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Maciej Haranczyk

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Maciej Haranczyk
Staff Scientist
Phone: +1 510 486 7749

Biographical Sketch

Maciej Haranczyk is a Staff Scientist in the Computational Chemistry, Materials and Climate (CCMC) Group at Berkeley Lab. Dr. Haranczyk received a PhD and MS degrees in Chemistry from University of Gdansk, Poland. He spent his post-doctoral appointment as a 2008 Glenn T. Seaborg Fellow at Berkeley Lab. His research interests include development of methods, tools and approaches to enable efficient molecular and materials discovery.

Journal Articles

Richard L. Martin, Cory M. Simon, Berend Smit, Maciej Haranczyk, "In-silico design of porous polymer networks: high-throughput screening for methane storage materials", Journal of the American Chemical Society, March 10, 2014,

Porous polymer networks (PPNs) are a class of advanced porous materials that combine the advantages of cheap and stable polymers with the high surface areas and tunable chemistry of metal-organic frameworks. They are of particular interest for gas separation or storage applications, for instance as methane adsorbents for a vehicular natural gas tank or other portable applications.

Richard L. Martin, Maciej Haranczyk, "Construction and Characterization of Structure Models of Crystalline Porous Polymers", Crystal Growth & Design, March 6, 2014,

Metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) are examples of advanced porous polymeric materials that have emerged in recent years. Their crystalline structure and modular synthesis offer unmatched versatility in their design. By exchanging chemical building blocks, one can both explore the unlimited space of possible structural chemistry within an isoreticular (same crystal topology) series, as well as achieve a wide range of alternative topologies.

Lev Sarkisov, Richard L. Martin, Maciej Haranczyk, Berend Smit, "On the Flexibility of Metal-Organic Frameworks", Journal of the American Chemical Society, January 24, 2014,

Occasional, large amplitude flexibility in metal-organic frameworks (MOFs) is one of the most intriguing recent discoveries in chemistry and material science. Yet, there is at present no theoretical framework that permits the identification of flexible structures in the rapidly expanding universe of MOFs. Here, we propose a simple method to predict whether a MOF is flexible, based on treating it as a system of rigid elements, connected by hinges. This proposition is correct in application to MOFs based on rigid carboxylate linkers.

Cory M. Simon, Jihan Kim, Li-Chiang Lin, Richard L. Martin, Maciej Haranczyk, Berend Smit, "Optimizing nanoporous materials for gas storage", Physical Chemistry Chemical Physics, December 4, 2013,

Natural gas, mostly methane, is an attractive replacement of petroleum fuels for automotive vehicles because of its economic and environmental advantages. The technological obstacle to using methane as a vehicular fuel is its comparatively low volumetric energy density, necessitating densification strategies to yield reasonable driving ranges from a reasonably sized tank.

Maciej Haranczyk, Li-Chiang Lin, Kyuho Lee, Richard L. Martin, Jeffrey B. Neaton, Berend Smit, "Methane storage capabilities of diamond analogues", Physical Chemistry Chemical Physics, October 31, 2013,

Methane can be an alternative fuel for vehicular usage provided that new porous materials are developed for its efficient adsorption-based storage. Herein, we search for materials for this application within the family of diamond analogues. We used density functional theory to investigate structures in which tetrahedral C atoms of diamond are separated by-CC-or-BN-groups, as well as ones involving substitution of tetrahedral C atoms with Si and Ge atoms.

Richard L Martin, Mahdi Niknam Shahrak, Joseph A Swisher, Cory M Simon, Julian P Sculley, Hong-Cai Zhou, Berend Smit, Maciej Haranczyk, "Modeling Methane Adsorption in Interpenetrating Porous Polymer Networks", The Journal of Physical Chemistry C, September 19, 2013,

Porous polymer networks (PPNs) are a class of porous materials of particular interest in a variety of energy-related applications because of their stability, high surface areas, and gas uptake capacities. Computationally derived structures for five recently synthesized PPN frameworks, PPN-2,-3,-4,-5, and-6, were generated for various topologies, optimized using semiempirical electronic structure methods, and evaluated using classical grand-canonical Monte Carlo simulations.

