Support for the UKCP consortium

Lead Research Organisation: University of Cambridge
Department Name: Materials Science & Metallurgy

Abstract

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
 
Description This Consortium grant provides access to the UK's most powerful supercomputer to a group of researchers across many institutions with the collective aim of applying novel computational methods to key scientific questions: these range from creating new machine learning methods to accelerate materials computations, applied dense hydrogen and silicon, to pushing first principles structure prediction methods to complex chemistries, such at those found in potential new battery cathode materials. Given the volume of work that this grant has supported, it would be true to say that it has shifted the state of the art across a wide range of fields.
Exploitation Route CASTEP, a key UKCP code, is sold commercially by Dassault Systemes, but has recently been made available at no cost to the entire global research community. Other codes, such as AIRSS and SHEAP are available under open source licenses.
Sectors Aerospace

Defence and Marine

Chemicals

Construction

Digital/Communication/Information Technologies (including Software)

Electronics

Energy

Environment

Healthcare

Manufacturing

including Industrial Biotechology

Pharmaceuticals and Medical Biotechnology

Transport
URL https://futurecat.ac.uk/abinitiorandomstructuresearch/
 
Description The open source software AIRSS is increasingly used to generate datasets for ML training of models and benchmarks, from generative structure prediction (https://www.microsoft.com/en-us/research/blog/mattergen-property-guided-materials-design/) to a project to augment the known materials convex hull (https://deepmind.google/discover/blog/millions-of-new-materials-discovered-with-deep-learning/).
First Year Of Impact 2023
Sector Chemicals,Digital/Communication/Information Technologies (including Software),Energy,Pharmaceuticals and Medical Biotechnology
Impact Types Economic
 
Title A Picture of Disorder in Hydrous Wadsleyite - Under the Combined Microscope of Solid-State NMR Spectroscopy and Ab Initio Random Structure Searching (dataset) 
Description  
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? Yes  
URL https://risweb.st-andrews.ac.uk:443/portal/en/datasets/a-picture-of-disorder-in-hydrous-wadsleyite--...
 
Title CCDC 1951694: Experimental Crystal Structure Determination 
Description Related Article: Jingwei Hou, María Laura Ríos Gómez, Andraž Krajnc, Aoife McCaul, Shichun Li, Alice M. Bumstead, Adam F. Sapnik, Zeyu Deng, Rijia Lin, Philip A. Chater, Dean S. Keeble, David A. Keen, Dominique Appadoo, Bun Chan, Vicki Chen, Gregor Mali, Thomas D. Bennett|2020|J.Am.Chem.Soc.|142|3880|doi:10.1021/jacs.9b11639 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL http://www.ccdc.cam.ac.uk/services/structure_request?id=doi:10.5517/ccdc.csd.cc23hwwd&sid=DataCite
 
Title CCDC 1951695: Experimental Crystal Structure Determination 
Description Related Article: Jingwei Hou, María Laura Ríos Gómez, Andraž Krajnc, Aoife McCaul, Shichun Li, Alice M. Bumstead, Adam F. Sapnik, Zeyu Deng, Rijia Lin, Philip A. Chater, Dean S. Keeble, David A. Keen, Dominique Appadoo, Bun Chan, Vicki Chen, Gregor Mali, Thomas D. Bennett|2020|J.Am.Chem.Soc.|142|3880|doi:10.1021/jacs.9b11639 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL http://www.ccdc.cam.ac.uk/services/structure_request?id=doi:10.5517/ccdc.csd.cc23hwxf&sid=DataCite
 
