From 0a0d4720b120c111b874d3a6ba316f5800c55e27 Mon Sep 17 00:00:00 2001 From: Simon Billinge Date: Thu, 5 Sep 2024 04:00:12 -0400 Subject: [PATCH 1/6] bob onboarding and a bunch of citations updating --- db/citations.yml | 120 ++++++++++++++++++++++++++++++------------ db/grants.yml | 2 +- db/people.yml | 39 +++++++++++++- db/presentations.yml | 121 ++++++++++++++++++++++++++++++++++++++++--- 4 files changed, 241 insertions(+), 41 deletions(-) diff --git a/db/citations.yml b/db/citations.yml index 9216f4d6..52364b46 100644 --- a/db/citations.yml +++ b/db/citations.yml @@ -386,6 +386,36 @@ anker;npjcm22: url: https://doi.org/10.1038/s41524-022-00896-3 volume: '8' year: '2022' +guo;npjcm24: + ackno: Work in the Lipson group was supported by U.S. National Science Foundation under AI Institute for + Dynamical Systems grant 372 2112085. Work in the Billinge group was supported by the U.S. Department of + Energy, Office of Science, Office of Basic Energy Sciences (DOE-BES) under contract No. DE-SC0024141. + author: + - Gabe Guo + - Judah Goldfeder + - Ling Lan + - Aniv Ray + - Albert Hanming Yang + - Boyuan Chen + - Simon J. L. Billinge + - Hod Lipson + doi: '' + entrytype: article + facility: '' + grant: doeneutron23 + journal: npj Computational Materials + month: '' + nb: '' + number: '' + note: to be published. Available on arXiv + pages: '' + professional_summary: "" + synopsis: '' + tags: ml, structure_solution, modeling + title: + url: https://doi.org/10.1038/s41524-022-00896-3 + volume: '8' + year: '2022' antic;jpcm13: author: - Antic, B. @@ -5468,17 +5498,27 @@ greta;prl13: wwwpub: http://slapper.apam.columbia.edu/bib-eu9iifae/papers/gretarsson_prl13.pdf year: '2013' griff;unpub23: - ackno: Work at Brookhaven National Laboratory was supported by the U.S. Department - of Energy, Office of Science, Office of Basic Energy Sciences, under Contract - No. DE-SC0012704. Use of the Linac Coherent Light Source (LCLS), SLAC National - Accelerator Laboratory, is supported by the U.S. Department of Energy, Office - of Science, Office of Basic Energy Sciences under Contract No. DE-AC02-76SF00515. - This work was supported by the National Institutes of Health grant S10 OD023453. - We would like to thank Andrey A. Yakovenko and Uta Ruett for help with reference - synchrotron measurements of equilibrium CuIr2S4. The measurements were carried - out at the Advanced Photon Source (APS) beamline 11-ID-C, which was supported - by the U. S. Department of Energy, Office of Science, Office of Basic Energy Sciences, - under Contract No. DE-AC02-06CH11357. + ackno: Work at Brookhaven National Laboratory was supported by the US Department + of Energy, Office of Science, Office of Basic Energy Sciences, under contract + no. DE-SC0012704 (J.G., A.F.S., L.W., M.P.M.D., I.R. and S.J.L.B). Sample preparation + utilized the resources of the Center for Functional Nanomaterials at Brookhaven + National Laboratory also funded under contract no. DE-SC0012704. Use of the Linac + Coherent Light Source (LCLS), SLAC National Accelerator Laboratory, is supported + by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, + under contract no. DE-AC0276SF00515 (V.E. and S.B.). The use of the Rayonix 340 + detector at the MFX beamline was supported by the National Institutes of Health + grant S10 OD023453 (S.B.). Work at Argonne National Laboratory (sample synthesis + and characterization) was supported by the US Department of Energy, Office of + Science, Basic Energy Sciences, Materials Science and Engineering Division (J.F.M.). + We gratefully acknowledge support from the US Department of Energy, Office of + Science, under grant no. DE-FG02-04ER46147 (S.D.M. and P.G.E.) and from the US + NSF through the University of Wisconsin Materials Research Science and Engineering + Center (DMR-2309000 and DMR-1720415) (S.D.M. and P.G.E.). Work performed at University + College London was supported by EPSRC (I.R.). We would like to thank A. A. Yakovenko + and U. Ruett for help with the reference synchrotron measurements of equilibrium + CIS. These reference measurements were carried out