikasaran, S., Li, J. Y., Kitanidis, P. K., Darve, E. F. 2012; 67 (5): 857-875

  View details for DOI 10.2516/ogst/2012064

  View details for Web of Science ID 000314141700010

• Fast directional multilevel summation for oscillatory kernels based on Chebyshev interpolation JOURNAL OF COMPUTATIONAL PHYSICS Messner, M., Schanz, M., Darve, E. 2012; 231 (4): 1175-1196

  View details for DOI 10.1016/j.jcp.2011.09.027

  View details for Web of Science ID 000300462100005

• Extension and optimization of the FIND algorithm: Computing Green's and less-than Green's functions JOURNAL OF COMPUTATIONAL PHYSICS Li, S., Darve, E. 2012; 231 (4): 1121-1139

  View details for DOI 10.1016/j.jcp.2011.05.027

  View details for Web of Science ID 000300462100003

• Optimizing the multipole-to-local operator in the fast multipole method for graphical processing units INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING Takahashi, T., Cecka, C., Fong, W., Darve, E. 2012; 89 (1): 105-133

  View details for DOI 10.1002/nme.3240

  View details for Web of Science ID 000298589300005

• Time integrators based on approximate discontinuous Hamiltonians INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING Dharmaraja, S., Kesari, H., Darve, E., Lew, A. J. 2012; 89 (1): 71-104

  View details for DOI 10.1002/nme.3236

  View details for Web of Science ID 000298589300004

• Fast Multipole Method Using the Cauchy Integral Formula Workshop on Numerical Analysis and Multiscale Computations Cecka, C., Letourneau, P., Darve, E. SPRINGER-VERLAG BERLIN. 2012: 127–144

  View details for DOI 10.1007/978-3-642-21943-6_6

  View details for Web of Science ID 000310180800006

• Folding Proteins at 500 ns/hour with Work Queue IEEE 8th International Conference on E-Science (e-Science) Abdul-Wahid, B., Yu, L., Rajan, D., Feng, H., Darve, E., Thain, D., Izaguirre, J. A. IEEE. 2012

  View details for Web of Science ID 000315360600019

• Optimization of the parallel black-box fast multipole method on CUDA Innovative Parallel Computing (InPar) Takahashi, T., Cecka, C., Darve, E. 2012: 1 - 14

  View details for DOI 10.1109/InPar.2012.6339607

• Poster: Matrices over Runtime Systems at Exascale Darve, E., Agullo, E., Bosilca, G., Bramas, B., Castagnede, C., Coulaud, O. 2012
• Folding Proteins at 500 ns/hour with Work Queue Abdul-Wahid, B., Yu, L., Rajan, D., Feng, H., Darve, E., Thain, D. 2012

  View details for DOI 10.1109/eScience.2012.6404429

• EFFICIENT DATA ASSIMILATION TOOL IN CONJUNCTION WITH TOUGH2 FOR CO2 MONITORING Li, J. Y., Ambikasaran, S., Kitanidis, P. K., Darve, E. 2012
• Matrices Over Runtime Systems at Exascale Agullo, E., Bosilca, G., Bramas, B., Castagnede, C., Coulaud, O., Darve, E. 2012
• Matrices Over Runtime Systems @ Exascale 25th ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC) Agullo, E., Bosilca, G., Bramas, B., Castagnede, C., Coulaud, O., Darve, E., Dongarra, J., Faverge, M., Furmento, N., Giraud, L., Lacoste, X., Langou, J., Ltaief, H., Messner, M., Namyst, R., Ramet, P., Takahashi, T., Thibault, S., Tomov, S., Yamazaki, I. IEEE. 2012: 1330–1331

  View details for Web of Science ID 000320824300158

• Assembly of finite element methods on graphics processors INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING Cecka, C., Lew, A. J., Darve, E. 2011; 85 (5): 640-669

