Workshop on FreeFEM

The Department of Mathematics of the University of Pittsburgh will be hosting a workshop on FreeFEM++ given by Professor Frederic Hecht:
What: An Introduction to Scientific Computing using Free Software FreeFem++
Description of the workshop from Professor Hecht:
“I would like it to be possible to solve digitally, in a user-friendly way, the problems modeled by partial differential equations (PDEs) from physics, engineering, computing graphics and recently from the finance-banking sector. This problem is therefore at the interface between applied mathematics, numerical analysis, computer science and the relevant applications (fluid mechanics, electromagnetism, quantum mechanics and stock options in finance).”
Where: Thackery hall Room 427
When: August 22, 2017 (All day) – September 1, 2017 (All day)
Who: Everyone is welcome. However, the current room is not large. It would be helpful to email us ( or if you plan to attend so we can estimate audience size and adjust if necessary.

For more information and the detailed schedule, please visit:

Updates to H2P: Partition Changes After Testing Phase

Dear H2P Users,

The testing period for the new nodes was a success! We need to shuffle around some of the nodes in smp to accommodate the new nodes. The partitions will become:

Old NameNew NameCharging Rate
testsmp (default)0.8

We will be draining all of the nodes and moving them into new partitions. Running jobs will not be affected. Any jobs which are submitted to the test partition will need to be resubmitted. Sorry for any inconvenience.


The CRC Team


Job Opportunity for Undergrads at CRC

Center for Research Computing (CRC) at Pitt is seeking two undergraduate candidates for operations support positions in the area of user management and support at the center. The position will work closely with CRC staff.

Essential functions of this position:
Address user tickets in consultation with center staff
Assist CRC staff in routine activities
Address bugs and problems with technical systems from time to time
Analyze user experience and propose and develop improvements

Required skills and experience: Familiarity with a Linux based working environment. Strong verbal and written communication skills.

Start date: ASAP

Compensation: $10/hour

If you are interested, please email your CV to


Thank you,

CRC Team

Computational investigation of CO2 electroreduction on tin oxide and predictions of Ti, V, Nb and Zr dopants for improved catalysis

The Journal of Matetrials Chemistry A has just published their issue highlighting their 2017 “rising stars” and one of those individuals invited to submit an article was our very own ChemE Assistant Professor John Keith.  The link to John’s article is here.

Journal of Materials Chemistry A is proud to present this themed issue highlighting 2017’s rising stars of materials chemistry research. This issue gathers the very best work from materials chemists in the early stages of their independent career. Each contributor was recommended by experts in their fields as carrying out work with the potential to influence future directions in materials chemistry. Congratulations to all of those who feature on their important work so far in the field of materials energy and sustainability.

Vice Provost of Research announced a new PSC initiative

Dear Pitt Faculty,

I want to make you aware of a new initiative at the Pittsburgh Supercomputing Center (PSC) for our faculty.  This could be a great opportunity for those faculty whose research includes High Performance Computing.

Earlier this year PSC completed a technical upgrade of Bridges, its unique high-performance computing (HPC) system. Bridges enables applications that have not traditionally used HPC, integrates HPC with Big Data and artificial intelligence, and helps researchers facing challenges in Big Data to work more intuitively.

PSC is now making Bridges available at no charge to CMU and Pitt faculty through a simple, easy process so you can discover how Bridges can facilitate your research.

To learn more on how Bridges can be a good fit for your research, and how to get started with this exciting new initiative go to

Pittsburgh Supercomputing Center is a joint effort of Carnegie Mellon University and the University of Pittsburgh. PSC provides university, government and industrial researchers with access to several of the most powerful systems for high-performance computing, communications and data storage available to scientists and engineers nationwide for unclassified research.



Mark S. Redfern, PhD

Vice Provost for Research

William Kepler-Whiteford Professor of Bioengineering

University of Pittsburgh

NSF CAREER Awards to Four CRC-Affiliated Faculty

Four CRC-affiliated faculty were awarded the National Science Foundation (NSF) CAREER Award this funding cycle. The CAREER Award is the NSF’s most prestigious award for early career-development for teacher-scholars, and has a reviewing and selection process that is one of the most competitive within NSF. The Pitt CRC faculty who received the CAREER Award this cycle are John Keith, Peng Liu, Giannis Mpourmpakis and Christopher Wilmer. Remarkably, three of the faculty, Keith, Mpourmpakis and Wilmer, all come from a single department within the Swanson School of Engineering (Chemical & Petroleum Engineering). All four faculty rely heavily on CRC resources to perform their research and all contributed startup funds to access the high-levels of computer time and support required to make their research a success. The role that CRC plays in facilitating their research is illustrated by this quote from Dr. Mpourmpakis: “CRC has been very instrumental in accelerating our research both in terms of available computational resources and support from experienced personnel.”

Descriptions of each of the CAREER research projects are given below.

