1
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Sahoo SJ, Xu Q, Lei X, Staros D, Iyer GR, Rubenstein B, Suryanarayana P, Medford AJ. Self-Consistent Convolutional Density Functional Approximations: Application to Adsorption at Metal Surfaces. Chemphyschem 2024; 25:e202300688. [PMID: 38421371 DOI: 10.1002/cphc.202300688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 02/23/2024] [Accepted: 02/25/2024] [Indexed: 03/02/2024]
Abstract
The exchange-correlation (XC) functional in density functional theory is used to approximate multi-electron interactions. A plethora of different functionals are available, but nearly all are based on the hierarchy of inputs commonly referred to as "Jacob's ladder." This paper introduces an approach to construct XC functionals with inputs from convolutions of arbitrary kernels with the electron density, providing a route to move beyond Jacob's ladder. We derive the variational derivative of these functionals, showing consistency with the generalized gradient approximation (GGA), and provide equations for variational derivatives based on multipole features from convolutional kernels. A proof-of-concept functional, PBEq, which generalizes the PBE α ${\alpha }$ framework with α ${\alpha }$ being a spatially-resolved function of the monopole of the electron density, is presented and implemented. It allows a single functional to use different GGAs at different spatial points in a system, while obeying PBE constraints. Analysis of the results underlines the importance of error cancellation and the XC potential in data-driven functional design. After testing on small molecules, bulk metals, and surface catalysts, the results indicate that this approach is a promising route to simultaneously optimize multiple properties of interest.
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Affiliation(s)
| | - Qimen Xu
- Georgia Institute of Technology, Atlanta, GA
- National Supercomputing Center, Shenzhen, People's Republic of China
| | | | - Daniel Staros
- Department of Chemistry, Brown University, Providence, RI
| | - Gopal R Iyer
- Department of Chemistry, Brown University, Providence, RI
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2
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Yonge A, Gusmão GS, Fushimi R, Medford AJ. Model-Based Design of Experiments for Temporal Analysis of Products (TAP): A Simulated Case Study in Oxidative Propane Dehydrogenation. Ind Eng Chem Res 2024; 63:4756-4770. [PMID: 38525291 PMCID: PMC10958505 DOI: 10.1021/acs.iecr.3c03418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 02/15/2024] [Accepted: 02/18/2024] [Indexed: 03/26/2024]
Abstract
Temporal analysis of products (TAP) reactors enable experiments that probe numerous kinetic processes within a single set of experimental data through variations in pulse intensity, delay, or temperature. Selecting additional TAP experiments often involves an arbitrary selection of reaction conditions or the use of chemical intuition. To make experiment selection in TAP more robust, we explore the efficacy of model-based design of experiments (MBDoE) for precision in TAP reactor kinetic modeling. We successfully applied this approach to a case study of synthetic oxidative propane dehydrogenation (OPDH) that involves pulses of propane and oxygen. We found that experiments identified as optimal through the MBDoE for precision generally reduce parameter uncertainties to a higher degree than alternative experiments. The performance of MBDoE for model divergence was also explored for OPDH, with the relevant active sites (catalyst structure) being unknown. An experiment that maximized the divergence between the three proposed mechanisms was identified and provided evidence that improved the mechanism discrimination. However, reoptimization of kinetic parameters eliminated the ability to discriminate between models. The findings yield insight into the prospects and limitations of MBDoE for TAP and transient kinetic experiments.
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Affiliation(s)
- Adam Yonge
- School
of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Gabriel S. Gusmão
- School
of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Rebecca Fushimi
- Catalysis
and Transient Kinetics Group, Idaho National
Laboratory, Idaho
Falls, Idaho 83415, United States
| | - Andrew J. Medford
- School
of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
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3
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Kumar S, Jing X, Pask JE, Medford AJ, Suryanarayana P. Kohn-Sham accuracy from orbital-free density functional theory via Δ-machine learning. J Chem Phys 2023; 159:244106. [PMID: 38147461 DOI: 10.1063/5.0180541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 11/30/2023] [Indexed: 12/28/2023] Open
Abstract
We present a Δ-machine learning model for obtaining Kohn-Sham accuracy from orbital-free density functional theory (DFT) calculations. In particular, we employ a machine-learned force field (MLFF) scheme based on the kernel method to capture the difference between Kohn-Sham and orbital-free DFT energies/forces. We implement this model in the context of on-the-fly molecular dynamics simulations and study its accuracy, performance, and sensitivity to parameters for representative systems. We find that the formalism not only improves the accuracy of Thomas-Fermi-von Weizsäcker orbital-free energies and forces by more than two orders of magnitude but is also more accurate than MLFFs based solely on Kohn-Sham DFT while being more efficient and less sensitive to model parameters. We apply the framework to study the structure of molten Al0.88Si0.12, the results suggesting no aggregation of Si atoms, in agreement with a previous Kohn-Sham study performed at an order of magnitude smaller length and time scales.