  View details for DOI 10.1002/nme.2989

  View details for Web of Science ID 000286775000007

• The fast multipole method on parallel clusters, multicore processors, and graphics processing units COMPTES RENDUS MECANIQUE Darve, E., Cecka, C., Takahashi, T. 2011; 339 (2-3): 185-193

  View details for DOI 10.1016/j.crme.2010.12.005

  View details for Web of Science ID 000287768400012

• Liszt: a domain specific language for building portable mesh-based PDE solvers DeVito, Z., Joubert, N., Palacios, F., Oakley, S., Medina, M., Barrientos, M., Darve, E. 2011

  View details for DOI 10.1145/2063384.2063396

• Generalized Fast Multipole Method 9th World Congress on Computational Mechanics/4th Asian Pacific Congress on Computational Mechanics Letourneau, P., Cecka, C., Darve, E. IOP PUBLISHING LTD. 2010

  View details for DOI 10.1088/1757-899X/10/1/012230

  View details for Web of Science ID 000290445000231

• The CUDA codes to perform M2L operation in FMM Takahashi, T., Cecka, C., Fong, W., Darve, E. 2010
• Generalized fast multipole method Létourneau, P. D., Cecka, C., Darve, E. 2010

  View details for DOI 10.1088/1757-899X/10/1/012230

• An implementation of low-frequency fast multipole BIEM for Helmholtz'equation on GPU Takahashi, T., Cecka, C., Darve, E. 2010
• Application of assembly of finite element methods on graphics processors for real-time elastodynamics GPU Computing Gems Cecka, C., Lew, A., Darve, E. edited by Hwu, Wen-mei, W. Elsevier. 2010: 1
• Introduction to Assembly of Finite Element Methods on Graphics Processors 9th World Congress on Computational Mechanics/4th Asian Pacific Congress on Computational Mechanics Cecka, C., Lew, A., Darve, E. IOP PUBLISHING LTD. 2010

  View details for DOI 10.1088/1757-899X/10/1/012009

  View details for Web of Science ID 000290445000010

• The black-box fast multipole method JOURNAL OF COMPUTATIONAL PHYSICS Fong, W., Darve, E. 2009; 228 (23): 8712-8725

  View details for DOI 10.1016/j.jcp.2009.08.031

  View details for Web of Science ID 000271671100011

• A hybrid method for the parallel computation of Green's functions JOURNAL OF COMPUTATIONAL PHYSICS Petersen, D. E., Li, S., Stokbro, K., Sorensen, H. H., Hansen, P. C., Skelboe, S., Darve, E. 2009; 228 (14): 5020-5039

  View details for DOI 10.1016/j.jcp.2009.03.035

  View details for Web of Science ID 000267846500005

• Computing generalized Langevin equations and generalized Fokker-Planck equations PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Darve, E., Solomon, J., Kia, A. 2009; 106 (27): 10884-10889

  Abstract

  The Mori-Zwanzig formalism is an effective tool to derive differential equations describing the evolution of a small number of resolved variables. In this paper we present its application to the derivation of generalized Langevin equations and generalized non-Markovian Fokker-Planck equations. We show how long time scales rates and metastable basins can be extracted from these equations. Numerical algorithms are proposed to discretize these equations. An important aspect is the numerical solution of the orthogonal dynamics equation which is a partial differential equation in a high dimensional space. We propose efficient numerical methods to solve this orthogonal dynamics equation. In addition, we present a projection formalism of the Mori-Zwanzig type that is applicable to discrete maps. Numerical applications are presented from the field of Hamiltonian systems.