Title CCDC 1951696: Experimental Crystal Structure Determination 
Description Related Article: Jingwei Hou, María Laura Ríos Gómez, Andraž Krajnc, Aoife McCaul, Shichun Li, Alice M. Bumstead, Adam F. Sapnik, Zeyu Deng, Rijia Lin, Philip A. Chater, Dean S. Keeble, David A. Keen, Dominique Appadoo, Bun Chan, Vicki Chen, Gregor Mali, Thomas D. Bennett|2020|J.Am.Chem.Soc.|142|3880|doi:10.1021/jacs.9b11639 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL http://www.ccdc.cam.ac.uk/services/structure_request?id=doi:10.5517/ccdc.csd.cc23hwyg&sid=DataCite
 
Title CCDC 1951697: Experimental Crystal Structure Determination 
Description Related Article: Jingwei Hou, María Laura Ríos Gómez, Andraž Krajnc, Aoife McCaul, Shichun Li, Alice M. Bumstead, Adam F. Sapnik, Zeyu Deng, Rijia Lin, Philip A. Chater, Dean S. Keeble, David A. Keen, Dominique Appadoo, Bun Chan, Vicki Chen, Gregor Mali, Thomas D. Bennett|2020|J.Am.Chem.Soc.|142|3880|doi:10.1021/jacs.9b11639 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL http://www.ccdc.cam.ac.uk/services/structure_request?id=doi:10.5517/ccdc.csd.cc23hwzh&sid=DataCite
 
Title CCDC 2114085: Experimental Crystal Structure Determination 
Description Related Article: Christopher J. H. Smalley, Harriet E. Hoskyns, Colan E. Hughes, Duncan N. Johnstone, Tom Willhammar, Mark T. Young, Christopher J. Pickard, Andrew J. Logsdail, Paul A. Midgley, Kenneth D. M. Harris|2022|Chemical Science|13|5277|doi:10.1039/D1SC06467C 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL http://www.ccdc.cam.ac.uk/services/structure_request?id=doi:10.5517/ccdc.csd.cc28yw9f&sid=DataCite
 
Title CSD 1888648: Experimental Crystal Structure Determination 
Description Related Article: Hayden A. Evans, Zeyu Deng, Ines E. Collings, Yue Wu, Jessica L. Andrews, Kartik Pilar, Joshua M. Tuffnell, Guang Wu, John Wang, Siân E. Dutton, Paul D. Bristowe, Ram Seshadri, Anthony K. Cheetham|2019|Chem.Commun.|55|2964|doi:10.1039/C9CC00118B 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes  
URL http://www.ccdc.cam.ac.uk/services/structure_request?id=doi:10.25505/fiz.icsd.cc21d94x&sid=DataCite
 
Title CSD 1888649: Experimental Crystal Structure Determination 
Description Related Article: Hayden A. Evans, Zeyu Deng, Ines E. Collings, Yue Wu, Jessica L. Andrews, Kartik Pilar, Joshua M. Tuffnell, Guang Wu, John Wang, Siân E. Dutton, Paul D. Bristowe, Ram Seshadri, Anthony K. Cheetham|2019|Chem.Commun.|55|2964|doi:10.1039/C9CC00118B 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes  
URL http://www.ccdc.cam.ac.uk/services/structure_request?id=doi:10.25505/fiz.icsd.cc21d95y&sid=DataCite
 
Title CSD 1888650: Experimental Crystal Structure Determination 
Description Related Article: Hayden A. Evans, Zeyu Deng, Ines E. Collings, Yue Wu, Jessica L. Andrews, Kartik Pilar, Joshua M. Tuffnell, Guang Wu, John Wang, Siân E. Dutton, Paul D. Bristowe, Ram Seshadri, Anthony K. Cheetham|2019|Chem.Commun.|55|2964|doi:10.1039/C9CC00118B 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes  
URL http://www.ccdc.cam.ac.uk/services/structure_request?id=doi:10.25505/fiz.icsd.cc21d96z&sid=DataCite
 