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Affiliation(s)
- Shashikant Kumar
- College of Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Xin Jing
- College of Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
- College of Computing, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - John E Pask
- Physics Division, Lawrence Livermore National Laboratory, Livermore, California 94550, USA
| | - Andrew J Medford
- College of Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Phanish Suryanarayana
- College of Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
- College of Computing, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
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4
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Huang PW, Tian N, Rajh T, Liu YH, Innocenti G, Sievers C, Medford AJ, Hatzell MC. Formation of Carbon-Induced Nitrogen-Centered Radicals on Titanium Dioxide under Illumination. JACS Au 2023; 3:3283-3289. [PMID: 38155641 PMCID: PMC10751760 DOI: 10.1021/jacsau.3c00556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 11/20/2023] [Accepted: 11/20/2023] [Indexed: 12/30/2023]
Abstract
Titanium dioxide is the most studied photocatalytic material and has been reported to be active for a wide range of reactions, including the oxidation of hydrocarbons and the reduction of nitrogen. However, the molecular-scale interactions between the titania photocatalyst and dinitrogen are still debated, particularly in the presence of hydrocarbons. Here, we used several spectroscopic and computational techniques to identify interactions among nitrogen, methanol, and titania under illumination. Electron paramagnetic resonance spectroscopy (EPR) allowed us to observe the formation of carbon radicals upon exposure to ultraviolet radiation. These carbon radicals are observed to transform into diazo- and nitrogen-centered radicals (e.g., CHxN2• and CHxNHy•) during photoreaction in nitrogen environment. In situ infrared (IR) spectroscopy under the same conditions revealed C-N stretching on titania. Furthermore, density functional theory (DFT) calculations revealed that nitrogen adsorption and the thermodynamic barrier to photocatalytic nitrogen fixation are significantly more favorable in the presence of hydroxymethyl or surface carbon. These results provide compelling evidence that carbon radicals formed from the photooxidation of hydrocarbons interact with dinitrogen and suggest that the role of carbon-based "hole scavengers" and the inertness of nitrogen atmospheres should be reevaluated in the field of photocatalysis.
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Affiliation(s)
- Po-Wei Huang
- School
of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Nianhan Tian
- School
of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Tijana Rajh
- School
of Molecular Science, Arizona State University, Tempe, Arizona 85281, United States
- Center
of Nanoscale Materials, Argonne National Laboratory, Woodridge, Illinois 60517, United States
| | - Yu-Hsuan Liu
- School
of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Giada Innocenti
- School
of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Carsten Sievers
- School
of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Andrew J. Medford
- School
of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Marta C. Hatzell
- School
of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- George
W .Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
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5
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Tian N, Comer BM, Medford AJ. Screening and Discovery of Metal Compound Active Sites for Strong and Selective Adsorption of N 2 in Air. ChemSusChem 2023; 16:e202300948. [PMID: 37890028 DOI: 10.1002/cssc.202300948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 10/26/2023] [Accepted: 10/27/2023] [Indexed: 10/29/2023]
Abstract
Photocatalytic nitrogen fixation has the potential to provide a greener route for producing nitrogen-based fertilizers under ambient conditions. Computational screening is a promising route to discover new materials for the nitrogen fixation process, but requires identifying "descriptors" that can be efficiently computed. In this work, we argue that selectivity toward the adsorption of molecular nitrogen and oxygen can act as a key descriptor. A catalyst that can selectively adsorb nitrogen and resist poisoning of oxygen and other molecules present in air has the potential to facilitate the nitrogen fixation process under ambient conditions. We provide a framework for active site screening based on multifidelity density functional theory (DFT) calculations for a range of metal oxides, oxyborides, and oxyphosphides. The screening methodology consists of initial low-fidelity fixed geometry calculations and a second screening in which more expensive geometry optimizations were performed. The approach identifies promising active sites on several TiO2 polymorph surfaces and a VBO4 surface, and the full nitrogen reduction pathway is studied with the BEEF-vdW and HSE06 functionals on two active sites. The findings suggest that metastable TiO2 polymorphs may play a role in photocatalytic nitrogen fixation, and that VBO4 may be an interesting material for further studies.
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Affiliation(s)
- Nianhan Tian
- Georgia Institute of Technology, 311 Ferst Dr NW, Atlanta, GA, 30332, United States
| | - Benjamin M Comer
- SUNCAT Center for Interface Science and Catalysis 443 Via Ortega, Stanford, CA 94305 United States, SLAC National Accelerator Laboratory 2575 Sand Hill Road, Mail Stop 31, Menlo Park, California, 94025, United States
- Now at Shell Global Solutions (United States) Inc, Houston, TX, United States
| | - Andrew J Medford
- Georgia Institute of Technology, 311 Ferst Dr NW, Atlanta, GA, 30332, United States
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6
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Kreitz B, Lott P, Studt F, Medford AJ, Deutschmann O, Goldsmith CF. Automated Generation of Microkinetics for Heterogeneously Catalyzed Reactions Considering Correlated Uncertainties. Angew Chem Int Ed Engl 2023; 62:e202306514. [PMID: 37505449 DOI: 10.1002/anie.202306514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 07/06/2023] [Accepted: 07/26/2023] [Indexed: 07/29/2023]
Abstract
The study presents an ab-initio based framework for the automated construction of microkinetic mechanisms considering correlated uncertainties in all energetic parameters and estimation routines. 2000 unique microkinetic models were generated within the uncertainty space of the BEEF-vdW functional for the oxidation reactions of representative exhaust gas emissions from stoichiometric combustion engines over Pt(111) and compared to experiments through multiscale modeling. The ensemble of simulations stresses the importance of considering uncertainties. Within this set of first-principles-based models, it is possible to identify a microkinetic mechanism that agrees with experimental data. This mechanism can be traced back to a single exchange-correlation functional, and it suggests that Pt(111) could be the active site for the oxidation of light hydrocarbons. The study provides a universal framework for the automated construction of reaction mechanisms with correlated uncertainty quantification, enabling a DFT-constrained microkinetic model optimization for other heterogeneously catalyzed systems.