  View details for DOI 10.1073/pnas.0902633106

  View details for Web of Science ID 000267796100005

  View details for PubMedID 19549838

  View details for PubMedCentralID PMC2708778

• High-ionic-strength electroosmotic flows in uncharged hydrophobic nanochannels JOURNAL OF COLLOID AND INTERFACE SCIENCE Kim, D., Darve, E. 2009; 330 (1): 194-200

  Abstract

  We report molecular dynamics simulation results of high-ionic-strength electroosmotic flows inside uncharged nanochannels. The possibility of this unusual electrokinetic phenomenon has been discussed by Dukhin et al. [A. Dukhin, S. Dukhin, P. Goetz, Langmuir 21 (2005) 9990]. Our computed velocity profiles clearly indicate the presence of a net flow with a maximum velocity around 2 m/s. We found the apparent zeta potential to be -29.7+/-6.8 mV, using the Helmholtz-Smoluchowski relation and the measured mean velocity. This value is comparable to experimentally measured values in Dukhin et al. and references therein. We also investigate the orientations of water molecules in response to an electric field by computing polarization density. Water molecules in the bulk region are oriented along the direction of the external electric field, while their near-wall orientation shows oscillations. The computation of three-dimensional density distributions of sodium and chloride ions around each individual water molecule show that chloride ions tend to concentrate near a water molecule, whereas sodium ions are diffusely distributed.

  View details for DOI 10.1016/j.jcis.2008.10.029

  View details for Web of Science ID 000262229700028

  View details for PubMedID 19007939

• Optimization of the FIND Algorithm to Compute the Inverse of a Sparse Matrix 13th International Workshop on Computational Electronics Li, S., Darve, E. IEEE. 2009: 285–288

  View details for Web of Science ID 000272988200074

• Concentration distributions of arbitrary shaped particles in microfluidic channel flows Bulletin of the American Physical Society Saibaba, A., Shaqfeh, E., Darve, E. 2009; 54 (19)
• Optimization of the FIND algorithm to compute the inverse of a sparse matrix Li, S., Darve, E. 2009

  View details for DOI 10.1109/IWCE.2009.5091136

• Computing generalized Langevin equations and generalized Fokker–Planck equations Darve, E., Solomon, J., Kia, A. edited by Chorin, Alexandre, J. 2009

  View details for DOI 10.1073/pnas.0902633106

• Large calculation of the flow over a hypersonic vehicle using a GPU JOURNAL OF COMPUTATIONAL PHYSICS Elsen, E., LeGresley, P., Darve, E. 2008; 227 (24): 10148-10161

  View details for DOI 10.1016/j.jcp.2008.08.023

  View details for Web of Science ID 000261207600009

• Computing entries of the inverse of a sparse matrix using the FIND algorithm JOURNAL OF COMPUTATIONAL PHYSICS Li, S., Ahmed, S., Klimeck, G., Darve, E. 2008; 227 (22): 9408-9427

  View details for DOI 10.1016/j.jcp.2008.06.033

  View details for Web of Science ID 000260645700006

• Fast electrostatic force calculation on parallel computer clusters JOURNAL OF COMPUTATIONAL PHYSICS Kia, A., Kim, D., Darve, E. 2008; 227 (19): 8551-8567

  View details for DOI 10.1016/j.jcp.2008.06.016

  View details for Web of Science ID 000259753700005

• Stability of asynchronous variational integrators JOURNAL OF COMPUTATIONAL PHYSICS Fong, W., Darve, E., Lew, A. 2008; 227 (18): 8367-8394

  View details for DOI 10.1016/j.jcp.2008.05.017

  View details for Web of Science ID 000258972000007

• Adaptive biasing force method for scalar and vector free energy calculations JOURNAL OF CHEMICAL PHYSICS Darve, E., Rodriguez-Gomez, D., Pohorille, A. 2008; 128 (14)