Title CSD 1888651: Experimental Crystal Structure Determination 
Description Related Article: Hayden A. Evans, Zeyu Deng, Ines E. Collings, Yue Wu, Jessica L. Andrews, Kartik Pilar, Joshua M. Tuffnell, Guang Wu, John Wang, Siân E. Dutton, Paul D. Bristowe, Ram Seshadri, Anthony K. Cheetham|2019|Chem.Commun.|55|2964|doi:10.1039/C9CC00118B 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes  
URL http://www.ccdc.cam.ac.uk/services/structure_request?id=doi:10.25505/fiz.icsd.cc21d970&sid=DataCite
 
Title CSD 1888652: Experimental Crystal Structure Determination 
Description Related Article: Hayden A. Evans, Zeyu Deng, Ines E. Collings, Yue Wu, Jessica L. Andrews, Kartik Pilar, Joshua M. Tuffnell, Guang Wu, John Wang, Siân E. Dutton, Paul D. Bristowe, Ram Seshadri, Anthony K. Cheetham|2019|Chem.Commun.|55|2964|doi:10.1039/C9CC00118B 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes  
URL http://www.ccdc.cam.ac.uk/services/structure_request?id=doi:10.25505/fiz.icsd.cc21d981&sid=DataCite
 
Title Data for "Stochastic sampling of quadrature grids for the evaluation of vibrational expectation values" 
Description Data for "Stochastic sampling of quadrature grids for the evaluation of vibrational expectation values" 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? Yes  
 
Title Data for "Structure and metallicity of phase V of hydrogen" 
Description Density functional theory and quantum Monte Carlo input and output files. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://www.repository.cam.ac.uk/handle/1810/332740
 
Title Data set related to the manuscript "Efficient prediction of Nucleus Independent Chemical Shifts for polycyclic aromatic hydrocarbons" 
Description Input/output files for Gaussian calculations, data sets for all plots shown in the manuscript "Efficient prediction of Nucleus Independent Chemical Shifts for polycyclic aromatic hydrocarbons", C code for the NICS calculations through the dipolar model and python code for the NICS calculations through the tight-binding model described in the manuscript. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://zenodo.org/record/3676905
 
Title Data set related to the manuscript "Efficient prediction of Nucleus Independent Chemical Shifts for polycyclic aromatic hydrocarbons" 
Description Input/output files for Gaussian calculations, data sets for all plots shown in the manuscript "Efficient prediction of Nucleus Independent Chemical Shifts for polycyclic aromatic hydrocarbons", C code for the NICS calculations through the dipolar model and python code for the NICS calculations through the tight-binding model described in the manuscript. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://zenodo.org/record/3676904
 
Title Data supporting "Accurate Total Energies from the Adiabatic-Connection Fluctuation-Dissipation Theorem" 
Description This is data associated with the publication "Accurate Total Energies from the Adiabatic-Connection Fluctuation-Dissipation Theorem". Four systems are studied, each of which are detailed in the main paper. The code used to generate all the data is contained in the head directory. 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://www.repository.cam.ac.uk/handle/1810/327641
 
Title Finite field formalism for bulk electrolyte solutions (data set) 
Description All simulations can be run with the LAMMPS code (22 Sept 2017). See also https://github.com/uccasco/FiniteFields for additional source code required to apply the constant D ensemble. Constant E simulations can be performed with in.SPCE.efield. The user will need to replace with the appropriate value of E (along the z direction). Constant D simulations can be performed with in.SPCE.dfield. Likewise, the user will need to replace with the appropriate value of D. Also included are configurations corresponding to different concentrations (these have been obtained from D = 0 simulations). The number of ions pairs and water molecules is given by the filename e.g. 10pair_256wat.data contains 10 ion pairs and 256 water molecules. The name of the configuration file will need to replace the text "" on line 13 of the input files. Note the user may wish to perform shorter simulations for equilibration purposes, especially when changing the value of Dz, or switching to the E ensemble. See included README file. 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes  
 
Title GAP-20 machine learning force field for phosphorus 
Description This dataset contains the force-field parameter files and reference database described in the manuscript "A general-purpose machine-learning force field for bulk and nanostructured phosphorus" (to be published). 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://zenodo.org/record/4003703
 