John A. Keith, Assistant Professor and Inaugural R.K. Mellon Faculty Fellow in Energy SusChEM: Unlocking local solvation environments for energetically efficient hydrogenations with quantum chemistry (#1653392)

John Keith’s proposal “Unlocking local solvation environments for energetically efficient hydrogenations with quantum chemistry” was recently selected for an NSF CAREER award. The project addresses the production of carbon-neutral liquid fuels via electrocatalytic reduction of the greenhouse gas carbon dioxide (CO2) to methanol. Specifically, the study seeks to improve the efficiency and selectivity of current solvent-based electrochemical processes by advancing understanding of how aqueous electrolytes participate in the overall reaction mechanisms at the atomic scale. The research will be coupled with educational thrusts that engage students in grades 8-12 in learning about renewable energy catalysis and computational chemistry.

In the figure shown above, A) overlaid Pourbaix diagrams for an N-doped graphene ribbon (gray/purple) and carbonic acid (solid lines). B) QC calculated ΔE values along the reaction pathway for the hydride transfer reaction: 2H2O + BH4– + CO2 →H3O+ +BH3OH– + HCO2–. PBE data corresponding to minimum energy pathways for a) explicit solvent + counter ion, b) continuum solvent only, c) 1st solvent shell + continuum solvent, d) counter ion and continuum solvent, e) 1st solvent shell + counter ion + continuum solvent.

Peng Liu, Department of Chemistry
Computational Studies of Transition Metal Catalyzed Reactions in Organic Synthesis (#1654122 )

In this CAREER project funded by the Chemical Structure, Dynamic & Mechanism-B Program (CSDM-B) of the Chemistry Division, Professor Peng Liu of the Department of Chemistry at the University of Pittsburgh is developing new strategies to use computational tools to investigate mechanisms and effects of ancillary ligands in transition-metal-catalyzed reactions of unactivated starting materials, such as C-C and C-H bonds, and unactivated olefins. The goal of this research is to reveal the fundamental reactivity rules of common organometallic intermediates in these transformations and to develop new models to interpret ligand effects on reactivity and selectivity. This proposal’s educational and outreach plan aims to maximize the power of computations to enhance learning of organic chemistry concepts and to facilitate synthetic organic chemistry research. Professor Liu’s team will develop virtual reality (VR) software and educational materials to visualize three-dimensional molecular structures and reaction mechanism videos in an interactive and immersive environment.

This project aims to address two basic challenges in performing computational studies on transition-metal-catalysis: 1) the lack of mechanistic understandings in many recently developed catalytic systems, and 2) the complexities in analyzing and rationalizing computational data, in particular, the origin of ligand effects. The proposed research will investigate novel reaction pathways involving the activated organometallic intermediates formed after the C-H and C-C bond cleavage steps, and elucidate the effects of ligands, directing groups, substituents, ring strain, and norbornene and Lewis acid co-catalysts. To systematically characterize the origin of ligand effects on reactivity and selectivity, a ligand-substrate interaction model will be developed. This model uses energy decomposition analysis (EDA) methods to dissect the through-space ligand-substrate interactions into chemically meaningful terms, including steric repulsion, polarization, charge transfer, and dispersion. The insights obtained from the proposed ligand-substrate interaction model will be used to develop of a catalyst screening methodology for transition-metal-catalysts.

Giannis (Yanni) Mpourmpakis, Assistant Professor
Designing synthesizable, ligand-protected bimetallic nanoparticles and modernizing engineering curriculum through computational nanoscience (#1652694)

“The goal of this project is to develop a novel open-access computational framework for predicting the growth mechanisms and morphologies of ligand-protected metal nanoparticles (NPs).
With NPs impacting numerous fields of science and technology, from energy to medicine to the environment, there is a critical need to determine the growth mechanisms of ligand-protected metal NPs and predict NP morphologies that can be synthesized in the laboratory. Although metal nanoparticles (NPs) of different sizes and shapes can be synthesized by colloidal chemistry methods, advances towards controlling NP morphology have been based largely on trial and error experimentation, which is often tedious and costly. The proposed computational framework will employ novel first-principles-based structure-property relationships accounting for structure sensitivity and metal composition. The integration of research and education efforts will focus on modernizing the traditional Chemical Thermodynamics course by introducing animation modules based on cutting-edge nanotechnology examples. Outreach activities are planned through a nanoscale-inspired interactive computer game to engage high school students, including underrepresented minorities, into pursuing STEM careers and increase awareness about the importance of the field of nanotechnology.

The proposed research project will combine Density Functional Theory methods with Monte Carlo and Molecular Dynamics simulations, Machine Learning, and scientific computing to develop a novel, open-access computational framework, applicable to the design of ligand-protected NPs. This framework will generate a library of crystal structures and electronic properties of thermodynamically stable, thiolate-protected, Au-based bimetallic NPs, across a range of heterometals and particle morphologies, all under realistic experimental conditions. The proposed work aims to advance current theories on NP stabilization, which are based on simplified, electron counting rules. The proposed computational framework will enable rational design of ligand-protected NPs. It will also elucidate NP growth steps that are experimentally intractable, thus accelerating nanomaterials discovery. The research findings will be made available online for experimental verification.”