  Abstract

  In free energy calculations based on thermodynamic integration, it is necessary to compute the derivatives of the free energy as a function of one (scalar case) or several (vector case) order parameters. We derive in a compact way a general formulation for evaluating these derivatives as the average of a mean force acting on the order parameters, which involves first derivatives with respect to both Cartesian coordinates and time. This is in contrast with the previously derived formulas, which require first and second derivatives of the order parameter with respect to Cartesian coordinates. As illustrated in a concrete example, the main advantage of this new formulation is the simplicity of its use, especially for complicated order parameters. It is also straightforward to implement in a molecular dynamics code, as can be seen from the pseudocode given at the end. We further discuss how the approach based on time derivatives can be combined with the adaptive biasing force method, an enhanced sampling technique that rapidly yields uniform sampling of the order parameters, and by doing so greatly improves the efficiency of free energy calculations. Using the backbone dihedral angles Phi and Psi in N-acetylalanyl-N'-methylamide as a numerical example, we present a technique to reconstruct the free energy from its derivatives, a calculation that presents some difficulties in the vector case because of the statistical errors affecting the derivatives.

  View details for DOI 10.1063/1.2829861

  View details for Web of Science ID 000255470300020

  View details for PubMedID 18412436

• A black-box Fast Multipole Method Darve, E., Fong, W. 2008
• BIRS 08w5074: Mathematical and numerical methods for free energy calculations in molecular systems Darve, E., Chipot, C. 2008
• Fast inverse using nested dissection for NEGF JOURNAL OF COMPUTATIONAL ELECTRONICS Li, S., Ahmed, S., Darve, E. 2007; 6 (1-3): 187-190

  View details for DOI 10.1007/s10825-006-0112-8

  View details for Web of Science ID 000208473600045

• Stability of asynchronous variational integrators 21st International Workshop on Principles of Advanced and Distributed Simulation (PADS 2007) Fong, W., Darve, E., Lew, A. IEEE COMPUTER SOC. 2007: 38–44

  View details for Web of Science ID 000248079800006

• Thermodynamic integration using constrained and unconstrained dynamics Free Energy Calculations Darve, E. 2007; 86: 119-170
• The effect of stratification on the wave number selection in the instability of sedimenting spheroids PHYSICS OF FLUIDS Saintillan, D., Shaqfeh, E. S., Darve, E. 2006; 18 (12)

  View details for DOI 10.1063/1.2396913

  View details for Web of Science ID 000243158200003

• Stabilization of a suspension of sedimenting rods by induced-charge electrophoresis PHYSICS OF FLUIDS Saintillan, D., Shaqfeh, E. S., Darve, E. 2006; 18 (12)

  View details for DOI 10.1063/1.2404948

  View details for Web of Science ID 000243158200013

• Hydrodynamic interactions in the induced-charge electrophoresis of colloidal rod dispersions JOURNAL OF FLUID MECHANICS Saintillan, D., Darve, E., Shaqfeh, E. S. 2006; 563: 223-259

  View details for DOI 10.1017/S0022112006001376

  View details for Web of Science ID 000241085500011

• Effect of flexibility on the shear-induced migration of short-chain polymers in parabolic channel flow JOURNAL OF FLUID MECHANICS Saintillan, D., Shaqfeh, E. S., Darve, E. 2006; 557: 297-306

  View details for DOI 10.1017/S0022112006000243

  View details for Web of Science ID 000238820700013

• Molecular dynamics simulation of electro-osmotic flows in rough wall nanochannels PHYSICAL REVIEW E Kim, D., Darve, E. 2006; 73 (5)