at the Advanced Photon Source + (APS) beamline 11-ID-C, which was supported by the US Department of Energy, Office + of Science, Office of Basic Energy Sciences, under contract no. DE-AC02-06CH11357. author: - Jack Griffiths - Ana Flávia Suzana @@ -5493,24 +5533,35 @@ griff;unpub23: - Ian Robinson - Simon J. L. Billinge - Emil S. Bozin - doi: '' + doi: 10.1038/s41563-024-01927-8 entrytype: article facility: slac lcls aps 11idc grant: fwp20 journal: Nature Materials - month: tbd + month: jun nb: '' - note: to be published number: '' - pages: '' - professional_summary: '' - synopsis: '' + optnote: to be published + pages: 1041–1047 + professional_summary: A key challenge in materials is understanding how they transition + from one phase to another, the so-called reaction coordinate. In principle, the + ability to measure time-resolved atomic pair distribution functions with sub-picosecond + time resolution could solve this challenge as the PDF can show quantitatively + how atoms move with respect to each other as a following a exciting stimulus. A + major challenge is to carry out these experiments in using the X-ray free electron + lasers (XFELs) that can provide this time resolution in prinicple. This experiment + demonstrates that this is possile, opening the door to future such experiments + on a wide range of materials. In this case, the destruction of an ordered charge + density wave state at the metal-insulator transition of the quantum material, + CuIr2S2, was studied. + synopsis: The first fully quantitative ultra-fast PDF experiment is demonstrated + from data from the LCLS at SLAC tags: ufpdf, cis, dimer, ultra_fast - title: Resolving length scale dependent transient disorder through an ultrafast + title: Resolving length-scale-dependent transient disorder through an ultrafast phase transition - url: '' - volume: '' - year: '2023' + url: https://doi.org/10.1038/s41563-024-01927-8 + volume: '23' + year: '2024' gu;aca19: ackno: This research was supported by the US National Science Foundation (NSF) through grant DMREF-1534910. SB acknowledges support from the National Defense Science @@ -5577,15 +5628,18 @@ gu;aca23: wwwemail: '' wwwpub: '' year: '2023' -gu;unpublished23: - ackno: We would like to thank Dr. Daniel Olds, for assistance during the measurements +gu;npjcm24: + ackno: 'We would like to thank Dr. Daniel Olds, for assistance during the measurements of the experimental PDF data. The work described here was funded by the Next Generation Synthesis Center (GENESIS), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award Number DE-SC0019212. X-ray PDF measurements were conducted on beamline 28-ID-2 of the National Synchrotron Light Source II, a US DOE Office of Science User Facility operated for the DOE Office of Science by Brookhaven National Laboratory under - contract No. DESC0012704. + contract No. DESC0012704. Q.D. is also partially supported by DOE-ASCRDE-SC0022317. + G.E.K received training and support as a part of QuADS: Quantitative Analysis + of Dynamic Structures National Science Foundation Research Traineeship Program, + grant number NSF DGE 1922639.' author: - Ran Gu - Yevgeny Rakita @@ -5599,25 +5653,25 @@ gu;unpublished23: - Karena W. Chapman - Qiang Du - Simon J. L. Billinge - doi: '' + doi: 10.1038/s41524-024-01377-5 entrytype: article facility: nslslii, xpd grant: efrc18 - journal: arXiv - month: tbd + journal: npj Comp. Mater. + month: aug nb: fy24, typeA - note: arXiv:2311.15173 [cond-mat.mtrl-sci] number: '' optannote: '' - pages: '' + optnote: arXiv:2311.15173 [cond-mat.mtrl-sci] + pages: '193' synopsis: stretched and sparse-stretched NMF unsupervised ML algorithms are described and tested against temperature dependent x-ray data from in situ inorganic chemical synthesis experiments. tags: ml, nmf, synthesis, in-situ - title: Stretched Non-negative Matrix Factorization - url: http://arxiv.org/abs/2311.15173 - volume: '' - year: '2023' + title: Stretched non-negative matrix factorization + url: https://doi.org/10.1038/s41524-024-01377-5 + volume: '10' + year: '2024' gualt;jac08: author: - Gualtieri, A. F. diff --git a/db/grants.yml b/db/grants.yml index 3439ad9b..3083cdb2 100644 --- a/db/grants.yml +++ b/db/grants.yml @@ -1195,7 +1195,7 @@ title: Towards a machine readable literature 22_tri: amount: 290000 - awardnr: n/a + awardnr: PO-002332 begin_date: 2023-01-01 end_date: 2024-12-31 funder: Toyota Research Institute diff --git a/db/people.yml b/db/people.yml index 74317e24..c727ed0b 100644 --- a/db/people.yml +++ b/db/people.yml @@ -4676,6 +4676,23 @@ sbillinge: publication list, can be found at http://thebillingegroup.com/ begin_year: 1987 service: + - type: profession + name: External PhD examiner for PhD student Rasmus Stubkjær Christensen of Aarhus + University + month: 12 + year: 2024 + role: member + other: [] + - type: profession + name: Member of the external advisory board, of the FULL-MAP project (Furthering + the development of a materials acceleration platform for sustainable batteries + (combining AI, big data, autonomous synthesis robotics, high throughput testing) + (Batt4EU Partnership)) at Vrije Universiteit Brussels + month: 12 + begin_date: 2024-08-01 + end_date: 2027-07-31 + role: member + other: [] - type: profession name: Review panel for Linear Coherent Light Source month: 4 @@ -5501,6 +5518,26 @@ sharouna-mayer: grp_mtg_active: false name: Sani Harouna-Mayer position: visiting student +sjblee: + active: true + aka: [] + avatar: https://github.com/bobleesj.png + bio: bio + education: [] + email: sl5400@columbia.edu + employment: + - begin_date: 2024-07-28 + end_date: 2024-12-31 + organization: columbiau + position: undergraduate researcher + group: bg + advisor: sbillinge + status: undergrad + github_id: bobleesj + grp_mtg_active: true + name: Sangjoon Bob Lee + orcid_id: 0000-0002-2367-3932 + position: undergraduate researcher smayers: active: false aka: @@ -6148,7 +6185,7 @@ ycchen: email: yucong.c@columbia.edu employment: - begin_date: 2023-10-23 - end_date: 2024-08-31 + end_date: 2025-05-31 organization: columbiau position: masters researcher group: bg diff --git a/db/presentations.yml b/db/presentations.yml index 7724d729..41c028e6 100644 --- a/db/presentations.yml +++ b/db/presentations.yml @@ -5561,7 +5561,7 @@ title: Do materials have a genome, and if they do, what can be done with it? type: invited 2407sb_washingtondc: - abstract: tbd + abstract: na authors: - sbillinge begin_date: 2024-07-30 @@ -5607,10 +5607,56 @@ project: - all status: accepted - title: 'Big box, small box, black box, George Box: some personal thoughts on determination - and interpretation of structural models' + subtitle: Some personal thoughts on determination and interpretation of structural + models + title: Big box, small box, black box, George Box type: invited -2408sb_padovaepdic,italy: +2408sb_padovasoftwarefayre,italy: + abstract: na + authors: + - sbillinge + begin_date: 2024-08-26 + end_date: 2024-08-30 + location: Padova, Italy + meeting_name: Software Fayre of the European Powder Diffraction Conference (EPDIC) + 18 + notes: [] + project: + - all + status: accepted + title: Updates on PDF modeling software with diffpy-cm + type: invited +2409sb_krakow,poland: + abstract: At the heart of materials science studies for next generation materials + is an idea that we want to be studying real materials doing real things, often + in real devices. In practice, this presents a number of key data analysis and + interpretation challenges because it implies we are studying ever more complicated + samples, often in complex heterogeneous environments and in time-resolved operando + setups, and we are interrogating our data for more and more subtle effects such + as microstructures and evolving defects and local structures. Advanced data analysis + algorithms and software are essential for the success of this enterprise. In + this talk I will describe various developments that leverage the power of artificial + intelligence (AI), principally machine learning (ML), to aid in this task. Some + of these powerful tools are clearly ready to be applied more broadly in the community + and others are still in the future but look very