Nils Zimmermann

Nils Zimmermann
Lawrence Berkeley National Laboratory | LBL · Computational Science

Doctor of Engineering

About

27
Publications
6,924
Reads
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1,320
Citations
Citations since 2016
15 Research Items
1170 Citations
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
Introduction
I am a researcher who is active at the interface between physical chemistry, materials science, engineering, and data science. I combine theory, computation, and visualization to improve our understanding of processes at the nanoscale and predictions of scientifically and/or technologically important, but challenging, properties. I am actively supporting key scientific principles (e.g., open access) and ways to strengthen diversity and inclusion in academia (e.g., via union leadership roles).
Additional affiliations
January 2021 - present
Universität Stuttgart
Position
  • Research Associate
Description
  • I'm currently working on predicting thermophoretic properties to facilitate characterization of active pharmaceutical ingredients with classical molecular simulations.
January 2017 - September 2018
Lawrence Berkeley National Laboratory
Position
  • PostDoc Position
Description
  • Smart descriptor design facilitating efficient materials database screenings for various applications such as energy storage, catalysis, electronics.
May 2015 - January 2017
Lawrence Berkeley National Laboratory
Position
  • PostDoc Position
Description
  • Smart descriptor design facilitating efficient materials database screenings for various applications such as energy storage, catalysis, electronics.
Education
November 2007 - March 2013
Technische Universität Hamburg
Field of study
  • Chemical Engineering
September 2004 - December 2004
KTH Royal Institute of Technology
Field of study
  • Chemical Engineering
August 2003 - June 2006
Technische Universität Hamburg
Field of study
  • Chemical Engineering