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Affiliation(s)
- Bjarne Kreitz
- School of Engineering, Brown University, 184 Hope Street, Providence, RI, 02912, USA
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, Engesserstr. 20, 76128, Karlsruhe, Germany
| | - Patrick Lott
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, Engesserstr. 20, 76128, Karlsruhe, Germany
| | - Felix Studt
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, Engesserstr. 20, 76128, Karlsruhe, Germany
- Institute of Catalysis Research and Technology, Karlsruhe Institute of Technology, 76344, Eggenstein-Leopoldshafen, Germany
| | - Andrew J Medford
- School of Chemical and Biomolecular Engineering, Atlanta, GA, 30318, USA
| | - Olaf Deutschmann
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, Engesserstr. 20, 76128, Karlsruhe, Germany
| | - C Franklin Goldsmith
- School of Engineering, Brown University, 184 Hope Street, Providence, RI, 02912, USA
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7
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Hu Y, Musielewicz J, Ulissi ZW, Medford AJ. Robust and scalable uncertainty estimation with conformal prediction for machine-learned interatomic potentials. Mach Learn : Sci Technol 2022. [DOI: 10.1088/2632-2153/aca7b1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
Abstract
Uncertainty quantification (UQ) is important to machine learning (ML) force fields to assess the level of confidence during prediction, as ML models are not inherently physical and can therefore yield catastrophically incorrect predictions. Established a-posteriori UQ methods, including ensemble methods, the dropout method, the delta method, and various heuristic distance metrics, have limitations such as being computationally challenging for large models due to model re-training. In addition, the uncertainty estimates are often not rigorously calibrated. In this work, we propose combining the distribution-free UQ method, known as conformal prediction (CP), with the distances in the neural network’s latent space to estimate the uncertainty of energies predicted by neural network force fields. We evaluate this method (CP+latent) along with other UQ methods on two essential aspects, calibration, and sharpness, and find this method to be both calibrated and sharp under the assumption of independent and identically-distributed (i.i.d.) data. We show that the method is relatively insensitive to hyperparameters selected, and test the limitations of the method when the i.i.d. assumption is violated. Finally, we demonstrate that this method can be readily applied to trained neural network force fields with traditional and graph neural network architectures to obtain estimates of uncertainty with low computational costs on a training dataset of 1 million images to showcase its scalability and portability. Incorporating the CP method with latent distances offers a calibrated, sharp and efficient strategy to estimate the uncertainty of neural network force fields. In addition, the CP approach can also function as a promising strategy for calibrating uncertainty estimated by other approaches.
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8
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Abstract
Machine-learning force fields have become increasingly popular because of their balance of accuracy and speed. However, a significant limitation is the use of element-specific features, leading to poor scalability with the number of elements. This work introduces the Gaussian multipole (GMP) featurization scheme that utilizes physically relevant multipole expansions of the electron density around atoms to yield feature vectors that interpolate between element types and have a fixed dimension regardless of the number of elements present. We combine GMP with neural networks and apply these models to the MD17 and QM9 data sets, revealing high computational efficiency, systematically improvable accuracy, and the ability to make reasonable predictions on elements not included in the training set. Finally, we test GMP-based models for the OCP data set, demonstrating comparable performance to graph-convolutional models. The results indicate that this featurization scheme fills a critical gap in the construction of efficient and transferable machine-learned force fields.
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Affiliation(s)
- Xiangyun Lei
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Andrew J Medford
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
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9
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Affiliation(s)
- Andrew J. Medford
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | | | - Karsten Wedel Jacobsen
- CAMD, Department of Physics, Technical University of Denmark, Kongens Lyngby DK-2800, Denmark
| | - Andrew A. Peterson
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
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10
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Choi S, Sholl DS, Medford AJ. Gaussian approximation of dispersion potentials for efficient featurization and machine-learning predictions of metal–organic frameworks. J Chem Phys 2022; 156:214108. [PMID: 35676126 DOI: 10.1063/5.0091405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Energy-related descriptors in machine learning are a promising strategy to predict adsorption properties of metal–organic frameworks (MOFs) in the low-pressure regime. Interactions between hosts and guests in these systems are typically expressed as a sum of dispersion and electrostatic potentials. The energy landscape of dispersion potentials plays a crucial role in defining Henry’s constants for simple probe molecules in MOFs. To incorporate more information about this energy landscape, we introduce the Gaussian-approximated Lennard-Jones (GALJ) potential, which fits pairwise Lennard-Jones potentials with multiple Gaussians by varying their heights and widths. The GALJ approach is capable of replicating information that can be obtained from the original LJ potentials and enables efficient development of Gaussian integral (GI) descriptors that account for spatial correlations in the dispersion energy environment. GI descriptors would be computationally inconvenient to compute using the usual direct evaluation of the dispersion potential energy surface. We show that these new GI descriptors lead to improvement in ML predictions of Henry’s constants for a diverse set of adsorbates in MOFs compared to previous approaches to this task.