promising. They include unsupervised + and supervised machine learning approaches, conventional ML and deep neural networks, + including generative models, as well as approaches for autonomous time-resolved + experimentation. I will lay out various aspects of ML in structure science using + examples from our own work. + authors: + - sbillinge + begin_date: 2024-09-01 + end_date: 2024-09-08 + location: Krakow, Poland + meeting_name: Swedish-German R\ontgen-\AAngstrom cluster (R\AA C) conference on + "X-ray and neutron research on bio-inspired materials and sustainable energy technology + notes: [] + project: + - all + status: accepted + title: '{AI} in material structure research: basics and applications' + type: invited +2409sb_padovaepdic,italy: abstract: At the heart of powder diffraction is the idea that we are studying real materials doing real things, often in real devices. It is now possible to solve single crystal structures from tiny crystals that are smaller than powder grains @@ -5639,6 +5685,69 @@ project: - all status: accepted - title: '{AI} at your service: {AI} as a tool for extracting more science, more easily - from powder diffraction data' + subtitle: '{AI} as a tool for extracting more science, more easily from powder diffraction + data' + title: '{AI} at your service' + type: invited +2411sb_tsukuba,japan: + abstract: At the heart of materials science studies for next generation materials + is an idea that we want to be studying real materials doing real things, often + in real devices. In practice, this presents a number of key data analysis and + interpretation challenges because it implies we are studying ever more complicated + samples, often in complex heterogeneous environments and in time-resolved operando + setups, and we are interrogating our data for more and more subtle effects such + as microstructures and evolving defects and local structures. Advanced data analysis + algorithms and software are essential for the success of this enterprise. Of + particular interest is the study of nanomaterials and materials structure on different + lengthscales. In this talk I will describe various developments that leverage + latest data acquisiont and analysis techniques, sometimes powered by artificial + intelligence (AI) and machine learning (ML), that reveal how materials behave + on different length-scales and sometimes also timescales. The materials studied + include materials for sustainable energy, environmental remediation, and cultural + heritage studies, and techniques range from spatially resolved x-ray and electron + nanostrucuture studies and neutron diffraction and scattering. + authors: + - sbillinge + begin_date: 2024-11-05 + end_date: 2024-11-08 + location: Tsukuba, Japan + meeting_name: Japanese national institute for materials science ({NIMS}) annual + award symposium + notes: + - ian work + - mary rose + - yevgeny work + - ufPDF + - nature materials with Kimber + project: + - all + status: accepted + title: 'Real Materials in Action: studying structure on different length and time-scales' + type: invited +2412sb_kigali,rwanda: + abstract: 'Development of next generation materials for applications in sustainable + energy and beyond require us to study the structure of real materials in real + devices even as they operate: for example, putting operating batteries in the + beam, studying spatially resolved labs-on-chip, doing real-time autonomous experiments + and using computed tomography to see diffraction from cross-sections of bulk samples. + These developments, powered by wonderful synchrotron and neutron source and detector + developments, present major challenges on the data acquisition and analysis side. + I will describe experimental approaches that we have been developing for measuring + and analyzing atomic pair distribution functions (PDF) from synchtrotron x-ray + diffraction data. The experiments are straightforward and broadly accessible + through general user programs at synchrotrons, including mail-in experiments. Software + for analyzing the data can be run on laptop computers and is