Publications

Publications (27)
Article
Coordination numbers and geometries form a theoretical framework for understanding and predicting materials properties. Algorithms to determine coordination numbers automatically are increasingly used for machine learning (ML) and automatic structural analysis. In this work, we introduce MaterialsCoord, a benchmark suite containing 56 experimentall...
Preprint
Coordination numbers and geometries form a theoretical framework for understanding and predicting materials properties. Algorithms to determine coordination numbers automatically are increasingly used for machine learning and automatic structural analysis. In this work, we introduce MaterialsCoord, a benchmark suite containing 56 experimentally-der...
Article
Full-text available
Structure characterization and classification is frequently based on local environment information of all or selected atomic sites in the crystal structure. Therefore, reliable and robust procedures to find coordinated neighbors and to evaluate the resulting coordination pattern (e.g., tetrahedral, square planar) are critically important for both t...
Article
Zeolites are important microporous framework materials, where 200+ structures are known to exist and many millions so-called hypothetical materials can be computationally created. Here, we screen the “Deem” database of hypothetical zeolite structures to find experimentally feasible and industrially relevant materials. We use established and existin...
Preprint
Structure characterization and classification is frequently based on local environment information of all or selected atomic sites in the crystal structure. Therefore, reliable and robust procedures to find coordinated neighbors and to evaluate the resulting coordination pattern (e.g., tetrahedral, square planar) are critically important for both t...
Preprint
div>Zeolites are important microporous framework materials, where 200+ structures are known to exist and many millions so-called hypothetical materials can be computationally created. Here, we screen the “Deem” database of hypothetical zeolite structures to find experimentally feasible and industrially relevant materials. We use established and exi...
Article
As materials data sets grow in size and scope, the role of data mining and statistical learning methods to analyze these materials data sets and build predictive models is becoming more important. This manuscript introduces matminer, an open-source, Python-based software platform to facilitate data-driven methods of analyzing and predicting materia...
Article
Full-text available
This work reexamines seeded simulation results for NaCl nucleation from a supersaturated aqueous solution at 298.15 K and 1 bar pressure. We present a linear regression approach for analyzing seeded simulation data that provides both nucleation rates and uncertainty estimates. Our results show that rates obtained from seeded simulations rely critic...
Article
We report on a scheme for estimating intercalant jump-diffusion barriers that are typically obtained from demanding density functional theory-nudged elastic band calculations. The key idea is to relax a chain of states in the field of the electrostatic potential that is averaged over a spherical volume using different finite-size ion models. For ma...
Article
Full-text available
Structure–property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors, as well as the capacity of and transport properties in cathode materials for rechargeable batteries. The immediate atomic env...
Article
The increasing demand of solid-state energy storage requires improved technologies, such as Mg-ion batteries, to address safety and cost concers as well as the energy density limitations of state-of-the-art Li-ion battery technology, however, the realization of Mg-ion batteries hinges on the discovery of host materials that possess sufficiently hig...
Article
Full-text available
Point defects have a strong impact on the performance of semiconductor and insulator materials used in technological applications, spanning microelectronics to energy conversion and storage. The nature of the dominant defect types, how they vary with processing conditions, and their impact on materials properties are central aspects that determine...
Article
Mature applications such as fluid catalytic cracking and hydrocracking rely critically on early zeolite structures. With a data-driven approach, we find that the discovery of exceptional zeolite framework types around the new millennium was spurred by exciting new utilization routes. The promising processes have yet not been successfully implemente...
Article
Full-text available
Diffusion in nanoporous host-guest systems is often considered to be too complicated to comply with such "simple" relationships as Fick's first and second law of diffusion. However, it is shown herein that the microscopic techniques of diffusion measurement, notably the pulsed field gradient (PFG) technique of NMR spectroscopy and microimaging by i...
Article
Die Diffusion in nanoporösen Wirt-Gast-Systemen wird oft als viel zu kompliziert angesehen, als dass sie mit so “einfachen” Beziehungen wie dem ersten und zweiten Fickschen Gesetz vereinbar sein könnte. Wir zeigen nun, dass die mikroskopischen Diffusionsmesstechniken, vor allem die NMR-Spektroskopie mit gepulsten Feldgradienten (PFG) und die Mikrob...
Article
Nucleation and crystal growth are important in material synthesis, climate modeling, biomineralization, and pharmaceutical formulation. Despite tremendous efforts, the mechanisms and kinetics of nucleation remain elusive to both theory and experiment. Here we investigate sodium chloride (NaCl) nucleation from supersaturated brines using seeded atom...
Article
Full-text available
Ultrathin porous materials, such as zeolite nanosheets, are prominent candidates for performing catalysis, drug supply, and separation processes in a highly efficient manner due to exceptionally short transport paths. Predictive design of such processes requires the application of diffusion equations that were derived for macroscopic, homogeneous s...
Article
Full-text available
The regular nanoporous structure make zeolite membranes attractive candidates for separating molecules on the basis of differences in transport rates (diffusion). Since improvements in synthesis have led to membranes as thin as several hundred nanometers by now, the slow transport in the boundary layer separating bulk gas and core of the nanoporous...
Article
Full-text available
Shedding light on the nature of surface barriers of nanoporous materials, molecular simulations (Monte Carlo, Reactive Flux) have been employed to investigate the tracer-exchange characteristics of hydrocarbons in defect-free single-crystal zeolite membranes. The concept of a critical membrane thickness as a quantitative measure of surface barriers...
Article
Full-text available
The influence of isotypic crystal structures on adsorption and diffusion of methane in all-silica LTA, SAS and ITE zeolites is studied. Results obtained with the experimental structures are compared with structure predictions and approximations that are commonly employed. The results indicate that diffusion coefficients are much more affected than...
Article
Full-text available
With the aid of molecular simulation techniques (molecular dynamics, grand-canonical Monte Carlo, and reactive flux correlation function RFCF), the influence of the external surface on the equilibrium permeation of methane and ethane into and out of an AFI-type zeolite crystal has been studied. In particular, “extended dynamically corrected transit...
Article
Increased interest in natural gas hydrate formation and decomposition, coupled with experimental difficulties in diffusion measurements, makes estimating transport properties in hydrates an important technological challenge. This research uses an equilibrium path sampling method for free energy calculations [Radhakrishnan, R.; Schlick, T. J. Chem....
Conference Paper
Diffusivities in natural gas hydrates are important but elusive transport properties. We describe an efficient and versatile equilibrium path sampling (EPS) approach for computing free energies. We use EPS along with transmission coefficient calculations and kinetic monte carlo simulations, to estimate the methane diffusivity within a structure I h...
Conference Paper
Zeolites represent a very important class of nanoporous materials that are frequently involved in industrial processes such as catalysis, separation, and ion-exchange. Therefore, the understanding and proper description of adsorption, diffusion, and reaction inside zeolite pores is crucial to process designing purposes. From a scientific point of v...
Article
Full-text available
Molecular-dynamics simulations are performed to understand the role of host-framework flexibility on the diffusion of methane molecules in the one-dimensional pores of AFI-, LTL-, and MTW-type zeolites. In particular, the impact of the choice of the host model is studied. Dynamically corrected Transition State Theory is used to provide insights int...

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Project (1)
Project
PyCDT's goal is to expedite the setup and post-processing of point defect calculations in insulators and semiconductors. PyCDT allows for setting up of DFT calculations for charged defects, as well as post-processing and applying state-of-the-art electrostatic correction terms. It also sets up calculation of auxiliary parameters such as chemical potentials and dielectric constants. It has a user-friendly command-line interface and can be interfaced with high-throughput workflow software such as Fireworks.