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Affiliation(s)
- Sihoon Choi
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - David S. Sholl
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
- Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, USA
| | - Andrew J. Medford
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
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11
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Yonge A, Kunz MR, Gusmão GS, Fang Z, Batchu R, Fushimi R, Medford AJ. Quantifying the impact of temporal analysis of products reactor initial state uncertainties on kinetic parameters. AIChE J 2022. [DOI: 10.1002/aic.17776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Adam Yonge
- College of Engineering Georgia Institute of Technology Atlanta GA
| | - M. Ross Kunz
- Department of Biological and Chemical Processing Idaho National Laboratory Idaho Falls ID
| | | | - Zongtang Fang
- Department of Biological and Chemical Processing Idaho National Laboratory Idaho Falls ID
| | - Rakesh Batchu
- Department of Biological and Chemical Processing Idaho National Laboratory Idaho Falls ID
| | - Rebecca Fushimi
- Department of Biological and Chemical Processing Idaho National Laboratory Idaho Falls ID
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12
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13
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Rasmussen MJ, Najmi S, Innocenti G, Medford AJ, Sievers C, Will Medlin J. Supported Molybdenum Oxides for the Aldol Condensation Reaction of Acetaldehyde. J Catal 2022. [DOI: 10.1016/j.jcat.2022.03.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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14
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Kunz MR, Yonge A, He X, Batchu R, Fang Z, Wang Y, Yablonsky GS, Medford AJ, Fushimi RR. Internal Calibration of Transient Kinetic Data via Machine Learning. Catal Today 2022. [DOI: 10.1016/j.cattod.2022.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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15
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Rose C, Medford AJ, Goldsmith CF, Vegge T, Weitz JS, Peterson AA. Heterogeneity in susceptibility dictates the order of epidemic models. J Theor Biol 2021; 528:110839. [PMID: 34314731 DOI: 10.1016/j.jtbi.2021.110839] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 07/16/2021] [Accepted: 07/18/2021] [Indexed: 12/21/2022]
Abstract
The fundamental models of epidemiology describe the progression of an infectious disease through a population using compartmentalized differential equations, but typically do not incorporate population-level heterogeneity in infection susceptibility. Here we combine a generalized analytical framework of contagion with computational models of epidemic dynamics to show that variation strongly influences the rate of infection, while the infection process simultaneously sculpts the susceptibility distribution. These joint dynamics influence the force of infection and are, in turn, influenced by the shape of the initial variability. We find that certain susceptibility distributions (the exponential and the gamma) are unchanged through the course of the outbreak, and lead naturally to power-law behavior in the force of infection; other distributions are often sculpted towards these "eigen-distributions" through the process of contagion. The power-law behavior fundamentally alters predictions of the long-term infection rate, and suggests that first-order epidemic models that are parameterized in the exponential-like phase may systematically and significantly over-estimate the final severity of the outbreak. In summary, our study suggests the need to examine the shape of susceptibility in natural populations as part of efforts to improve prediction models and to prioritize interventions that leverage heterogeneity to mitigate against spread.
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Affiliation(s)
- Christopher Rose
- School of Engineering, Brown University, Providence, Rhode Island 02912, USA
| | - Andrew J Medford
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | | | - Tejs Vegge
- Department of Energy Conversion and Storage, Technical University of Denmark, Lyngby 2800 Kgs., Denmark
| | - Joshua S Weitz
- School of Biological Sciences and School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
| | - Andrew A Peterson
- School of Engineering, Brown University, Providence, Rhode Island 02912, USA; Department of Energy Conversion and Storage, Technical University of Denmark, Lyngby 2800 Kgs., Denmark.
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16
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Comer BM, Lenk MH, Rajanala AP, Flynn EL, Medford AJ. Computational Study of Transition-Metal Substitutions in Rutile TiO2 (110) for Photoelectrocatalytic Ammonia Synthesis. Catal Letters 2021. [DOI: 10.1007/s10562-020-03348-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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17
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Nezam I, Zhou W, Gusmão GS, Realff MJ, Wang Y, Medford AJ, Jones CW. Direct aromatization of CO2 via combined CO2 hydrogenation and zeolite-based acid catalysis. J CO2 UTIL 2021. [DOI: 10.1016/j.jcou.2020.101405] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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18
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Innocenti G, Papadopoulos E, Fornasari G, Cavani F, Medford AJ, Sievers C. Continuous Liquid-Phase Upgrading of Dihydroxyacetone to Lactic Acid over Metal Phosphate Catalysts. ACS Catal 2020. [DOI: 10.1021/acscatal.0c03761] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Giada Innocenti
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst Dr., NW Atlanta, Georgia 30332, United States
- Dipartimento di Chimica Industriale “Toso-Montanari”, Universitá di Bologna, Viale del Risorgimento 4, Bologna 40136, Italy
- Research Unit of Bologna, Consorzio INSTM, Firenze 50121, Italy
| | - Eleni Papadopoulos
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst Dr., NW Atlanta, Georgia 30332, United States
| | - Giuseppe Fornasari
- Dipartimento di Chimica Industriale “Toso-Montanari”, Universitá di Bologna, Viale del Risorgimento 4, Bologna 40136, Italy
| | - Fabrizio Cavani
- Dipartimento di Chimica Industriale “Toso-Montanari”, Universitá di Bologna, Viale del Risorgimento 4, Bologna 40136, Italy
- Research Unit of Bologna, Consorzio INSTM, Firenze 50121, Italy
| | - Andrew J. Medford
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst Dr., NW Atlanta, Georgia 30332, United States
| | - Carsten Sievers
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst Dr., NW Atlanta, Georgia 30332, United States
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19
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Affiliation(s)
- Fuzhu Liu
- School of Chemical & Biomolecular Engineering Georgia Institute of Technology Atlanta Georgia 30332 United States
- School of Science Key Laboratory of Shaanxi for Advanced Materials and Mesoscopic Physics State Key Laboratory for Mechanical Behavior of Materials Xi'an Jiaotong University Xi'an 710049 People's Republic of China
| | - Shengchun Yang
- School of Science Key Laboratory of Shaanxi for Advanced Materials and Mesoscopic Physics State Key Laboratory for Mechanical Behavior of Materials Xi'an Jiaotong University Xi'an 710049 People's Republic of China
| | - Andrew J. Medford
- School of Chemical & Biomolecular Engineering Georgia Institute of Technology Atlanta Georgia 30332 United States
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20
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Affiliation(s)
- Chaoyi Chang
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Andrew J. Medford
