---
_id: '12879'
abstract:
- lang: eng
text: Machine learning (ML) has been widely applied to chemical property prediction,
most prominently for the energies and forces in molecules and materials. The strong
interest in predicting energies in particular has led to a ‘local energy’-based
paradigm for modern atomistic ML models, which ensures size-extensivity and a
linear scaling of computational cost with system size. However, many electronic
properties (such as excitation energies or ionization energies) do not necessarily
scale linearly with system size and may even be spatially localized. Using size-extensive
models in these cases can lead to large errors. In this work, we explore different
strategies for learning intensive and localized properties, using HOMO energies
in organic molecules as a representative test case. In particular, we analyze
the pooling functions that atomistic neural networks use to predict molecular
properties, and suggest an orbital weighted average (OWA) approach that enables
the accurate prediction of orbital energies and locations.
acknowledgement: KC acknowledges funding from the China Scholarship Council. KC is
grateful for the TUM graduate school finance support to visit Bingqing Cheng's group
in IST for two months. We also thankfully acknowledge computational resources provided
by the MPCDF Supercomputing Centre.
article_processing_charge: No
article_type: original
author:
- first_name: Ke
full_name: Chen, Ke
id: c636c5ca-e8b8-11ed-b2d4-cc2c37613a8d
last_name: Chen
- first_name: Christian
full_name: Kunkel, Christian
last_name: Kunkel
- first_name: Bingqing
full_name: Cheng, Bingqing
id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
last_name: Cheng
orcid: 0000-0002-3584-9632
- first_name: Karsten
full_name: Reuter, Karsten
last_name: Reuter
- first_name: Johannes T.
full_name: Margraf, Johannes T.
last_name: Margraf
citation:
ama: Chen K, Kunkel C, Cheng B, Reuter K, Margraf JT. Physics-inspired machine learning
of localized intensive properties. Chemical Science. 2023. doi:10.1039/d3sc00841j
apa: Chen, K., Kunkel, C., Cheng, B., Reuter, K., & Margraf, J. T. (2023). Physics-inspired
machine learning of localized intensive properties. Chemical Science. Royal
Society of Chemistry. https://doi.org/10.1039/d3sc00841j
chicago: Chen, Ke, Christian Kunkel, Bingqing Cheng, Karsten Reuter, and Johannes
T. Margraf. “Physics-Inspired Machine Learning of Localized Intensive Properties.”
Chemical Science. Royal Society of Chemistry, 2023. https://doi.org/10.1039/d3sc00841j.
ieee: K. Chen, C. Kunkel, B. Cheng, K. Reuter, and J. T. Margraf, “Physics-inspired
machine learning of localized intensive properties,” Chemical Science.
Royal Society of Chemistry, 2023.
ista: Chen K, Kunkel C, Cheng B, Reuter K, Margraf JT. 2023. Physics-inspired machine
learning of localized intensive properties. Chemical Science.
mla: Chen, Ke, et al. “Physics-Inspired Machine Learning of Localized Intensive
Properties.” Chemical Science, Royal Society of Chemistry, 2023, doi:10.1039/d3sc00841j.
short: K. Chen, C. Kunkel, B. Cheng, K. Reuter, J.T. Margraf, Chemical Science (2023).
date_created: 2023-04-30T22:01:06Z
date_published: 2023-04-10T00:00:00Z
date_updated: 2023-08-01T14:18:10Z
day: '10'
ddc:
- '000'
- '540'
department:
- _id: BiCh
doi: 10.1039/d3sc00841j
external_id:
isi:
- '000971508100001'
file:
- access_level: open_access
checksum: 5eeec69a51e192dcd94b955d84423836
content_type: application/pdf
creator: dernst
date_created: 2023-05-02T07:17:05Z
date_updated: 2023-05-02T07:17:05Z
file_id: '12883'
file_name: 2023_ChemialScience_Chen.pdf
file_size: 1515446
relation: main_file
success: 1
file_date_updated: 2023-05-02T07:17:05Z
has_accepted_license: '1'
isi: 1
language:
- iso: eng
license: https://creativecommons.org/licenses/by/3.0/
month: '04'
oa: 1
oa_version: Published Version
publication: Chemical Science
publication_identifier:
eissn:
- 2041-6539
issn:
- 2041-6520
publication_status: published
publisher: Royal Society of Chemistry
quality_controlled: '1'
scopus_import: '1'
status: public
title: Physics-inspired machine learning of localized intensive properties
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/3.0/legalcode
name: Creative Commons Attribution 3.0 Unported (CC BY 3.0)
short: CC BY (3.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
year: '2023'
...
