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The nudged-elastic band (NEB) method is modified with concomitant two climbing images (C2-NEB) to find a transition state (TS) in complex energy landscapes, such as those with serpentine minimal energy path (MEP). If a single climbing image…

Computational Physics · Physics 2017-11-28 Nikolai A. Zarkevich , Duane D. Johnson

Accurate determination of transition states is central to an understanding of reaction kinetics. Double-endpoint methods where both initial and final states are specified, such as the climbing image nudged elastic band (CI-NEB), identify…

Chemical Physics · Physics 2026-04-08 Rohit Goswami , Miha Gunde , Hannes Jónsson

The discovery of a minimum energy pathway (MEP) between metastable states is crucial for scientific tasks including catalyst and biomolecular design. However, the standard nudged elastic band (NEB) algorithm requires hundreds to tens of…

Materials Science · Physics 2025-12-18 Pranav Kakhandiki , Sathya Chitturi , Daniel Ratner , Sean Gasiorowski

We present a modified version of the nudged elastic band (NEB) algorithm to find minimum energy paths con-necting two known configurations. We show that replacing the harmonic band-energy term with a discretized version of the…

Computational Physics · Physics 2024-06-19 Davide Mandelli , Michele Parrinello

The nudged elastic band (NEB) method is the standard approach for finding minimum energy paths and transition states on potential energy surfaces. Practical NEB calculations require several pre-processing steps: endpoint minimization,…

Chemical Physics · Physics 2026-04-17 Rohit Goswami

The nudged elastic band (NEB) method is one of the most widely used techniques for determining minimum-energy reaction pathways and activation barriers between known initial and final states. However, conventional implementations face steep…

Computational Physics · Physics 2025-10-21 Qiuhan Jia , Jiuyang Shi , Jian Sun

Efficient algorithms for the calculation of minimum energy paths of magnetic transitions are implemented within the geodesic nudged elastic band (GNEB) approach. While an objective function is not available for GNEB and a traditional line…

Computational Physics · Physics 2020-11-30 Aleksei V. Ivanov , Damjan Dagbartsson , Julien Tranchida , Valery M. Uzdin , Hannes Jónsson

We present a modified nudged elastic band routine that can reduce the number of force calls by more than 50% for bands with non-uniform convergence. The method, which we call "dyNEB", dynamically and selectively optimizes states based on…

Chemical Physics · Physics 2023-08-04 Per Lindgren , Georg Kastlunger , Andrew A. Peterson

The nudged elastic band (NEB) method is a commonly used approach for the calculation of minimum energy pathways of kinetic processes. However, the final paths obtained rely heavily on the nature of the initially chosen path. This often…

Materials Science · Physics 2019-04-30 Jason M. Munro , Vincent S. Liu , Venkatraman Gopalan , Ismaila Dabo

The modeling of solid-state transformations, such as polymorphic transitions and chemical reactions in molecular crystals, is vital for many applications including drug design or the development of new synthesis methods. However, a…

Chemical Physics · Physics 2025-06-17 Natalia Goncharova , Johannes Hoja

We demonstrate that the straightforward application of the Nudged Elastic Band (NEB) method does not determine the correct Peierls barrier of 1/2<111> screw dislocations in BCC metals. Although this method guarantees that the states…

Materials Science · Physics 2011-11-28 R. Gröger , V. Vitek

The nudged elastic band (NEB) and Dimer methods are standard tools for computing minimum-energy paths and index-one saddle points in atomistic transition problems. They are increasingly driven by surrogate or learned force models, whose…

Numerical Analysis · Mathematics 2026-05-26 Yifan Yu , Yangshuai Wang

The nuclear fission process is a dramatic example of the large-amplitude collective motion in which the nucleus undergoes a series of shape changes before splitting into distinct fragments. This motion can be represented by a pathway in the…

We present the incorporation of a surrogate Gaussian Process Regression (GPR) atomistic model to greatly accelerate the rate of convergence of classical Nudged Elastic Band (NEB) calculations. In our surrogate model approach, the cost of…

Computational Physics · Physics 2019-04-24 José A. Garrido Torres , Paul C. Jennings , Martin H. Hansen , Jacob R. Boes , Thomas Bligaard

Solid-state electrolytes are essential in the development of all-solid-state batteries. While density functional theory (DFT)-based nudged elastic band (NEB) and ab initio molecular dynamics (AIMD) methods provide fundamental insights on…

Materials Science · Physics 2025-07-04 Jingchen Lian , Xiao Fu , Xuhe Gong , Ruijuan Xiao , Hong Li

In finite systems, such as nanoparticles and gas-phase molecules, calculations of minimum energy paths (MEPs) connecting initial and final states of transitions as well as searches for saddle points are complicated by the presence of…

Chemical Physics · Physics 2015-06-09 Marko Melander , Kari Laasonen , Hannes Jonsson

The minimum energy path (MEP) describes the mechanism of reaction, and the energy barrier along the path can be used to calculate the reaction rate in thermal systems. The nudged elastic band (NEB) method is one of the most commonly used…

Numerical Analysis · Mathematics 2025-03-24 Xuanyu Liu , Huajie Chen , Christoph Ortner

Locating transition states is crucial for investigating transition mechanisms in wide-ranging phenomena, from atomistic to macroscale systems. Existing methods, however, can struggle in problems with a large number of degrees of freedom,…

Computational Physics · Physics 2022-09-07 Samuel J. Avis , Jack R. Panter , Halim Kusumaatmaja

We show that neural networks can be optimized to represent minimum energy paths as continuous functions, offering a flexible alternative to discrete path-search methods such as Nudged Elastic Band (NEB). Our approach parameterizes reaction…

Machine Learning · Computer Science 2025-07-10 Kalyan Ramakrishnan , Lars L. Schaaf , Chen Lin , Guangrun Wang , Philip Torr

We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by generalizing three components of BFGS to subdifferentials: the…

Machine Learning · Statistics 2010-11-30 Jin Yu , S. V. N. Vishwanathan , Simon Guenter , Nicol N. Schraudolph
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