  Abstract

  We performed equilibrium and nonequilibrium molecular dynamics simulation to study electro-osmotic flows inside charged nanochannels with different types of surface roughness. We modeled surface roughness as a sequence of two-dimensional subnanoscale grooves and ridges (step function-type roughness) along the flow direction. The amplitude, spatial period, and symmetry of surface roughness were varied. The amplitude of surface roughness was on the order of the Debye length. The walls have uniform negative charges at the interface with fluids. We included only positive ions (counterions) for simplicity of computation. For the smooth wall, we compared our molecular dynamics simulation results to the well-known Poisson-Boltzmann theory. The density profiles of water molecules showed "layering" near the wall. For the rough walls, the density profiles measured from the wall are similar to those for the smooth wall except near where the steps are located. Because of the layering of water molecules and the finite size effect of ions and the walls, the ionic distribution departs from the Boltzmann distribution. To further understand the structure of water molecules and ions, we computed the polarization density. Near the wall, its z component dominates the other components, indicating the preferred orientation ("ordering") of water molecules. Especially, inside the groove for the rough walls, its maximum is 10% higher (stronger ordering) than for the smooth wall. The dielectric constant, computed with a Clausius-Mosotti-type equation, confirmed the ordering near the wall and the enhanced ordering inside the groove. The residence time and the diffusion coefficient, computed using the velocity autocorrelation function, showed that the diffusion of water and ions along the direction normal to the wall is significantly reduced near the wall and further decreases inside the groove. Along the flow direction, the diffusion of water and ions inside the groove is significantly lowered while it is similar to the bulk value elsewhere. We performed nonequilibrium molecular dynamics simulation to compute electro-osmotic velocities and flow rates. The velocity profiles correspond to those for overlapped electric double layers. For the rough walls, velocity inside the groove is close to zero, meaning that the channel height is effectively reduced. The flow rate was found to decrease as the period of surface roughness decreases or the amplitude of surface roughness increases. We defined the zeta potential as the electrostatic potential at the location of a slip plane. We computed the electrostatic potential with the ionic distribution and the dielectric constant both from our molecular dynamics simulation. We estimated the slip plane from the velocity profile. The zeta potential showed the same trend as the flow rate: it decreases with an increasing amplitude and a decreasing period of surface roughness.

  View details for DOI 10.1103/PhysRevE.73.051203

  View details for Web of Science ID 000237951300019

  View details for PubMedID 16802924

• The growth of concentration fluctuations in dilute dispersions of orientable and deformable particles under sedimentation JOURNAL OF FLUID MECHANICS Saintillan, D., Shaqfeh, E. S., Darve, E. 2006; 553: 347-388

  View details for DOI 10.1017/S0022112006009025

  View details for Web of Science ID 000237366800015

• Numerical Methods for Calculating the Potential of Mean Force New Algorithms for Macromolecular Simulation Darve, E. 2006; 49: 213-249

  View details for DOI 10.1007/3-540-31618-3_13

• A Bayesian approach to calculating free energies in chemical and biological systems 26th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering Pohorille, A., Darve, E. AMER INST PHYSICS. 2006: 23–30

  View details for Web of Science ID 000244484400003

• Stratification and wavenumber selection in the instability of sedimenting spheroids Saintillan, D., Shaqfeh, E. S., Darve, E. 2006
• The Dynamics of Rodlike Particles under Sedimentation and Induced-Charge Electrophoresis Shaqfeh, E. S., Saintillan, D., Darve, E. 2006
• Adaptive Biasing Force Method for Vector Free Energy Calculations Darve, E. 2006
• Electric Double Layer Structures near Rough Surfaces: Molecular Dynamics Simulation Bulletin of the American Physical Society Kim, D., Darve, E. 2006
• Fast Inverse using Nested Dissection for the Non Equilibrium Green's Function 11th International Workshop on Computational Electronics Li, S., Darve, E. 2006
• Effect of flexibility on the shear-induced migration of short polymers in parabolic channel flow Saintillan, D., Shaqfeh, E. S., Darve, E. 2006
• A smooth particle-mesh Ewald algorithm for Stokes suspension simulations: The sedimentation of fibers PHYSICS OF FLUIDS Saintillan, D., Darve, E., Shaqfeh, E. S. 2005; 17 (3)

  View details for DOI 10.1063/1.1862262

  View details for Web of Science ID 000227372600031

• Interactions of wall roughness and electroosmotic flows inside nanochannels 3rd International Conference on Microchannels and Minichannels Kim, D., Darve, E. AMER SOC MECHANICAL ENGINEERS. 2005: 641–645