---
_id: '10350'
abstract:
- lang: eng
text: The misfolding and aberrant aggregation of proteins into fibrillar structures
is a key factor in some of the most prevalent human diseases, including diabetes
and dementia. Low molecular weight oligomers are thought to be a central factor
in the pathology of these diseases, as well as critical intermediates in the fibril
formation process, and as such have received much recent attention. Moreover,
on-pathway oligomeric intermediates are potential targets for therapeutic strategies
aimed at interrupting the fibril formation process. However, a consistent framework
for distinguishing on-pathway from off-pathway oligomers has hitherto been lacking
and, in particular, no consensus definition of on- and off-pathway oligomers is
available. In this paper, we argue that a non-binary definition of oligomers'
contribution to fibril-forming pathways may be more informative and we suggest
a quantitative framework, in which each oligomeric species is assigned a value
between 0 and 1 describing its relative contribution to the formation of fibrils.
First, we clarify the distinction between oligomers and fibrils, and then we use
the formalism of reaction networks to develop a general definition for on-pathway
oligomers, that yields meaningful classifications in the context of amyloid formation.
By applying these concepts to Monte Carlo simulations of a minimal aggregating
system, and by revisiting several previous studies of amyloid oligomers in light
of our new framework, we demonstrate how to perform these classifications in practice.
For each oligomeric species we obtain the degree to which it is on-pathway, highlighting
the most effective pharmaceutical targets for the inhibition of amyloid fibril
formation.
acknowledgement: We are grateful to the Schiff Foundation (AJD), Peterhouse, Cambridge
(TCTM), the Swiss National Science foundation (TCTM), Ramon Jenkins Fellowship,
Sidney Sussex, Cambridge (GM), the Royal Society (AŠ), the Academy of Medical Sciences
and Wellcome Trust (AŠ), the Danish Research Council (MK), the Lundbeck Foundation
(MK), the Swedish Research Council (SL), the Wellcome Trust (TPJK), the Cambridge
Centre for Misfolding Diseases (TPJK), the BBSRC (TPJK), the Frances and Augustus
Newman Foundation (TPJK) for financial support. The research leading to these results
has received funding from the European Research Council under the European Union's
Seventh Framework Programme (FP7/2007-2013) through the ERC grants PhysProt (agreement
no. 337969), MAMBA (agreement no. 340890) and NovoNordiskFonden (SL).
article_processing_charge: No
article_type: original
author:
- first_name: Alexander J.
full_name: Dear, Alexander J.
last_name: Dear
- first_name: Georg
full_name: Meisl, Georg
last_name: Meisl
- first_name: Anđela
full_name: Šarić, Anđela
id: bf63d406-f056-11eb-b41d-f263a6566d8b
last_name: Šarić
orcid: 0000-0002-7854-2139
- first_name: Thomas C. T.
full_name: Michaels, Thomas C. T.
last_name: Michaels
- first_name: Magnus
full_name: Kjaergaard, Magnus
last_name: Kjaergaard
- first_name: Sara
full_name: Linse, Sara
last_name: Linse
- first_name: Tuomas P. J.
full_name: Knowles, Tuomas P. J.
last_name: Knowles
citation:
ama: Dear AJ, Meisl G, Šarić A, et al. Identification of on- and off-pathway oligomers
in amyloid fibril formation. Chemical Science. 2020;11(24):6236-6247. doi:10.1039/c9sc06501f
apa: Dear, A. J., Meisl, G., Šarić, A., Michaels, T. C. T., Kjaergaard, M., Linse,
S., & Knowles, T. P. J. (2020). Identification of on- and off-pathway oligomers
in amyloid fibril formation. Chemical Science. Royal Society of Chemistry.