Christopher Wilmer, Assistant Professor
Fundamental limits of physical adsorption in porous materials (#1653375) 

“The research objective of this proposal is to further our understanding of the range of physically accessible adsorption behavior in porous materials, and in so doing determine theoretical efficiency limits on important adsorption-related processes
, such as post-combustion carbon capture. The PI will use classical molecular modeling to simulate adsorption in randomly generated porous materials, called pseudomaterials, where the constraint that the materials be energetically stable is relaxed. Since the limits of adsorption in pseudomaterials will necessarily be higher than in real materials, determining the limits of pseudomaterials will also determine the limits for real materials. This approach will be used to establish a rigorous theoretical upper limit on the efficiency of a membrane-based post-combustion carbon capture process, which is considered one of the most promising technologies for mitigating climate change due to fossil fuel-based power plant emissions.”
“The educational objective of this proposal is to further public understanding of gas separations processes at the molecular level, especially as they pertain to carbon capture technologies relevant to climate change. The PI will (1) leverage his past success in creating award-winning scientific movies to develop a sequence of five educational movies on the fundamental physics, and applications, of gas adsorption (one for each year of the grant period), (2) teach lessons on adsorption to high school students interested in STEM careers as part of the University of Pittsburgh’s INVESTING NOW program, and (3) mentor undergraduates from underrepresented groups via the University of Pittsburgh’s EXCEL program. To increase their effectiveness and scale of impact, the educational movies will be created in consultation with science film-making professionals at Untamed Science, who will also help disseminate the movies online.”

$15,000/yr ACM SIGHPC/Intel Computational & Data Science Fellowships

ACM SIGHPC and Intel have partnered to create Computational and Data Science Fellowships, a 5-year program to increase the diversity of students pursuing graduate degrees in data science and computational science. Specifically targeted at women or students from racial/ethnic backgrounds that have not traditionally participated in the computing field, the program is open to students pursuing degrees at institutions anywhere in the world. Here are the important dates:

Submissions open: March 15
Submissions close: April 30
Winners announced: by July 31

For more information on qualification criteria and application submission, please visit SIGHPC website.

ARC 2017 Poster Session Winners

CRC would like to acknowledge and congratulate our poster session winners from our recent Advancing Research through Computing symposium!  Two winners were selected from more than 20 submissions.  Each winner received a $500 travel stipend.  More information about each winner below.

Michael Taylor

BioI received my B.S. in Chemical Engineering from University of Nebraska-Lincoln, followed by a year of process engineering work experience at Cargill in Nebraska before coming to the University of Pittsburgh to work on my PhD. I am pursing my PhD in the Department of Chemical Engineering at the University of Pittsburgh under the direction of Prof. Giannis Mpourmpakis. My primary focus is on the stability and synthesis of colloidal “magic-number” nanoclusters, while I am have on several side-projects on topics ranging from kidney stone growth modifiers to catalytic applications of nanomaterials.

Poster Title: “Stability and Prediction of Thiolated Metal Nanoclusters”

Poster Abstract: Thiolate-protected metal nanoclusters (NCs) of the form Mn(SR)m, exhibiting “magic numbers” in their stability, and several of their corresponding atomically-precise structures have been identified. These NCs show promising applications in fields such as drug delivery, bio-imaging, and catalysis. However, understanding what drives NC stability remains limited. Herein we introduce a first-principles derived structure-stability model of thiolate-protected NCs that rationalizes their experimental stability. Utilizing this model we report the successful reproduction of a known NC core structure, taking a step towards a general methodology for NCs structure prediction. Ultimately, our model aids in accelerating the discovery of atomically precise, highly-stable, colloidal NCs.

Jon Ruffley 

Bio: I received my B.S. in Chemical Engineering from The Ohio State University, where I did undergraduate research in the organic synthesis lab of Dr. Noel Paul. I am currently working toward my PhD at University of Pittsburgh under the guidance of Dr. J. Karl Johnson. My areas of study include plasmonic properties of non-noble metal nanoparticles, and the application of quantum chemistry methods to the design of metal-organic frameworks.

Poster Title: Hybrid Stratified MOF-Plasmonic Nanoparticle Materials for Detection and Destruction of Chemical Agents

Abstract: There is a pressing need for methods capable of rapidly detecting and destroying chemical warfare agents. We seek to develop a detailed understanding of the fundamental properties of multifunctional plasmonic hybrid nanomaterials for sorption, transport, photodetection, and photocatalytic degradation of target chemical species. We use continuum models to predict extinction spectra of CuSe nanoparticles, quantum mechanical methods to identify promising functional groups to bind target species in metal-organic frameworks (MOFs), and Monte Carlo methods to perform pure fluid adsorption isotherms in candidate MOFs. We have accurately predicted the extinction spectra of noble metal nanoparticles. Initial ab initio calculations have been used to identify functional groups capable of binding target chemical warfare agent simulants. We have calculated isotherms of small gas molecules in MOFs and compared our results with experiments, as a step toward computing isotherms of chemical warfare agent simulants.