Richard L. Martin, Maciej Haranczyk, "Insights into Multi-Objective Design of Metal–Organic Frameworks", Crystal Growth & Design, September 18, 2013,

Metal-organic framework (MOF) crystal topologies which permit the highest internal surface areas are identified by means of multiobjective optimization and abstract structure models. We demonstrate that MOF design efforts can be focused within five underlying nets to engineer distinct, Pareto-optimal compromises between high gravimetric and high volumetric surface area materials.

Marielle Pinheiro, Richard L. Martin, Chris H. Rycroft, Maciej Haranczyk, "High accuracy geometric analysis of crystalline porous materials", CrystEngComm, September 5, 2013,

A number of algorithms to analyze crystalline porous materials and their porosity employ the Voronoi tessellation, whereby the space in the material is divided into irregular polyhedral cells that can be analyzed to determine the pore topology and structure. However, the Voronoi tessellation is only appropriate when atoms all have equal radii, and the natural generalization to structures with unequal radii leads to cells with curved boundaries, which are computationally expensive to compute.

Marielle Pinheiro, Richard L. Martin, Chris H. Rycroft, Andrew Jones, Enrique Iglesia, Maciej Haranczyk, "Characterization and comparison of pore landscapes in crystalline porous materials", Journal of Molecular Graphics and Modelling, July 31, 2013,

Crystalline porous materials have many applications, including catalysis and separations. Identifying suitable materials for a given application can be achieved by screening material databases. Such a screening requires automated high-throughput analysis tools that characterize and represent pore landscapes with descriptors, which can be compared using similarity measures in order to select, group and classify materials. Here, we discuss algorithms for the calculation of two types of pore landscape descriptors.

Richard L. Martin, Maciej Haranczyk, "Optimization-Based Design of Metal-Organic Framework Materials", Journal of Chemical Theory and Computation, May 16, 2013,

Metal–organic frameworks (MOFs) are a class of porous materials constructed from metal or metal oxide building blocks connected by organic linkers. MOFs are highly tunable structures that can in theory be custom designed to meet the specific pore geometry and chemistry required for a given application such as methane storage or carbon capture. However, due to the sheer number of potential materials, identification of optimal MOF structures is a significant challenge.

Richard L. Martin, Li-Chiang Lin, Kuldeep Jariwala, Berend Smit, Maciej Haranczyk, "Mail-Order Metal–Organic Frameworks (MOFs): Designing Isoreticular MOF-5 Analogues Comprising Commercially Available Organic Molecules", The Journal of Physical Chemistry C, April 17, 2013,

Metal–organic frameworks (MOFs), a class of porous materials, are of particular interest in gas storage and separation applications due largely to their high internal surface areas and tunable structures. MOF-5 is perhaps the archetypal MOF; in particular, many isoreticular analogues of MOF-5 have been synthesized, comprising alternative dicarboxylic acid ligands. In this contribution we introduce a new set of hypothesized MOF-5 analogues, constructed from commercially available organic molecules.

Richard L. Martin, Maciej Haranczyk, "Exploring frontiers of high surface area metal-organic frameworks", Chemical Science, February 6, 2013, 4:1781-1785,

Metal–organic frameworks (MOFs) have enjoyed considerable interest due to their high internal surface areas as well as tunable pore geometry and chemistry. However, design of optimal MOFs is a great challenge due to the significant number of possible structures. In this work, we present a strategy to rapidly explore the frontiers of these high surface area materials. Here, organic ligands are abstracted by geometrical (alchemical) building blocks, and an optimization of their defining geometrical parameters is performed to identify shapes of ligands which maximize gravimetric surface area of the resulting MOFs. A strength of our approach is that the space of ligands to be explored can be rigorously bounded, allowing discovery of the optimum ligand shape within any criteria, conforming to synthetic requirements or arbitrary exploratory limits. By modifying these bounds, we can project to what extent achievable surface area increases when moving beyond the present limits of organic synthesis. Projecting optimal ligand shapes onto real chemical species, we achieve blueprints for MOFs of various topologies that are predicted to achieve up to 70% higher surface area than the current benchmark materials.