available free of + charge. I will present recent experimental developments, but also lay out approaches + for getting started doing experiments such as these.' + authors: + - sbillinge + begin_date: 2024-12-16 + end_date: 2024-12-19 + location: Kigali, Rwanda + meeting_name: 'African Materials Research Society (AMRS) Meeting ' + notes: [] + project: + - all + status: accepted + title: Structure-property studies of nano-materials using synchrotron radiation type: invited From 012b86c0bc5a83a5bc03b5b9b43ff3053eb602bf Mon Sep 17 00:00:00 2001 From: Simon Billinge Date: Thu, 5 Sep 2024 04:12:18 -0400 Subject: [PATCH 2/6] fix bug in krakow presentation --- db/presentations.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/db/presentations.yml b/db/presentations.yml index 41c028e6..9b08e267 100644 --- a/db/presentations.yml +++ b/db/presentations.yml @@ -5648,7 +5648,7 @@ begin_date: 2024-09-01 end_date: 2024-09-08 location: Krakow, Poland - meeting_name: Swedish-German R\ontgen-\AAngstrom cluster (R\AA C) conference on + meeting_name: Swedish-German R\o ntgen-\AA ngstrom cluster (R\AA C) conference on "X-ray and neutron research on bio-inspired materials and sustainable energy technology notes: [] project: From 290db5246ec343796b16e8f1839ce518cfbab2d3 Mon Sep 17 00:00:00 2001 From: Simon Billinge Date: Thu, 5 Sep 2024 05:18:04 -0400 Subject: [PATCH 3/6] fixme in broken grants --- db/grants.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/db/grants.yml b/db/grants.yml index 3083cdb2..f83767ad 100644 --- a/db/grants.yml +++ b/db/grants.yml @@ -1216,7 +1216,7 @@ begin_date: 2023-09-01 end_date: 2026-08-31 funder: DOE-BES - narrative: 'The main goal of the project is to develop data analysis and knowledge + narrative: 'Fixme The main goal of the project is to develop data analysis and knowledge extraction strategies to separate signals in complex data from in situ and operando neutron diffraction measurements. In general, operating devices are highly heterogeneous, made up of different components in complex arrangements on micron and millimeter From 2ba38c8bf4ed2bc6083ab1a03ac0aabff553ceae Mon Sep 17 00:00:00 2001 From: Simon Billinge Date: Thu, 5 Sep 2024 05:53:17 -0400 Subject: [PATCH 4/6] remove krakow to get it to pass tests --- db/presentations.yml | 30 ------------------------------ 1 file changed, 30 deletions(-) diff --git a/db/presentations.yml b/db/presentations.yml index 9b08e267..4eba6370 100644 --- a/db/presentations.yml +++ b/db/presentations.yml @@ -5626,36 +5626,6 @@ status: accepted title: Updates on PDF modeling software with diffpy-cm type: invited -2409sb_krakow,poland: - abstract: At the heart of materials science studies for next generation materials - is an idea that we want to be studying real materials doing real things, often - in real devices. In practice, this presents a number of key data analysis and - interpretation challenges because it implies we are studying ever more complicated - samples, often in complex heterogeneous environments and in time-resolved operando - setups, and we are interrogating our data for more and more subtle effects such - as microstructures and evolving defects and local structures. Advanced data analysis - algorithms and software are essential for the success of this enterprise. In - this talk I will describe various developments that leverage the power of artificial - intelligence (AI), principally machine learning (ML), to aid in this task. Some - of these powerful tools are clearly ready to be applied more broadly in the community - and others are still in the future but look very promising. They include unsupervised - and supervised machine learning approaches, conventional ML and deep neural networks, - including generative models, as well as approaches for autonomous time-resolved - experimentation. I will lay out various aspects of ML in structure science using - examples from our own work. - authors: - - sbillinge - begin_date: 2024-09-01 - end_date: 2024-09-08 - location: Krakow, Poland - meeting_name: Swedish-German R\o ntgen-\AA ngstrom cluster (R\AA C) conference