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Hydrophilic microporous membranes for selective ion separation and flow-battery energy storage

Nature materials, 2020-02, Vol.19 (2), p.195-202

2020

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stk: An extendable Python framework for automated molecular and supramolecular structure assembly and discovery

The Journal of chemical physics, 2021-06, Vol.154 (21), p.214102-214102

2021

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Machine Learning for Organic Cage Property Prediction

Chemistry of materials, 2019-02, Vol.31 (3), p.714-727

2019

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Computationally-inspired discovery of an unsymmetrical porous organic cage

Nanoscale, 2018-12, Vol.10 (47), p.22381-22388

2018

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Computational discovery of molecular C60 encapsulants with an evolutionary algorithm

Communications chemistry, 2020-01, Vol.3 (1), p.10-10, Article 10

2020

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Author Correction: Hydrophilic microporous membranes for selective ion separation and flow-battery energy storage

Nature materials, 2020-02, Vol.19 (2), p.251-251

2020

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stk: A python toolkit for supramolecular assembly

Journal of computational chemistry, 2018-09, Vol.39 (23), p.1931-1942

2018

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High-Throughput Screening Approach for the Optoelectronic Properties of Conjugated Polymers

Journal of chemical information and modeling, 2018-12, Vol.58 (12), p.2450-2459

2018

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An evolutionary algorithm for the discovery of porous organic cages

Chemical science (Cambridge), 2018-12, Vol.9 (45), p.8513-8527

2018

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Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks

Physical chemistry chemical physics : PCCP, 2020-06, Vol.22 (23), p.1341-1348

2020

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An evolutionary algorithm for the discovery of porous organic cagesElectronic supplementary information (ESI) available: Further details about the fitness function calculation, setup of optimization runs, and the properties of the cages found in the final population for all the case studies. The structure files of the top five candidates in each run are also provided. See DOI: 10.1039/c8sc03560a

2018-11

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An evolutionary algorithm for the discovery of porous organic cages† †Electronic supplementary information (ESI) available: Further details about the fitness function calculation, setup of optimization runs, and the properties of the cages found in the final population for all the case studies. The structure files of the top five candidates in each run are also provided. See DOI: 10.1039/c8sc03560a

Chemical science (Cambridge), 2018-09, Vol.9 (45), p.8513-8527

2018

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Maximising the hydrogen evolution activity in organic photocatalysts by co-polymerisation

Journal of materials chemistry. A, Materials for energy and sustainability, 2018, Vol.6 (25), p.11994-12003

2018

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Materials Precursor Score: Modeling Chemists’ Intuition for the Synthetic Accessibility of Porous Organic Cage Precursors

Journal of chemical information and modeling, 2021-09, Vol.61 (9), p.4342-4356

2021

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Streamlining the automated discovery of porous organic cages

Chemical science (Cambridge), 2024-05, Vol.15 (17), p.6331-6348

2024

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Computational workflow for steric assessment using the electric field-derived size

Electronic Structure, 2023-12, Vol.5 (4), p.45004

2023

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Computationally-inspired discovery of an unsymmetrical porous organic cageElectronic supplementary information (ESI) available: Full high throughput synthetic and experimental details, gas sorption, TGA, and NMR data, together with computational methodology details, structural and electronic properties for all 36 isomers, structures of all of the 36 DFT optimised isomers, and the amorphous structure model. See DOI: 10.1039/c8nr06868b

2018-12

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Computational discovery of molecular C 60 encapsulants with an evolutionary algorithm

Communications chemistry, 2020-01, Vol.3 (1), p.10

2020

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Hydrophilic microporous membranes for selective ion separation and flow-battery energy storage

Nature materials, 2019-12, Vol.19 (2)

2019

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Maximising the hydrogen evolution activity in organic photocatalysts by co-polymerisationElectronic supplementary information (ESI) available: Further synthetic details, polymer characterisation, TCSPC data, photocatalysis results, (TD-)DFT results, xyz coordinates and DFT energies of relevant structures. See DOI: 10.1039/c8ta04186e

2018-06

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Evaluating the Emotional State of a User Using a Webcam

International journal of interactive multimedia and artificial intelligence, 2016-09, Vol.4 (1), p.61

2016

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Evaluating the Emotional State of a User Using a Webcam

International journal of interactive multimedia and artificial intelligence, 2016-09, Vol.4 (1), p.61-68

2016

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Hydrophilic microporous membranes for selective ion separation and flow-battery energy storage

stk: An extendable Python framework for automated molecular and supramolecular structure assembly and discovery

Machine Learning for Organic Cage Property Prediction

Computationally-inspired discovery of an unsymmetrical porous organic cage

Computational discovery of molecular C60 encapsulants with an evolutionary algorithm

Author Correction: Hydrophilic microporous membranes for selective ion separation and flow-battery energy storage

stk: A python toolkit for supramolecular assembly

High-Throughput Screening Approach for the Optoelectronic Properties of Conjugated Polymers

An evolutionary algorithm for the discovery of porous organic cages

Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks

Maximising the hydrogen evolution activity in organic photocatalysts by co-polymerisation

Materials Precursor Score: Modeling Chemists’ Intuition for the Synthetic Accessibility of Porous Organic Cage Precursors

Streamlining the automated discovery of porous organic cages

Computational workflow for steric assessment using the electric field-derived size

Computational discovery of molecular C 60 encapsulants with an evolutionary algorithm

Hydrophilic microporous membranes for selective ion separation and flow-battery energy storage

Evaluating the Emotional State of a User Using a Webcam

Evaluating the Emotional State of a User Using a Webcam

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