Richard L. Martin, Thomas F. Willems, Li-Chiang Lin, Jihan Kim, Joseph A. Swisher, Berend Smit & Maciej Haranczyk, "Similarity-Driven Discovery of Zeolite Materials for Adsorption-Based Separations", ChemPhysChem, August 22, 2012, 13:3595-3597,

Crystalline porous materials can be exploited in many applications. Discovery of materials with optimum adsorption properties typically involves expensive brute-force characterization of large sets of materials. An alternative approach based on similarity searching that enables discovery of materials with optimum adsorption for CO2 and other molecules at a fraction of the cost of brute-force characterization is demonstrated.

This work was featured on the front cover of the journal, available here: http://onlinelibrary.wiley.com/doi/10.1002/cphc.201290074/abstract

Jihan Kim, Li-Chiang Lin, Richard L. Martin, Joseph A. Swisher, Maciej Haranczyk & Berend Smit, "Large-Scale Computational Screening of Zeolites for Ethane/Ethene Separation", Langmuir, July 11, 2012, 28:11914–1191,

Large-scale computational screening of thirty thousand zeolite structures was conducted to find optimal structures for separation of ethane/ethene mixtures. Efficient grand canonical Monte Carlo (GCMC) simulations were performed with graphics processing units (GPUs) to obtain pure component adsorption isotherms for both ethane and ethene. We have utilized the ideal adsorbed solution theory (IAST) to obtain the mixture isotherms, which were used to evaluate the performance of each zeolite structure based on its working capacity and selectivity. In our analysis, we have determined that specific arrangements of zeolite framework atoms create sites for the preferential adsorption of ethane over ethene. The majority of optimum separation materials can be identified by utilizing this knowledge and screening structures for the presence of this feature will enable the efficient selection of promising candidate materials for ethane/ethene separation prior to performing molecular simulations.

Li-Chiang Lin, Adam H. Berger, Richard L. Martin, Jihan Kim, Joseph A. Swisher, Kuldeep Jariwala, Chris H. Rycroft, Abhoyjit S. Bhown, Michael W. Deem, Maciej Haranczyk & Berend Smit, "In Silico Screening of Carbon Capture Materials", Nature Materials, May 27, 2012, 11:633–641,

One of the main bottlenecks to deploying large-scale carbon dioxide capture and storage (CCS) in power plants is the energy required to separate the CO2 from flue gas. For example, near-term CCS technology applied to coal-fired power plants is projected to reduce the net output of the plant by some 30% and to increase the cost of electricity by 60–80%. Developing capture materials and processes that reduce the parasitic energy imposed by CCS is therefore an important area of research. We have developed a computational approach to rank adsorbents for their performance in CCS. Using this analysis, we have screened hundreds of thousands of zeolite and zeolitic imidazolate framework structures and identified many different structures that have the potential to reduce the parasitic energy of CCS by 30–40% compared with near-term technologies.