https://doi.org/10.1039/c9sc06501f
chicago: Dear, Alexander J., Georg Meisl, Anđela Šarić, Thomas C. T. Michaels, Magnus
Kjaergaard, Sara Linse, and Tuomas P. J. Knowles. “Identification of On- and off-Pathway
Oligomers in Amyloid Fibril Formation.” Chemical Science. Royal Society
of Chemistry, 2020. https://doi.org/10.1039/c9sc06501f.
ieee: A. J. Dear et al., “Identification of on- and off-pathway oligomers
in amyloid fibril formation,” Chemical Science, vol. 11, no. 24. Royal
Society of Chemistry, pp. 6236–6247, 2020.
ista: Dear AJ, Meisl G, Šarić A, Michaels TCT, Kjaergaard M, Linse S, Knowles TPJ.
2020. Identification of on- and off-pathway oligomers in amyloid fibril formation.
Chemical Science. 11(24), 6236–6247.
mla: Dear, Alexander J., et al. “Identification of On- and off-Pathway Oligomers
in Amyloid Fibril Formation.” Chemical Science, vol. 11, no. 24, Royal
Society of Chemistry, 2020, pp. 6236–47, doi:10.1039/c9sc06501f.
short: A.J. Dear, G. Meisl, A. Šarić, T.C.T. Michaels, M. Kjaergaard, S. Linse,
T.P.J. Knowles, Chemical Science 11 (2020) 6236–6247.
date_created: 2021-11-26T09:08:19Z
date_published: 2020-06-08T00:00:00Z
date_updated: 2021-11-26T11:21:20Z
day: '08'
doi: 10.1039/c9sc06501f
extern: '1'
external_id:
pmid:
- '32953019'
intvolume: ' 11'
issue: '24'
keyword:
- general chemistry
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc/3.0/
main_file_link:
- open_access: '1'
url: https://pubs.rsc.org/en/content/articlehtml/2020/sc/c9sc06501f
month: '06'
oa: 1
oa_version: Published Version
page: 6236-6247
pmid: 1
publication: Chemical Science
publication_identifier:
eissn:
- 2041-6539
issn:
- 2041-6520
publication_status: published
publisher: Royal Society of Chemistry
quality_controlled: '1'
scopus_import: '1'
status: public
title: Identification of on- and off-pathway oligomers in amyloid fibril formation
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/3.0/legalcode
name: Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
short: CC BY-NC (3.0)
type: journal_article
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
volume: 11
year: '2020'
...
---
_id: '7292'
abstract:
- lang: eng
text: 'Rechargeable Li–O2 batteries have amongst the highest formal energy and could
store significantly more energy than other rechargeable batteries in practice
if at least a large part of their promise could be realized. Realization, however,
still faces many challenges than can only be overcome by fundamental understanding
of the processes taking place. Here, we review recent advances in understanding
the chemistry of the Li–O2 cathode and provide a perspective on dominant research
needs. We put particular emphasis on issues that are often grossly misunderstood:
realistic performance metrics and their reporting as well as identifying reversibility
and quantitative measures to do so. Parasitic reactions are the prime obstacle
for reversible cell operation and have recently been identified to be predominantly
caused by singlet oxygen and not by reduced oxygen species as thought before.
We discuss the far reaching implications of this finding on electrolyte and cathode
stability, electrocatalysis, and future research needs.'
article_processing_charge: No
article_type: original
author:
- first_name: Nika
full_name: Mahne, Nika
last_name: Mahne
- first_name: Olivier
full_name: Fontaine, Olivier
last_name: Fontaine
- first_name: Musthafa Ottakam
full_name: Thotiyl, Musthafa Ottakam
last_name: Thotiyl
- first_name: Martin
full_name: Wilkening, Martin
last_name: Wilkening
- first_name: Stefan Alexander
full_name: Freunberger, Stefan Alexander
id: A8CA28E6-CE23-11E9-AD2D-EC27E6697425
last_name: Freunberger
orcid: 0000-0003-2902-5319
citation:
ama: Mahne N, Fontaine O, Thotiyl MO, Wilkening M, Freunberger SA. Mechanism and
performance of lithium–oxygen batteries – a perspective. Chemical Science.