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
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21
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Najmi S, Rasmussen M, Innocenti G, Chang C, Stavitski E, Bare SR, Medford AJ, Medlin JW, Sievers C. Pretreatment Effects on the Surface Chemistry of Small Oxygenates on Molybdenum Trioxide. ACS Catal 2020. [DOI: 10.1021/acscatal.0c01992] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Sean Najmi
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Mathew Rasmussen
- Department of Chemical and Biological Engineering, University of Colorado Boulder, JSCBB D125, 3415 Colorado Avenue, Boulder, Colorado 80303, United States
| | - Giada Innocenti
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Chaoyi Chang
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- Renewable Bioproducts Institute, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Eli Stavitski
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, New York 11973, United States
| | - Simon R. Bare
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States
| | - Andrew J. Medford
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- Renewable Bioproducts Institute, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - J. Will Medlin
- Department of Chemical and Biological Engineering, University of Colorado Boulder, JSCBB D125, 3415 Colorado Avenue, Boulder, Colorado 80303, United States
| | - Carsten Sievers
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- Renewable Bioproducts Institute, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
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22
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Affiliation(s)
- Jennifer N. Jocz
- School of Chemical & Biomolecular Engineering Georgia Institute of Technology 311 Ferst Dr. NW Atlanta GA-30332 USA
| | - Andrew J. Medford
- School of Chemical & Biomolecular Engineering Georgia Institute of Technology 311 Ferst Dr. NW Atlanta GA-30332 USA
| | - Carsten Sievers
- School of Chemical & Biomolecular Engineering Georgia Institute of Technology 311 Ferst Dr. NW Atlanta GA-30332 USA
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23
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Comer BM, Liu YH, Dixit MB, Hatzell KB, Ye Y, Crumlin EJ, Hatzell MC, Medford AJ. The Role of Adventitious Carbon in Photo-catalytic Nitrogen Fixation by Titania. J Am Chem Soc 2018; 140:15157-15160. [PMID: 30372055 DOI: 10.1021/jacs.8b08464] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Photo-catalytic fixation of nitrogen by titania catalysts at ambient conditions has been reported for decades, yet the active site capable of adsorbing an inert N2 molecule at ambient pressure and the mechanism of dissociating the strong dinitrogen triple bond at room temperature remain unknown. In this work in situ near-ambient-pressure X-ray photo-electron spectroscopy and density functional theory calculations are used to probe the active state of the rutile (110) surface. The experimental results indicate that photon-driven interaction of N2 and TiO2 is observed only if adventitious surface carbon is present, and computational results show a remarkably strong interaction between N2 and carbon substitution (C*) sites that act as surface-bound carbon radicals. A carbon-assisted nitrogen reduction mechanism is proposed and shown to be thermodynamically feasible. The findings provide a molecular-scale explanation for the long-standing mystery of photo-catalytic nitrogen fixation on titania. The results suggest that controlling and characterizing carbon-based active sites may provide a route to engineering more efficient photo(electro)-catalysts and improving experimental reproducibility.
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Affiliation(s)
- Benjamin M Comer
- School of Chemical & Biomolecular Engineering , Georgia Institute of Technology , Atlanta , Georgia 30318 , United States
| | - Yu-Hsuan Liu
- School of Civil and Environmental Engineering , Georgia Institute of Technology , Atlanta , Georgia 30313 , United States
| | - Marm B Dixit
- Department of Mechanical Engineering , Vanderbilt University , Nashville , Tennessee 37235 , United States
| | - Kelsey B Hatzell
- Department of Mechanical Engineering , Vanderbilt University , Nashville , Tennessee 37235 , United States
| | - Yifan Ye
- Advanced Light Source , Lawrence Berkeley National Laboratory , Berkeley , California 94720 , United States
| | - Ethan J Crumlin
- Advanced Light Source , Lawrence Berkeley National Laboratory , Berkeley , California 94720 , United States
| | - Marta C Hatzell
- George W. Woodruff School of Mechanical Engineering , Georgia Institute of Technology , Atlanta , Georgia 30313 , United States
| | - Andrew J Medford
- School of Chemical & Biomolecular Engineering , Georgia Institute of Technology , Atlanta , Georgia 30318 , United States
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24
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Duyar MS, Tsai C, Snider JL, Singh JA, Gallo A, Yoo JS, Medford AJ, Abild‐Pedersen F, Studt F, Kibsgaard J, Bent SF, Nørskov JK, Jaramillo TF. A Highly Active Molybdenum Phosphide Catalyst for Methanol Synthesis from CO and CO
2. Angew Chem Int Ed Engl 2018. [DOI: 10.1002/ange.201806583] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Melis S. Duyar
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Charlie Tsai
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Jonathan L. Snider
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Joseph A. Singh
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Alessandro Gallo
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Jong Suk Yoo
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Andrew J. Medford
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Frank Abild‐Pedersen
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Felix Studt
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Jakob Kibsgaard
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Stacey F. Bent
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Jens K. Nørskov
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Thomas F. Jaramillo
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
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25
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Duyar MS, Tsai C, Snider JL, Singh JA, Gallo A, Yoo JS, Medford AJ, Abild‐Pedersen F, Studt F, Kibsgaard J, Bent SF, Nørskov JK, Jaramillo TF. A Highly Active Molybdenum Phosphide Catalyst for Methanol Synthesis from CO and CO
2. Angew Chem Int Ed Engl 2018; 57:15045-15050. [PMID: 30134041 DOI: 10.1002/anie.201806583] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Indexed: 11/09/2022]
Affiliation(s)
- Melis S. Duyar
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Charlie Tsai
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Jonathan L. Snider
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Joseph A. Singh
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Alessandro Gallo
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Jong Suk Yoo
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Andrew J. Medford
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Frank Abild‐Pedersen
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Felix Studt
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Jakob Kibsgaard
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Stacey F. Bent
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Jens K. Nørskov
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
| | - Thomas F. Jaramillo
- SUNCAT Center for Interface Science and Catalysis Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory Menlo Park CA 94025 USA
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26
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Affiliation(s)