  View details for Web of Science ID 000243025800091

• Concentration fluctuations in dilute suspensions of orientable and deformable particles under sedimentation Saintillan, D., Shaqfeh, E. S., Darve, E. 2005
• Hydrodynamic interactions in colloidal dispersions of conducting rods under induced-charge electrophoresis Saintillan, D., Shaqfeh, E. S., Darve, E. 2005
• Induced-charge electrophoresis in suspensions of rodlike particles: Theory and simulations ASME International Mechanical Engineering Congress and Exposition Saintillan, D., Darve, E., Shaqfeh, E. S. AMER SOC MECHANICAL ENGINEERS. 2005: 251–256

  View details for Web of Science ID 000243038600033

• Microstructure in the sedimentation of anisotropic and deformable particles ASME International Mechanical Engineering Congress and Exposition Saintillan, D., Darve, E., Shaqfeh, E. S. AMER SOC MECHANICAL ENGINEERS. 2005: 797–803

  View details for Web of Science ID 000243038600101

• Efficient fast multipole method for low-frequency scattering JOURNAL OF COMPUTATIONAL PHYSICS Darve, E., Have, P. 2004; 197 (1): 341-363

  View details for DOI 10.1016/j.jcp.2003.12.002

  View details for Web of Science ID 000221833000016

• A fast multipole method for Maxwell equations stable at all frequencies PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES Darve, E., Have, P. 2004; 362 (1816): 603-628

  Abstract

  The solution of Helmholtz and Maxwell equations by integral formulations (kernel in exp(i kr)/r) leads to large dense linear systems. Using direct solvers requires large computational costs in O(N(3)). Using iterative solvers, the computational cost is reduced to large matrix-vector products. The fast multipole method provides a fast numerical way to compute convolution integrals. Its application to Maxwell and Helmholtz equations was initiated by Rokhlin, based on a multipole expansion of the interaction kernel. A second version, proposed by Chew, is based on a plane-wave expansion of the kernel. We propose a third approach, the stable-plane-wave expansion, which has a lower computational expense than the multipole expansion and does not have the accuracy and stability problems of the plane-wave expansion. The computational complexity is Nlog N as with the other methods.

  View details for DOI 10.1098/rsta.2003.1337

  View details for Web of Science ID 000220407200010

  View details for PubMedID 15306510

• Assessing the efficiency of free energy calculation methods JOURNAL OF CHEMICAL PHYSICS Rodriguez-Gomez, D., Darve, E., Pohorille, A. 2004; 120 (8): 3563-3578

  Abstract

  The efficiencies of two recently developed methods for calculating free energy changes along a generalized coordinate in a system are discussed in the context of other, related approaches. One method is based on Jarzynski's identity [Phys. Rev. Lett. 78, 2690 (1997)]. The second method relies on thermodynamic integration of the average force and is called the adaptive biasing force method [Darve and Pohorille, J. Chem. Phys. 115, 9169 (2001)]. Both methods are designed such that the system evolves along the chosen coordinate(s) without experiencing free energy barriers and they require calculating the instantaneous, unconstrained force acting on this coordinate using the formula derived by Darve and Pohorille. Efficiencies are analyzed by comparing analytical estimates of statistical errors and by considering two numerical examples-internal rotation of hydrated 1,2-dichloroethane and transfer of fluoromethane across a water-hexane interface. The efficiencies of both methods are approximately equal in the first but not in the second case. During transfer of fluoromethane the system is easily driven away from equilibrium and, therefore, the performance of the method based on Jarzynski's identity is poor.