2017;8(10):6716-6729. doi:10.1039/c7sc02519j
apa: Mahne, N., Fontaine, O., Thotiyl, M. O., Wilkening, M., & Freunberger,
S. A. (2017). Mechanism and performance of lithium–oxygen batteries – a perspective.
Chemical Science. RSC. https://doi.org/10.1039/c7sc02519j
chicago: Mahne, Nika, Olivier Fontaine, Musthafa Ottakam Thotiyl, Martin Wilkening,
and Stefan Alexander Freunberger. “Mechanism and Performance of Lithium–Oxygen
Batteries – a Perspective.” Chemical Science. RSC, 2017. https://doi.org/10.1039/c7sc02519j.
ieee: N. Mahne, O. Fontaine, M. O. Thotiyl, M. Wilkening, and S. A. Freunberger,
“Mechanism and performance of lithium–oxygen batteries – a perspective,” Chemical
Science, vol. 8, no. 10. RSC, pp. 6716–6729, 2017.
ista: Mahne N, Fontaine O, Thotiyl MO, Wilkening M, Freunberger SA. 2017. Mechanism
and performance of lithium–oxygen batteries – a perspective. Chemical Science.
8(10), 6716–6729.
mla: Mahne, Nika, et al. “Mechanism and Performance of Lithium–Oxygen Batteries
– a Perspective.” Chemical Science, vol. 8, no. 10, RSC, 2017, pp. 6716–29,
doi:10.1039/c7sc02519j.
short: N. Mahne, O. Fontaine, M.O. Thotiyl, M. Wilkening, S.A. Freunberger, Chemical
Science 8 (2017) 6716–6729.
date_created: 2020-01-15T12:15:42Z
date_published: 2017-07-31T00:00:00Z
date_updated: 2021-01-12T08:12:49Z
day: '31'
ddc:
- '540'
doi: 10.1039/c7sc02519j
extern: '1'
file:
- access_level: open_access
checksum: 70c7c2ce5430b6e8605ccbf0275f1e80
content_type: application/pdf
creator: dernst
date_created: 2020-01-26T15:04:44Z
date_updated: 2020-07-14T12:47:55Z
file_id: '7363'
file_name: 2017_ChemicalScience_Mahne.pdf
file_size: 992106
relation: main_file
file_date_updated: 2020-07-14T12:47:55Z
has_accepted_license: '1'
intvolume: ' 8'
issue: '10'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 6716-6729
publication: Chemical Science
publication_identifier:
eissn:
- 2041-6539
issn:
- 2041-6520
publication_status: published
publisher: RSC
quality_controlled: '1'
status: public
title: Mechanism and performance of lithium–oxygen batteries – a perspective
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 8
year: '2017'
...
---
_id: '10374'
abstract:
- lang: eng
text: The formation of filaments from naturally occurring protein molecules is a
process at the core of a range of functional and aberrant biological phenomena,
such as the assembly of the cytoskeleton or the appearance of aggregates in Alzheimer's
disease. The macroscopic behaviour associated with such processes is remarkably
diverse, ranging from simple nucleated growth to highly cooperative processes
with a well-defined lagtime. Thus, conventionally, different molecular mechanisms
have been used to explain the self-assembly of different proteins. Here we show
that this range of behaviour can be quantitatively captured by a single unifying
Petri net that describes filamentous growth in terms of aggregate number and aggregate
mass concentrations. By considering general features associated with a particular
network connectivity, we are able to establish directly the rate-determining steps
of the overall aggregation reaction from the system's scaling behaviour. We illustrate
the power of this framework on a range of different experimental and simulated
aggregating systems. The approach is general and will be applicable to any future
extensions of the reaction network of filamentous self-assembly.
acknowledgement: The research leading to these results has received funding from the
European Research Council under the European Union's Seventh Framework Programme
(FP7/2007-2013) through the ERC grant PhysProt (agreement no. 337969) (SL, TPJK),
Sidney Sussex College Cambridge (GM), the Frances and Augusta Newman Foundation
(TPJK), the Biotechnology and Biological Science Research Council (TPJK), the Swedish
Research Council (SL), the Academy of Medical Sciences (AŠ), Wellcome Trust (AŠ),
and the Cambridge Centre for Misfolding Diseases (CMD, TPJK, MV).
article_processing_charge: No
article_type: original
author:
- first_name: Georg
full_name: Meisl, Georg
last_name: Meisl
- first_name: Luke
full_name: Rajah, Luke
last_name: Rajah
- first_name: Samuel A. I.