Title GAP-20 machine learning force field for phosphorus 
Description This dataset contains the force-field parameter files and reference database described in the manuscript "A general-purpose machine-learning force field for bulk and nanostructured phosphorus" (to be published). 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://zenodo.org/record/4003702
 
Title Research Data supporting "Quantifying Chemical Structure and Machine-Learned Atomic Energies in Amorphous and Liquid Silicon" 
Description This file contains additional data supporting the above-mentioned publication. Coordinate files from molecular dynamics simulations and structural relaxations are provided, alongside original data for local energies, all as discussed in the publication. A detailed description may be found in the README.txt file within the archive. 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes  
URL https://www.repository.cam.ac.uk/handle/1810/292653
 
Title Research data supporting "A predictive modelling study of the impact of chemical doping on the strength of a Ag/ZnO interface" 
Description The data and lattice structures used to calculate the interfacial adhesion and bond populations are available in this dataset. 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? Yes  
 
Title Research data supporting "Controlling Ag diffusion in ZnO by donor doping: a first principles study" 
Description The data and lattice structures used to calculate the formation energies and diffusion barriers are available in this dataset. The transition state structures used for charge density analysis are also provided. 
Type Of Material Database/Collection of data 
Year Produced 2017 
Provided To Others? Yes  
 
Title Research data supporting "Data-driven learning and prediction of inorganic crystal structures" 
Description This dataset contains potential parameter files (*.xml) for the different generations of GAP-RSS interatomic potential models described in the article, as well as structural information and DFT-computed reference and testing databases. 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? Yes  
URL https://www.repository.cam.ac.uk/handle/1810/278614
 
Title Research data supporting "De novo exploration and self-guided learning of potential-energy surfaces" 
Description This dataset supports our work on Gaussian Approximation Potential driven random structure searching (GAP-RSS) models for exploring and fitting potential-energy surfaces of materials. It provides, in separate tar archives, an implementation of the methodology and the final GAP-RSS models as reported in the associated publication. 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes  
URL https://www.repository.cam.ac.uk/handle/1810/297743
 
Title Research data supporting "First-principles study of alkali-metal intercalation in disordered carbon anode materials" 
Description Structural data are given as obtained from DFT computations of metal-intercalated carbon structures, as described in the main article. In each coordinate file, the computed energy is also given ("energy" entry in the second line). Individual files are concatenated for each metal species and carbon structure. Files are named according to the naming system in the paper: e.g., "K-structure-2.xyz" corresponds to K intercalation in structural model 2 (Fig. 3c). 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes  
URL https://www.repository.cam.ac.uk/handle/1810/295100
 
Title Research data supporting "High-throughput discovery of high-temperature conventional superconductors" 
Description Crystal structures of the materials listed in Table. 1 of "High-throughput discovery of high-temperature conventional superconductors", generated using ab initio random structure searching (AIRSS). These are the structures as found to exhibit high-Tc superconductivity after an initial geometry optimization at the listed pressure. They are provided in the CASTEP .cell format and can be easily converted to a number of different formats using the C2x software (https://www.c2x.org.uk/). 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://www.repository.cam.ac.uk/handle/1810/326388
 
Title Research data supporting "Investigating Sodium Storage Mechanisms in Tin Anodes: A Combined Pair Distribution Function Analysis, Density Functional Theory, and Solid-State NMR Approach" 
Description Raw and processed PDF, XRD, electrochemistry, ssNMR data and CIF files along with corresponding metadata for all measurements published in the paper "Investigating Sodium Storage Mechanisms in Tin Anodes: A Combined Pair Distribution Function Analysis, Density Functional Theory and Solid-State NMR Approach." Specifically, we provide PDF data as .hdf5 or .tif (raw unprocessed) and .csv (integrated and extracted) files, XRD data as .tif (raw unprocessed) and .csv (integrated and extracted) files, electrochemistry data as .csv (plain text) files, and unprocessed NMR data in the IUPAC standard JCAMP-DX format, processed data available as .csv. We refer the reader to the aforementioned paper for further details. 
Type Of Material Database/Collection of data 
Year Produced 2017 
Provided To Others? Yes  
 
