scholarly journals Energy landscapes of perfect and defective solids: from structure prediction to ion conduction

2021 ◽  
Vol 140 (11) ◽  
Author(s):  
Neil L. Allan ◽  
Sergio Conejeros ◽  
Judy N. Hart ◽  
Chris E. Mohn
Keyword(s):  
Ion Transport ◽  
Solid Solutions ◽  
Structure Prediction ◽  
Dynamic Properties ◽  
Energy Landscape ◽  
Disordered Materials ◽  
Low Density ◽  
Energy Landscapes ◽  
Inorganic Solids ◽  
Fast Ion

AbstractThe energy landscape concept is increasingly valuable in understanding and unifying the structural, thermodynamic and dynamic properties of inorganic solids. We present a range of examples which include (i) structure prediction of new bulk phases including carbon nitrides, phosphorus carbides, LiMgF3 and low-density, ultra-flexible polymorphs of B2O3, (ii) prediction of graphene and related forms of ZnO, ZnS and other compounds which crystallise in the bulk with the wurtzite structure, (iii) solid solutions, (iv) understanding grossly non-stoichiometric oxides including the superionic phases of δ-Bi2O3 and BIMEVOX and the consequences for the mechanisms of ion transport in these fast ion conductors. In general, examination of the energy landscapes of disordered materials highlights the importance of local structural environments, rather than sole consideration of the average structure.

Energy landscapes and solved protein–folding problems

2004 ◽  
Vol 363 (1827) ◽  
pp. 453-467 ◽  
Author(s):  
Peter G. Wolynes
Keyword(s):  
Protein Folding ◽  
Protein Design ◽  
Structure Prediction ◽  
Energy Landscape ◽  
Protein Structures ◽  
Energy Landscapes ◽  
Folding Kinetics ◽  
Energy Functions ◽  
Energy Landscape Theory ◽  
Novel Proteins

Energy–landscape theory has led to much progress in protein folding kinetics, protein structure prediction and protein design. Funnel landscapes describe protein folding and binding and explain how protein topology determines kinetics. Landscape–optimized energy functions based on bioinformatic input have been used to correctly predict low–resolution protein structures and also to design novel proteins automatically.

scholarly journals Exploring biomolecular energy landscapes

2017 ◽  
Vol 53 (52) ◽  
pp. 6974-6988 ◽  
Author(s):  
Jerelle A. Joseph ◽  
Konstantin Röder ◽  
Debayan Chakraborty ◽  
Rosemary G. Mantell ◽  
David J. Wales
Keyword(s):  
Potential Energy ◽  
Structure Prediction ◽  
Energy Landscape ◽  
Energy Landscapes ◽  
Computational Framework ◽  
Feature Article ◽  
Thermodynamics And Kinetics ◽  
Potential Energy Landscape ◽  
Kinetics Of

This feature article presents the potential energy landscape perspective, which provides both a conceptual and computational framework for structure prediction, and decoding the global thermodynamics and kinetics of biomolecules.

scholarly journals Sonifying Stochastic Walks on Biomolecular Energy Landscapes

2018 ◽  
Author(s):  
Robert E. Arbon ◽  
Alex J. Jones ◽  
Lars A. Bratholm ◽  
Tom Mitchell ◽  
David R. Glowacki
Keyword(s):  
Free Energy ◽  
Markov Models ◽  
Dynamic Properties ◽  
Energy Landscape ◽  
Visual Display ◽  
Free Energy Landscape ◽  
Auditory Display ◽  
Energy Landscapes ◽  
Biomolecular Systems ◽  
Relative Free Energy

Translating the complex, multi-dimensional data produced by simulations of biomolecules into an intelligible form is a major challenge in computational chemistry and biology. The so-called “free energy landscape” is amongst the most fundamental concepts used by scientists to understand both static and dynamic properties of biomolecular systems. In this paper we use Markov models to design a strategy for mapping features of this landscape to sonic parameters, for use in conjunction with visual display techniques such as structural animations and free energy diagrams. This allows for concurrent visual display of the physical configuration of a biomolecule and auditory display of characteristics of the corresponding free energy landscape. The resulting sonification provides information about the relative free energy features of a given configuration including its stability.

scholarly journals Interpreting computed crystal energy landscapes for pharmaceutical molecules