- Andrew J. Medford
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30318 United States
| | - M. Ross Kunz
- Biological and Chemical Processing Department, Energy and Environmental Science and Technology, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, Idaho 83415, United States
| | - Sarah M. Ewing
- Biological and Chemical Processing Department, Energy and Environmental Science and Technology, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, Idaho 83415, United States
| | - Tammie Borders
- Biological and Chemical Processing Department, Energy and Environmental Science and Technology, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, Idaho 83415, United States
| | - Rebecca Fushimi
- Biological and Chemical Processing Department, Energy and Environmental Science and Technology, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, Idaho 83415, United States
- Center for Advanced Energy Studies, 995 University Boulevard, Idaho Falls, Idaho 83401, United States
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27
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Schumann J, Medford AJ, Yoo JS, Zhao ZJ, Bothra P, Cao A, Studt F, Abild-Pedersen F, Nørskov JK. Selectivity of Synthesis Gas Conversion to C2+ Oxygenates on fcc(111) Transition-Metal Surfaces. ACS Catal 2018. [DOI: 10.1021/acscatal.8b00201] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Julia Schumann
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States
| | - Andrew J. Medford
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States
| | - Jong Suk Yoo
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
| | - Zhi-Jian Zhao
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States
| | - Pallavi Bothra
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States
| | - Ang Cao
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
| | - Felix Studt
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States
| | - Frank Abild-Pedersen
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States
| | - Jens K. Nørskov
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States
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28
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Andersen M, Medford AJ, Nørskov JK, Reuter K. Scaling-Relation-Based Analysis of Bifunctional Catalysis: The Case for Homogeneous Bimetallic Alloys. ACS Catal 2017. [DOI: 10.1021/acscatal.7b00482] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Mie Andersen
- Chair
for Theoretical Chemistry and Catalysis Research Center, Technische Universität München, Lichtenbergstraße 4, D-85747 Garching, Germany
| | - Andrew J. Medford
- SUNCAT
Center for Interface Science and Catalysis, Department of Chemical
Engineering, Stanford University, Stanford, California 94305, United States
- SUNCAT
Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo
Park, California 94025, United States
| | - Jens K. Nørskov
- SUNCAT
Center for Interface Science and Catalysis, Department of Chemical
Engineering, Stanford University, Stanford, California 94305, United States
- SUNCAT
Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo
Park, California 94025, United States
| | - Karsten Reuter
- Chair
for Theoretical Chemistry and Catalysis Research Center, Technische Universität München, Lichtenbergstraße 4, D-85747 Garching, Germany
- SUNCAT
Center for Interface Science and Catalysis, Department of Chemical
Engineering, Stanford University, Stanford, California 94305, United States
- SUNCAT
Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo
Park, California 94025, United States
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29
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Affiliation(s)
- Andrew J. Medford
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Marta C. Hatzell
- George
W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
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30
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Ulissi ZW, Medford AJ, Bligaard T, Nørskov JK. To address surface reaction network complexity using scaling relations machine learning and DFT calculations. Nat Commun 2017; 8:14621. [PMID: 28262694 PMCID: PMC5343483 DOI: 10.1038/ncomms14621] [Citation(s) in RCA: 252] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Accepted: 01/03/2017] [Indexed: 12/27/2022] Open
Abstract
Surface reaction networks involving hydrocarbons exhibit enormous complexity with thousands of species and reactions for all but the very simplest of chemistries. We present a framework for optimization under uncertainty for heterogeneous catalysis reaction networks using surrogate models that are trained on the fly. The surrogate model is constructed by teaching a Gaussian process adsorption energies based on group additivity fingerprints, combined with transition-state scaling relations and a simple classifier for determining the rate-limiting step. The surrogate model is iteratively used to predict the most important reaction step to be calculated explicitly with computationally demanding electronic structure theory. Applying these methods to the reaction of syngas on rhodium(111), we identify the most likely reaction mechanism. Propagating uncertainty throughout this process yields the likelihood that the final mechanism is complete given measurements on only a subset of the entire network and uncertainty in the underlying density functional theory calculations.
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Affiliation(s)
- Zachary W. Ulissi
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, California 94305, USA
| | - Andrew J. Medford
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Thomas Bligaard
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - Jens K. Nørskov
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, California 94305, USA
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31
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Affiliation(s)
- Mie Andersen
- Chair for Theoretical Chemistry and Catalysis Research Center; Technische Universität München; Lichtenbergstrasse 4 85747 Garching Deutschland
| | - Andrew J. Medford
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering; Stanford University; Stanford CA 94305 USA
- SUNCAT Center for Interface Science and Catalysis; SLAC National Accelerator Laboratory; 2575 Sand Hill Road Menlo Park CA 94025 USA
| | - Jens K. Nørskov
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering; Stanford University; Stanford CA 94305 USA
- SUNCAT Center for Interface Science and Catalysis; SLAC National Accelerator Laboratory; 2575 Sand Hill Road Menlo Park CA 94025 USA
| | - Karsten Reuter
- Chair for Theoretical Chemistry and Catalysis Research Center; Technische Universität München; Lichtenbergstrasse 4 85747 Garching Deutschland
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering; Stanford University; Stanford CA 94305 USA
- SUNCAT Center for Interface Science and Catalysis; SLAC National Accelerator Laboratory; 2575 Sand Hill Road Menlo Park CA 94025 USA
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32
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Abstract
Bifunctional coupling of two different catalytic site types has often been invoked to explain experimentally observed enhanced catalytic activities. We scrutinize such claims with generic scaling-relation-based microkinetic models that allow exploration of the theoretical limits for such a bifunctional gain for several model reactions. For sites at transition-metal surfaces, the universality of the scaling relations between adsorption energies largely prevents any improvements through bifunctionality. Only the consideration of systems that involve the combination of different materials, such as metal particles on oxide supports, offers hope for significant bifunctional gains.