Title Research data supporting "Predicting novel superconducting hydrides using machine learning approaches" 
Description  
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://www.repository.cam.ac.uk/handle/1810/303296
 
Title Research data supporting "Stability and superconductivity of Lanthanum and Yttrium decahydrides" 
Description Structures of LaH10 and YH10 studied in the paper "stability and superconductivity of Lanthanum and Yttrium decahydrides" (full text available here https://arxiv.org/abs/2001.05305). These are the lowest-energy structures resulting from using the AIRSS package (https://www.mtg.msm.cam.ac.uk/Codes/AIRSS), provided as Crystallographic Information (.cif) files. These can be converted to desired formats using the c2x software, available at https://www.c2x.org.uk/. These structures make up the phase diagram for LaH10 and YhH10 between ~200 and 400GPa, and exhibit high-temperature, conventional superconductivity. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://www.repository.cam.ac.uk/handle/1810/307980
 
Title Research data supporting "Structural and vibrational properties of lithium under ambient conditions within density functional theory" 
Description Helmholtz free energies resulting from DFT calculations of Li phases. Results of ab initio random structure searching (AIRSS) calculations. Analysis scripts. All presented in "Structural and vibrational properties of lithium under ambient conditions withindensity functional theory". See individual folders for README files. 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? Yes  
URL https://www.repository.cam.ac.uk/handle/1810/285564
 
Title Research data supporting "Using forces to accelerate first-principles anharmonic vibrational calculations" 
Description This dataset contains data used for testing a new and efficient approach for describing strongly anharmonic systems using a VSCF method. The new method uses calculated force data to improve the mapping of the Born-Oppenheimer surface, an integral part of the problem. This is compared to the previous version of the VSCF method, which did not make use of forces. The systems tested are molecular hydrogen, three phases of solid high pressure hydrogen, and the bcc phases of lithium and zirconium. The dataset consists of significant numbers of density functional theory calculations, performed using CASTEP 8.0, and then the analyses of these results to obtain the anharmonic vibrational energy and wavefunction for each test case for each method. 
Type Of Material Database/Collection of data 
Year Produced 2017 
Provided To Others? Yes  
URL https://www.repository.cam.ac.uk/handle/1810/265354
 
Title Research data supporting 'Strong coupling superconductivity in a quasiperiodic host-guest structure' 
Description Data underlying the figures shown in the publication 'Strong coupling superconductivity in a quasiperiodic host-guest structure', including resistivity versus temperature at different pressures and magnetic fields, the critical-field curve of high pressure bismuth, the high pressure magnetisation of bismuth, and the results of phonon dispersion calculations. 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? Yes  
URL https://www.repository.cam.ac.uk/handle/1810/278535
 
Title Stabilization of AgI's polar surfaces by the aqueous environment, and its implications for ice formation (data set) 
Description See also the README file. This dataset contains three sub-directories: (1) D0o0 -- contains input files for performing simulations at D = 0 (2) DCNC -- contains input files for performing simulations at DCNC (2) ECNC -- contains input files for performing simulations at ECNC All simulations can be run with the LAMMPS code (16 Mar 2018). See also https://github.com/uccasco/FiniteFields for additional source code required to apply the E and D fields. Each directory contains the followings files: (a) init.data -- initial structure for pure water in contact with AgI. (b) in.tip4p2005.equil -- input file for performing the initial equilibration of the system at 252K. (c) in.tip4p2005.cool -- input file for performing the cooling ramp simulation between 252K and 242K. (d) in.tip4p2005.constT -- input file for performing a constant T simulation at 242K. The above files perform simulations with an immobile AgI crystal. The DCNC additionally contains a file "in.tip4p2005.constT.mob" which demonstrates the changes needed to perform a simulation with a mobile AgI crystal. (The other equilibration and cooling input files can be similarly adapted.) The ECNC and DCNC directories also contain a file "init.data.electrolyte" which contains an initial structure for NaCl electrolyte in contact with AgI. Please see Table S1 of the article for values of D and E fields used. AgI.table -- tabulated interatomic potential for AgI crystal. 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes  
 