on - "X-ray and neutron research on bio-inspired materials and sustainable energy technology - notes: [] - project: - - all - status: accepted - title: '{AI} in material structure research: basics and applications' - type: invited 2409sb_padovaepdic,italy: abstract: At the heart of powder diffraction is the idea that we are studying real materials doing real things, often in real devices. It is now possible to solve From 4caefd67e5d2a43870468a9d21a747e5d577d409 Mon Sep 17 00:00:00 2001 From: Simon Billinge Date: Thu, 5 Sep 2024 06:12:59 -0400 Subject: [PATCH 5/6] add subtitle to regolithrc.json as it is not yet in regolith schema --- db/presentations.yml | 30 ++++++++++++++++++++++++++++++ local/regolithrc.json | 6 ++++++ 2 files changed, 36 insertions(+) diff --git a/db/presentations.yml b/db/presentations.yml index 4eba6370..9b08e267 100644 --- a/db/presentations.yml +++ b/db/presentations.yml @@ -5626,6 +5626,36 @@ status: accepted title: Updates on PDF modeling software with diffpy-cm type: invited +2409sb_krakow,poland: + abstract: At the heart of materials science studies for next generation materials + is an idea that we want to be studying real materials doing real things, often + in real devices. In practice, this presents a number of key data analysis and + interpretation challenges because it implies we are studying ever more complicated + samples, often in complex heterogeneous environments and in time-resolved operando + setups, and we are interrogating our data for more and more subtle effects such + as microstructures and evolving defects and local structures. Advanced data analysis + algorithms and software are essential for the success of this enterprise. In + this talk I will describe various developments that leverage the power of artificial + intelligence (AI), principally machine learning (ML), to aid in this task. Some + of these powerful tools are clearly ready to be applied more broadly in the community + and others are still in the future but look very promising. They include unsupervised + and supervised machine learning approaches, conventional ML and deep neural networks, + including generative models, as well as approaches for autonomous time-resolved + experimentation. I will lay out various aspects of ML in structure science using + examples from our own work. + authors: + - sbillinge + begin_date: 2024-09-01 + end_date: 2024-09-08 + location: Krakow, Poland + meeting_name: Swedish-German R\o ntgen-\AA ngstrom cluster (R\AA C) conference on + "X-ray and neutron research on bio-inspired materials and sustainable energy technology + notes: [] + project: + - all + status: accepted + title: '{AI} in material structure research: basics and applications' + type: invited 2409sb_padovaepdic,italy: abstract: At the heart of powder diffraction is the idea that we are studying real materials doing real things, often in real devices. It is now possible to solve diff --git a/local/regolithrc.json b/local/regolithrc.json index dcf5facd..3a25d47b 100644 --- a/local/regolithrc.json +++ b/local/regolithrc.json @@ -87,6 +87,12 @@ "description": "The zipcode of the school", "required": false, "type": ["string", "integer"]} + }, + "presentations": { + "subtitle": { + "description": "The subtitle", + "required": false, + "type": "string"} } }, "repos": [{"_id": "talk_repo", From 391b2c0a5620d80088eea9d7ac0a62bc812cda28 Mon Sep 17 00:00:00 2001 From: Simon Billinge Date: Thu, 5 Sep 2024 06:39:16 -0400 Subject: [PATCH 6/6] change krakow _id --- db/presentations.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/db/presentations.yml b/db/presentations.yml index 9b08e267..c17d14ca 100644 --- a/db/presentations.yml +++ b/db/presentations.yml @@ -5626,7 +5626,7 @@ status: accepted title: Updates on PDF modeling software with diffpy-cm type: invited -2409sb_krakow,poland: +2409sb_krakow_poland: abstract: At the heart of materials science studies for next generation materials is an idea that we want to be studying real materials doing real things, often in real devices. In practice, this presents a number of key data analysis and