Jihan Kim, Richard L. Martin, Oliver Rübel, Maciej Haranczyk & Berend Smit, "High-throughput Characterization of Porous Materials Using Graphics Processing Units", Journal of Chemical Theory and Computation, March 16, 2012, 8:1684–1693, LBNL 5409E, doi: 10.1021/ct200787v

We have developed a high-throughput graphics processing unit (GPU) code that can characterize a large database of crystalline porous materials. In our algorithm, the GPU is utilized to accelerate energy grid calculations, where the grid values represent interactions (i.e., Lennard-Jones + Coulomb potentials) between gas molecules (i.e., CH4 and CO2) and materials’ framework atoms. Using a parallel flood fill central processing unit (CPU) algorithm, inaccessible regions inside the framework structures are identified and blocked, based on their energy profiles. Finally, we compute the Henry coefficients and heats of adsorption through statistical Widom insertion Monte Carlo moves in the domain restricted to the accessible space. The code offers significant speedup over a single core CPU code and allows us to characterize a set of porous materials at least an order of magnitude larger than those considered in earlier studies. For structures selected from such a prescreening algorithm, full adsorption isotherms can be calculated by conducting multiple Grand Canonical Monte Carlo (GCMC) simulations concurrently within the GPU.

Richard L. Martin, Prabhat, David D. Donofrio, James A. Sethian & Maciej Haranczyk, "Accelerating Analysis of void spaces in porous materials on multicore and GPU platforms", International Journal of High Performance Computing Applications, February 5, 2012, 26:347-357,

Developing computational tools that enable discovery of new materials for energy-related applications is a challenge. Crystalline porous materials are a promising class of materials that can be used for oil refinement, hydrogen or methane storage as well as carbon dioxide capture. Selecting optimal materials for these important applications requires analysis and screening of millions of potential candidates. Recently, we proposed an automatic approach based on the Fast Marching Method (FMM) for performing analysis of void space inside materials, a critical step preceding expensive molecular dynamics simulations. This breakthrough enables unsupervised, high-throughput characterization of large material databases. The algorithm has three steps: (1) calculation of the cost-grid which represents the structure and encodes the occupiable positions within the void space; (2) using FMM to segment out patches of the void space in the grid of (1), and find how they are connected to form either periodic channels or inaccessible pockets; and (3) generating blocking spheres that encapsulate the discovered inaccessible pockets and are used in proceeding molecular simulations. In this work, we expand upon our original approach through (A) replacement of the FMM-based approach with a more computationally efficient flood fill algorithm; and (B) parallelization of all steps in the algorithm, including a GPU implementation of the most computationally expensive step, the cost-grid generation. We report the acceleration achievable in each step and in the complete application, and discuss the implications for high-throughput material screening.

Thomas F. Willems, Chris H. Rycroft, Michaeel Kazi, Juan C. Meza, Maciej Haranczyk, "Algorithms and tools for high-throughput geometry-based analysis of crystalline porous materials", Microporous and Mesoporous Materials, 2012, 149:134--141, doi: 10.1016/j.micromeso.2011.08.020

Richard L. Martin, Berend Smit & Maciej Haranczyk, "Addressing Challenges of Identifying Geometrically Diverse Sets of Crystalline Porous Materials", Journal of Chemical Information and Modeling, November 18, 2011, 52:308–318,

Crystalline porous materials have a variety of uses, such as for catalysis and separations. Identifying suitable materials for a given application can, in principle, be done by screening material databases. Such a screening requires automated high-throughput analysis tools that calculate topological and geometrical parameters describing pores. These descriptors can be used to compare, select, group, and classify materials. Here, we present a descriptor that captures shape and geometry characteristics of pores. Together with proposed similarity measures, it can be used to perform diversity selection on a set of porous materials. Our representations are histogram encodings of the probe-accessible fragment of the Voronoi network representing the void space of a material. We discuss and demonstrate the application of our approach on the International Zeolite Association (IZA) database of zeolite frameworks and the Deem database of hypothetical zeolites, as well as zeolitic imidazolate frameworks constructed from IZA zeolite structures. The diverse structures retrieved by our method are complementary to those expected by emphasizing diversity in existing one-dimensional descriptors, e.g., surface area, and similar to those obtainable by a (subjective) manual selection based on materials’ visual representations. Our technique allows for reduction of large sets of structures and thus enables the material researcher to focus efforts on maximally dissimilar structures.