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Affiliation(s)
- Mie Andersen
- Chair for Theoretical Chemistry and Catalysis Research Center, Technische Universität München, Lichtenbergstrasse 4, 85747, Garching, Deutschland
| | - Andrew J Medford
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, CA, 94305, USA.,SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - Jens K Nørskov
- SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, CA, 94305, USA.,SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - Karsten Reuter
- Chair for Theoretical Chemistry and Catalysis Research Center, Technische Universität München, Lichtenbergstrasse 4, 85747, Garching, Deutschland. .,SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, CA, 94305, USA. .,SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA.
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33
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Yang N, Medford AJ, Liu X, Studt F, Bligaard T, Bent SF, Nørskov JK. Intrinsic Selectivity and Structure Sensitivity of Rhodium Catalysts for C2+ Oxygenate Production. J Am Chem Soc 2016; 138:3705-14. [PMID: 26958997 DOI: 10.1021/jacs.5b12087] [Citation(s) in RCA: 148] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Nuoya Yang
- Department
of Materials Science and Engineering, Stanford University, 496 Lomita
Mall, Stanford, California 94305, United States
| | - Andrew J. Medford
- Department
of Chemical Engineering, Stanford University, 443 Via Ortega, Stanford, California 94305, United States
- SLAC
National Accelerator Laboratory, SUNCAT Center for Interface Science and Catalysis, 2575 Sand Hill Road, Menlo
Park, California 94025, United States
| | - Xinyan Liu
- Department
of Chemical Engineering, Stanford University, 443 Via Ortega, Stanford, California 94305, United States
- SLAC
National Accelerator Laboratory, SUNCAT Center for Interface Science and Catalysis, 2575 Sand Hill Road, Menlo
Park, California 94025, United States
| | - Felix Studt
- Department
of Chemical Engineering, Stanford University, 443 Via Ortega, Stanford, California 94305, United States
- SLAC
National Accelerator Laboratory, SUNCAT Center for Interface Science and Catalysis, 2575 Sand Hill Road, Menlo
Park, California 94025, United States
| | - Thomas Bligaard
- Department
of Chemical Engineering, Stanford University, 443 Via Ortega, Stanford, California 94305, United States
- SLAC
National Accelerator Laboratory, SUNCAT Center for Interface Science and Catalysis, 2575 Sand Hill Road, Menlo
Park, California 94025, United States
| | - Stacey F. Bent
- Department
of Chemical Engineering, Stanford University, 443 Via Ortega, Stanford, California 94305, United States
| | - Jens K. Nørskov
- Department
of Chemical Engineering, Stanford University, 443 Via Ortega, Stanford, California 94305, United States
- SLAC
National Accelerator Laboratory, SUNCAT Center for Interface Science and Catalysis, 2575 Sand Hill Road, Menlo
Park, California 94025, United States
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34
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Medford AJ, Vojvodic A, Hummelshøj JS, Voss J, Abild-Pedersen F, Studt F, Bligaard T, Nilsson A, Nørskov JK. From the Sabatier principle to a predictive theory of transition-metal heterogeneous catalysis. J Catal 2015. [DOI: 10.1016/j.jcat.2014.12.033] [Citation(s) in RCA: 840] [Impact Index Per Article: 93.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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35
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Medford AJ, Wellendorff J, Vojvodic A, Studt F, Abild-Pedersen F, Jacobsen KW, Bligaard T, Nørskov JK. Catalysis. Assessing the reliability of calculated catalytic ammonia synthesis rates. Science 2014; 345:197-200. [PMID: 25013071 DOI: 10.1126/science.1253486] [Citation(s) in RCA: 201] [Impact Index Per Article: 20.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
We introduce a general method for estimating the uncertainty in calculated materials properties based on density functional theory calculations. We illustrate the approach for a calculation of the catalytic rate of ammonia synthesis over a range of transition-metal catalysts. The correlation between errors in density functional theory calculations is shown to play an important role in reducing the predicted error on calculated rates. Uncertainties depend strongly on reaction conditions and catalyst material, and the relative rates between different catalysts are considerably better described than the absolute rates. We introduce an approach for incorporating uncertainty when searching for improved catalysts by evaluating the probability that a given catalyst is better than a known standard.
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Affiliation(s)
- Andrew J Medford
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA. SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Jess Wellendorff
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA. SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Aleksandra Vojvodic
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
| | - Felix Studt
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
| | - Frank Abild-Pedersen
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
| | - Karsten W Jacobsen
- Center for Atomic-scale Materials Design (CAMD), Department of Physics, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Thomas Bligaard
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
| | - Jens K Nørskov
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA. SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA.