full_name: Cohen, Samuel A. I.
last_name: Cohen
- first_name: Manuela
full_name: Pfammatter, Manuela
last_name: Pfammatter
- first_name: Anđela
full_name: Šarić, Anđela
id: bf63d406-f056-11eb-b41d-f263a6566d8b
last_name: Šarić
orcid: 0000-0002-7854-2139
- first_name: Erik
full_name: Hellstrand, Erik
last_name: Hellstrand
- first_name: Alexander K.
full_name: Buell, Alexander K.
last_name: Buell
- first_name: Adriano
full_name: Aguzzi, Adriano
last_name: Aguzzi
- first_name: Sara
full_name: Linse, Sara
last_name: Linse
- first_name: Michele
full_name: Vendruscolo, Michele
last_name: Vendruscolo
- first_name: Christopher M.
full_name: Dobson, Christopher M.
last_name: Dobson
- first_name: Tuomas P. J.
full_name: Knowles, Tuomas P. J.
last_name: Knowles
citation:
ama: Meisl G, Rajah L, Cohen SAI, et al. Scaling behaviour and rate-determining
steps in filamentous self-assembly. Chemical Science. 2017;8(10):7087-7097.
doi:10.1039/c7sc01965c
apa: Meisl, G., Rajah, L., Cohen, S. A. I., Pfammatter, M., Šarić, A., Hellstrand,
E., … Knowles, T. P. J. (2017). Scaling behaviour and rate-determining steps in
filamentous self-assembly. Chemical Science. Royal Society of Chemistry.
https://doi.org/10.1039/c7sc01965c
chicago: Meisl, Georg, Luke Rajah, Samuel A. I. Cohen, Manuela Pfammatter, Anđela
Šarić, Erik Hellstrand, Alexander K. Buell, et al. “Scaling Behaviour and Rate-Determining
Steps in Filamentous Self-Assembly.” Chemical Science. Royal Society of
Chemistry, 2017. https://doi.org/10.1039/c7sc01965c.
ieee: G. Meisl et al., “Scaling behaviour and rate-determining steps in filamentous
self-assembly,” Chemical Science, vol. 8, no. 10. Royal Society of Chemistry,
pp. 7087–7097, 2017.
ista: Meisl G, Rajah L, Cohen SAI, Pfammatter M, Šarić A, Hellstrand E, Buell AK,
Aguzzi A, Linse S, Vendruscolo M, Dobson CM, Knowles TPJ. 2017. Scaling behaviour
and rate-determining steps in filamentous self-assembly. Chemical Science. 8(10),
7087–7097.
mla: Meisl, Georg, et al. “Scaling Behaviour and Rate-Determining Steps in Filamentous
Self-Assembly.” Chemical Science, vol. 8, no. 10, Royal Society of Chemistry,
2017, pp. 7087–97, doi:10.1039/c7sc01965c.
short: G. Meisl, L. Rajah, S.A.I. Cohen, M. Pfammatter, A. Šarić, E. Hellstrand,
A.K. Buell, A. Aguzzi, S. Linse, M. Vendruscolo, C.M. Dobson, T.P.J. Knowles,
Chemical Science 8 (2017) 7087–7097.
date_created: 2021-11-29T09:29:31Z
date_published: 2017-08-31T00:00:00Z
date_updated: 2021-11-29T10:00:00Z
day: '31'
ddc:
- '540'
doi: 10.1039/c7sc01965c
extern: '1'
external_id:
pmid:
- '29147538'
intvolume: ' 8'
issue: '10'
keyword:
- general chemistry
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://pubs.rsc.org/en/content/articlelanding/2017/SC/C7SC01965C
month: '08'
oa: 1
oa_version: Published Version
page: 7087-7097
pmid: 1
publication: Chemical Science
publication_identifier:
eissn:
- 2041-6539
issn:
- 2041-6520
publication_status: published
publisher: Royal Society of Chemistry
quality_controlled: '1'
scopus_import: '1'
status: public
title: Scaling behaviour and rate-determining steps in filamentous self-assembly
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/3.0/legalcode
name: Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
short: CC BY-NC (3.0)
type: journal_article
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
volume: 8
year: '2017'
...