Title AIRSS 
Description Ab initio Random Structure Searching (AIRSS) is a very simple, yet powerful and highly parallel, approach to structure prediction. The concept was introduced in 2006 and its philosophy more extensively discussed in 2011. Random structures - or more precisely, random "sensible" structures - are generated and then relaxed to nearby local energy minima. Particular success has been found using density functional theory (DFT) for the energies, hence the focus on "ab initio" random structure searching. The sensible random structures are constructed so that they have reasonable densities, and atomic separations. Additionally they may embody crystallographic, chemical or prior experimental/computational knowledge. Beyond these explicit constraints the emphasis is on a broad, uniform, sampling of structure space. AIRSS has been used in a number of landmark studies in structure prediction, from the structure of SiH4 under pressure to providing the theoretical structures which are used to understand dense hydrogen (and anticipating the mixed Phase IV), incommensurate phases in aluminium under terapascal pressures, and ionic phases of ammonia. The approach naturally extends to the prediction clusters/molecules, defects in solids, interfaces and surfaces (interfaces with vacuum). The AIRSS package is tightly integrated with the CASTEP first principles total energy code. However, it is relatively straightforward to modify the scripts to use alternative codes to obtain the core functionality, and examples are provided. The AIRSS package is released under the GPL2 licence. 
Type Of Technology Software 
Year Produced 2017 
Impact It appears that researcher are routinely using AIRSS. 
URL https://www.mtg.msm.cam.ac.uk/Codes/AIRSS
 
Title EDDP 
Description Ephemeral Data Derived Potentials (EDDP): The ddp package contains a suite of tools to construct and test data derived interatomic potentials. They are designed to be used with the airss first principles structure prediction package. Ab initio random structure searching (AIRSS) can be used to generate data, and exploit the generated ddp potentials to potentially accelerate searches. They are referred to as ephemeral data derived potentials as they are designed to be constructed for a particular set of structure searching parameters, discarded and regenerated as those parameters change. The methodology is introduced in Pickard, Ephemeral data derived potentials for random structure search, 2022. 
Type Of Technology Software 
Year Produced 2022 
Open Source License? Yes  
Impact The EDDP package has been downloaded over 140 times since its release - an entirely organic uptake, as the focus has been on exploring its impact locally. Given its compatibility with the CASTEP and AIRSS codes there is scope for significant adoption over time. 
URL https://www.mtg.msm.cam.ac.uk/Codes/EDDP
 
Title Stochastic Hyperspace Embedding and Projection (SHEAP) 
Description Stochastic Hyperspace Embedding And Projection (SHEAP) is a dimensionality reduction method designed for visualising potential energy surfaces. Computational structure prediction can assist the discovery of new materials. One searches for the most stable configurations of a given set of atomic building blocks, which correspond to the deepest regions of an energy landscape-the system's energy as a function of the relative positions of its atoms. To explore these landscapes efficiently, it is important to understand their topologies. However, they exist in spaces with very large numbers of dimensions, making them difficult to visualise. SHEAP uses dimensionality reduction through manifold learning to effectively visualise the distribution of stable structures across a high-dimensional energy landscape. 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact The SHEAP code is being routinely used in our structure searches to map the energy landscape, and help to steer the searches. 
URL https://www.mtg.msm.cam.ac.uk/Codes/sheap