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36
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Brogaard RY, Henry R, Schuurman Y, Medford AJ, Moses PG, Beato P, Svelle S, Nørskov JK, Olsbye U. Methanol-to-hydrocarbons conversion: The alkene methylation pathway. J Catal 2014. [DOI: 10.1016/j.jcat.2014.04.006] [Citation(s) in RCA: 100] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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37
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38
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Medford AJ, Sehested J, Rossmeisl J, Chorkendorff I, Studt F, Nørskov JK, Moses PG. Thermochemistry and micro-kinetic analysis of methanol synthesis on ZnO (0 0 0 1). J Catal 2014. [DOI: 10.1016/j.jcat.2013.10.015] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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39
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Medford AJ, Lausche AC, Abild-Pedersen F, Temel B, Schjødt NC, Nørskov JK, Studt F. Activity and Selectivity Trends in Synthesis Gas Conversion to Higher Alcohols. Top Catal 2013. [DOI: 10.1007/s11244-013-0169-0] [Citation(s) in RCA: 155] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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40
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Peterson AA, Grabow LC, Brennan TP, Shong B, Ooi C, Wu DM, Li CW, Kushwaha A, Medford AJ, Mbuga F, Li L, Nørskov JK. Finite-Size Effects in O and CO Adsorption for the Late Transition Metals. Top Catal 2012. [DOI: 10.1007/s11244-012-9908-x] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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41
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Medford AJ, Vojvodic A, Studt F, Abild-Pedersen F, Nørskov JK. Elementary steps of syngas reactions on Mo2C(001): Adsorption thermochemistry and bond dissociation. J Catal 2012. [DOI: 10.1016/j.jcat.2012.03.007] [Citation(s) in RCA: 82] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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42
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Alstrup J, Jørgensen M, Medford AJ, Krebs FC. Ultra fast and parsimonious materials screening for polymer solar cells using differentially pumped slot-die coating. ACS Appl Mater Interfaces 2010; 2:2819-2827. [PMID: 20879717 DOI: 10.1021/am100505e] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
We present a technique that enables the probing of the entire parameter space for each parameter with good statistics through a simple roll-to-roll processing method where gradients of donor, acceptor, and solvent are applied by differentially pumped slot-die coating. We thus demonstrate how the optimum donor-acceptor ratio and device film thickness can be determined with improved accuracy by varying the composition in small steps. We give as an example P3HT-PCBM devices and vary the composition between P3HT and PCBM in steps of 0.5-1% giving 100-200 individual solar cells. The coating experiment itself takes less than 4-8 min and requires 15-30 mg each of donor and acceptor material. The optimum donor-acceptor composition of P3HT and PCBM was found to be a broad maximum centered on a 1:1 ratio. We demonstrate how the optimal thickness of the active layer can be found by the same method and materials usage by variation of the layer thickness in small steps of 1.5-4 nm. Contrary to expectation we did not find oscillatory variation of the device performance with device thickness because of optical interference. We ascribe this to the nature of the solar cell type explored in this example that employs nonreflective or semitransparent printed electrodes. We further found that very thick active layers on the order of 1 μm can be prepared without loss in performance and estimate the active layer thickness could easily approach 4-5 μm while maintaining photovoltaic properties.
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Affiliation(s)
- Jan Alstrup
- Risø National Laboratory for Sustainable Energy, Technical University of Denmark Frederiksborgvej 399, DK-4000 Roskilde, Denmark
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Medford AJ, Lilliedal MR, Jørgensen M, Aarø D, Pakalski H, Fyenbo J, Krebs FC. Grid-connected polymer solar panels: initial considerations of cost, lifetime, and practicality. Opt Express 2010; 18 Suppl 3:A272-A285. [PMID: 21165057 DOI: 10.1364/oe.18.00a272] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Large solar panels were constructed from polymer solar cell modules prepared using full roll-to-roll (R2R) manufacture based on the previously published ProcessOne. The individual flexible polymer solar modules comprising multiple serially connected single cell stripes were joined electrically and laminated between a 4 mm tempered glass window and black Tetlar foil using two sheets of 0.5 mm thick ethylene vinyl acetate (EVA). The panels produced up to 8 W with solar irradiance of ~960 Wm⁻², and had outer dimensions of 1 m x 1.7 m with active areas up to 9180 cm². Panels were mounted on a tracking station and their output was grid connected between testing. Several generations of polymer solar cells and panel constructions were tested in this context to optimize the production of polymer solar panels. Cells lacking a R2R barrier layer were found to degrade due to diffusion of oxygen after less than a month, while R2R encapsulated cells showed around 50% degradation after 6 months but suffered from poor performance due to de-lamination during panel production. A third generation of panels with various barrier layers was produced to optimize the choice of barrier foil and it was found that the inclusion of a thin protective foil between the cell and the barrier foil is critical. The findings provide a preliminary foundation for the production and optimization of large-area polymer solar panels and also enabled a cost analysis of solar panels based on polymer solar cells.
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Ji L, Lin Z, Guo B, Medford AJ, Zhang X. Assembly of Carbon-SnO2 Core-Sheath Composite Nanofibers for Superior Lithium Storage. Chemistry 2010; 16:11543-8. [PMID: 20827708 DOI: 10.1002/chem.201001564] [Citation(s) in RCA: 73] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2010] [Indexed: 11/10/2022]
Affiliation(s)
- Liwen Ji
- Fiber and Polymer Science Program, Department of Textile Engineering, Chemistry and Science, North Carolina State University, Raleigh, NC 27695-8301, USA
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Ji L, Lin Z, Medford AJ, Zhang X. In-Situ Encapsulation of Nickel Particles in Electrospun Carbon Nanofibers and the Resultant Electrochemical Performance. Chemistry 2009; 15:10718-22. [PMID: 19746369 DOI: 10.1002/chem.200902012] [Citation(s) in RCA: 75] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Liwen Ji
- Fiber and Polymer Science Program, Department of Textile Engineering, Chemistry and Science, North Carolina State University, Raleigh, NC 27695-8301, USA
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Ji L, Medford AJ, Zhang X. Fabrication of carbon fibers with nanoporous morphologies from electrospun polyacrylonitrile/poly(L-lactide) blends. ACTA ACUST UNITED AC 2009. [DOI: 10.1002/polb.21654] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Ji L, Jung KH, Medford AJ, Zhang X. Electrospun polyacrylonitrile fibers with dispersed Si nanoparticles and their electrochemical behaviors after carbonization. ACTA ACUST UNITED AC 2009. [DOI: 10.1039/b903165k] [Citation(s) in RCA: 92] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Ji L, Medford AJ, Zhang X. Porous carbon nanofibers loaded with manganese oxide particles: Formation mechanism and electrochemical performance as energy-storage materials. ACTA ACUST UNITED AC 2009. [DOI: 10.1039/b905755b] [Citation(s) in RCA: 103] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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