2014 ◽  
Vol 70 (a1) ◽  
pp. C1615-C1615
Author(s):  
Sarah Price
Keyword(s):  
Crystal Structure ◽  
Crystal Structures ◽  
Structure Prediction ◽  
Energy Landscape ◽  
Crystal Structure Prediction ◽  
Energy Landscapes ◽  
Pyridinecarboxylic Acid ◽  
Solid Form ◽  
Pharmaceutical Molecules ◽  
Polymorph Screening

Crystal Structure Prediction (CSP) algorithms aim to generate the thermodynamically feasible crystal structures of a molecule from the chemical diagram, ranking their relative stability by a necessarily approximate estimate of the crystal energy. Such calculations are becoming feasible for molecules of a size and flexibility of small molecule pharmaceuticals. Contrasting the crystal energy landscape, the computer generated structures that are thermodynamically plausible as polymorphs, with the results of experimental polymorph screening, shows that CSP studies are not limited to being a search for the most thermodynamically stable crystal structure but can play a valuable role in understanding polymorphism and the potential complexity of crystallisation behaviour.[1] This presentation will illustrate the use of CSP as a complement to industrial-type solid form screening activities. Examples will include olanzapine, [2] tazofelone, two closely related 5-HT2a agonists and 6-[(5-chloro-2-([(4-chloro-2-fluorophenyl)methyl]oxy)phenyl)methyl]-2-pyridinecarboxylic acid (GSK269984B).[3] This illustrates the use of the crystal energy landscape to understand disorder, help structurally characterise metastable polymorphs and suggest whether there are additional polymorphs to be targeted. Since crystal energy landscapes usually include a wider range of crystal structures than known polymorphs, it raises the scientific question as to what determines which structures can be observed as metastable polymorphs. Thus both scientific as well as technological challenges need to be overcome before we can predict polymorphs.

Energy Landscapes: An Overview

2001 ◽  
Vol 700 ◽  
Author(s):  
David J. Wales
Keyword(s):  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Dynamic Properties ◽  
Energy Landscape ◽  
Global Optimisation ◽  
Energy Landscapes ◽  
Energy Landscape Theory ◽  
Landscape Theory ◽  
Optimisation Algorithms

AbstractThe goal of energy landscape theory is to relate observable thermodynamic and dynamic properties to features of the underlying potential energy surface. Here we illustrate the approach with reference to the annealing of C60 and indicate how it may be used to design improved global optimisation algorithms.

scholarly journals Fast-ion transport in low density L-mode plasmas at TCV using FIDA spectroscopy and the TRANSP code

2017 ◽  
Vol 59 (11) ◽  
pp. 115002 ◽  
Author(s):  
B Geiger ◽  
A N Karpushov ◽  
B P Duval ◽  
C Marini ◽  
O Sauter ◽  
...  
Keyword(s):  
Ion Transport ◽  
Low Density ◽  
Fast Ion

scholarly journals Universally bistable shells with nonzero Gaussian curvature for two-way transition waves

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Nikolaos Vasios ◽  
Bolei Deng ◽  
Benjamin Gorissen ◽  
Katia Bertoldi
Keyword(s):  
Gaussian Curvature ◽  
Energy Landscape ◽  
Propagation Distance ◽  
Energy Landscapes ◽  
Bending Energy ◽  
Nonlinear Dynamic Response ◽  
One Dimensional ◽  
Doubly Curved Shells ◽  
Doubly Curved ◽  
The Waves

AbstractMulti-welled energy landscapes arising in shells with nonzero Gaussian curvature typically fade away as their thickness becomes larger because of the increased bending energy required for inversion. Motivated by this limitation, we propose a strategy to realize doubly curved shells that are bistable for any thickness. We then study the nonlinear dynamic response of one-dimensional (1D) arrays of our universally bistable shells when coupled by compressible fluid cavities. We find that the system supports the propagation of bidirectional transition waves whose characteristics can be tuned by varying both geometric parameters as well as the amount of energy supplied to initiate the waves. However, since our bistable shells have equal energy minima, the distance traveled by such waves is limited by dissipation. To overcome this limitation, we identify a strategy to realize thick bistable shells with tunable energy landscape and show that their strategic placement within the 1D array can extend the propagation distance of the supported bidirectional transition waves.

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