Beketayev, K., Weber, G.H., Haranczyk, M., Bremer, P.-T., Hlawitschka, M., and Hamann, B., "Topology-based Visualization of Transformation Pathways in Complex Chemical Systems", Computer Graphics Forum (Special Issue, Proc. Eurographics / IEEE Symposium on Visualization), June 2011, 663-672, LBNL 5242E,

Maciej Haranczyk, Richard L. Martin, Prabhat, James A. Sethian & E. Wes Bethel, "Computational Approaches for the High-Throughput Analysis of Porous materials for Energy related applications", Scientific Discovery through Advanced Computing 2011, 2011,

Jihan Kim, Alice Koniges, Richard L. Martin, Maciej Haranczyk, Joseph A. Swisher & Berend Smit, "GPU Computational Screening of Carbon Capture Materials", Scientific Discovery through Advanced Computing 2011, 2011,

Maciej Haranczyk, James A. Sethian, "Automatic Structure Analysis in High-Throughput Characterization of Porous Materials", Journal of Chemical Theory and Computation, 2010, 6:3472-3480, doi: 10.1021/ct100433z

Reports

Gunther H. Weber, Kenes Beketayev, Peer-Timo Bremer, Bernd Hamann, Maciej Haranczyk, Mario Hlawitschka, Valerio Pascucci, "Comprehensible Presentation of Topological Information", Status report for DOE Exascale Research Conference, April 2012, LBNL 5693E,

Web Articles

"New materials could slash energy costs for CO2 capture", Jade Boyd, David Ruth, May 30, 2012,

A detailed analysis of more than 4 million absorbent minerals has determined that new materials could help electricity producers slash as much as 30 percent of the “parasitic energy” costs associated with removing carbon dioxide from power plant emissions...

When power plants begin capturing their carbon emissions to reduce greenhouse gases – and to most in the electric power industry, it’s a question of when, not if – it will be an expensive undertaking...

Posters

Gunther H. Weber, Dmitriy Morozov, Kenes Beketayev, John Bell, Peer-Timo Bremer, Marc Day, Bernd Hamann, Christian Heine, Maciej Haranczyk, Mario Hlawitschka, Valerio Pascucci, Patrick Oesterling, Gerik Scheuermann, "Topology-based Visualization and Analysis of High-dimensional Data and Time-varying Data at the Extreme Scale", DOE Exascale Research Conference, April 2012,

Richard L. Martin, Thomas F. Willems, Chris H. Rycroft, Prabhat, Michael Kazi and Maciej Haranczyk, "High-throughput structure analysis and descriptor generation for crystalline porous materials", International Conference on Chemical Structures (Noordwijkerhout, Netherlands), June 5, 2011,

Richard L. Martin, Maciej Haranczyk, Prabhat and James A. Sethian, "PDE-based analysis of void space of porous materials on multicore CPUs", Manycore and Accelerator-based High-performance Scientific Computing 2011 (Berkeley, CA), January 24, 2011,

Cover Storys

Richard L. Martin, Thomas F. Willems, Li-Chiang Lin, Jihan Kim, Joseph A. Swisher, Berend Smit & Maciej Haranczyk, "Similarity-Driven Discovery of Zeolite Materials for Adsorption-Based Separations", ChemPhysChem, Pages: 3561 August 22, 2012,

A tool for identifying optimum zeolite frameworks for gas separations at a fraction of the cost of molecular simulation is presented on p. 3595 ff. by M. Haranczyk et al. The method is based on identifying property-determining substructure features and searching material databases for geometrically similar arrangements of framework atoms. The approach is deployed to screen a database an order of magnitude larger than has been examined in previous studies.

Others

Maciej Haranczyk, Chris H. Rycroft & James A. Sethian, Empty Space and New Materials: Computational Tools for Porous Materials, SIAM News, October 18, 2011,

Crystalline porous materials are some of the most important synthetic products ever made...