  View details for DOI 10.1063/1.1642607

  View details for Web of Science ID 000189139700006

  View details for PubMedID 15268518

• Calculating transport properties of nanodevices Conference on Nanosensing Darve, E., Li, S., Teslyar, Y. SPIE-INT SOC OPTICAL ENGINEERING. 2004: 452–463

  View details for DOI 10.1117/12.571494

  View details for Web of Science ID 000226789700046

• Computing flow rate of electroosmotic flows in nanochannels with different wall roughness The Smithsonian/NASA Astrophysics Data System Kim, D., Darve, E. 2004
• Calculating transport properties of nanodevices Darve, E. F., Li, S., Teslyar, Y. 2004

  View details for DOI 10.1117/12.571494

• Dynamic Simulations of Sedimenting Fibers with Fast Fourier Transform Acceleration Abstracts of the Papers Darve, E., Saintillan, D., Shaqfeh, E. S. 2004
• Pattern formation in sedimenting suspensions of spheroids Saintillan, D., Darve, E., Shaqfeh, E. S. 2004
• Analysis and performance results of a molecular modeling application on Merrimac Erez, M., Ahn, J. H., Garg, A., Dally, W. J., Darve, E. 2004

  View details for DOI 10.1109/SC.2004.69

• Fast multipole method for low-frequency electromagnetic scattering 2nd MIT Conference on Computational Fluid and Solid Mechanics Darve, E., Have, P. ELSEVIER SCIENCE BV. 2003: 1299–1302

  View details for Web of Science ID 000184938200317

• Unfolding of proteins: Thermal and mechanical unfolding Hur, J. S., Darve, E. 2003
• Surface tension evaluation in lennard-jones fluid system with untruncated potentials Sinha, S., Shi, B., Dhir, Vijay, K., Freund, Jonathan, B., Darve, E. 2003
• Calculating free energies using a scaled-force molecular dynamics algorithm MOLECULAR SIMULATION Darve, E., Wilson, M. A., Pohorille, A. 2002; 28 (1-2): 113-144

  View details for DOI 10.1080/08927020290004412

  View details for Web of Science ID 000176122400009

• Calculating free energies using average force JOURNAL OF CHEMICAL PHYSICS Darve, E., Pohorille, A. 2001; 115 (20): 9169-9183

  View details for Web of Science ID 000172129300010

• The fast multipole method I: error analysis and asymptotic complexity SIAM JOURNAL ON NUMERICAL ANALYSIS Darve, E. 2000; 38 (1): 98-128

  View details for Web of Science ID 000088263500006

• The fast multipole method: Numerical implementation JOURNAL OF COMPUTATIONAL PHYSICS Darve, E. 2000; 160 (1): 195-240

  View details for Web of Science ID 000086782500010

• Méthodes multipôles rapides: Résolution des équations de Maxwell par formulations intégrales Darve, E., Olivier, P. 1999; 133 ( 99 PA06 6598): 228
• Advanced structured-unstructured solver for electromagnetic scattering from multimaterial objects Darve, E., Loehner, R. 1997

  View details for DOI 10.2514/6.1997-863

• Fast-multipole method: a mathematical study Comptes Rendus de l'Académie des Sciences-Series I-Mathematics Darve, E. 1997; 325 (9): 1037–1042

  View details for DOI http://dx.doi.org/10.1016/S0764-4442(97)89101-X

• THE MULTISTEP FAST MULTIPOLE METHOD: ALGORITHM AND ERROR ESTIMATION DARVE, E. 1997
• SOLVING THE SCALAR WAVE EQUATION VIA A DIRECTIONAL FAST MULTIPOLE METHOD MESSNER, M., DARVE, E., SCHANZ, M.
• A KALMAN FILTER POWERED BY H-MATRICES FOR QUASI-CONTINUOUS DATA ASSIMILATION PROBLEMS LI, Y. J., AMBIKASARAN, S., DARVE, E. F., KITANIDIS, P. K.
• Concentration fluctuations in the dilute sedimentation of anisotropic particles 15th US National Congress Darve, E., SAINTILLAN, D., SHAQFEH, E. S.
• CFD for Blood Transfusions on the Battlefield and Inhalation of Toxic Agents in the Lung Shaqfeh, E. E., Iaccarino, G., Darve, E.
• Dynamic simulations of the instability of sedimenting fibers Saintillan, D., Darve, E., Shaqfeh, E. S.