The Future of Materials Exploration: Intelligent synthesis, discovery, characterization, and optimization

LBNL is presently considering ideas for new materials-focused “observatories”— new user facilities that will host future research programs in the energy sciences area. One nascent proposal, with working title “X-LAB” is being spearheaded by the workshop organizers. X-LAB is a concept for a new experimental hall adjacent to the ALS building, dedicated to applications of soft X-ray and tender X-ray spectromicroscopy as direct feedback to synthesis.  A common vacuum envelope encompasses not only the endstations, but also a full suite of automated sample preparation and complementary characterization tools, so that we can automate precise cross correlation of measurements taken on the same set of sample areas at the same well-defined state.

Developers of functional materials can now draw on a limitless variety of possible morphologies and compositions, that far outstrip the capacity of small research groups to efficiently exploit.  Both automation of sample preparation/characterization and  large-scale informatics for data analysis has had a huge impact in the biosciences, but these methods have not been as widely adopted by materials science. At the same time, automation and refinement of materials science research tools such as electron and x-ray imaging enables acquisition of a huge volume of disparate spatially-resolved information, that can be measured in terabytes per individual sample, which is sure to grow further with new capabilities enabled by coherent sources such as ALS-U.  

The intent of this workshop is to discuss these possibilities from a technical perspective, and to engage a broad user community in ideas for the X-LAB scope and science program.  While the focus of this workshop is functional materials studied in vacuo, X-LAB also contains paradigms for discovery and optimization that easily extend to other fields, like chemical or biological sciences.

This 1.5 day workshop will explore the impact of combining synthesis, spatially-resolved synchrotron and non-synchrotron characterization, prediction, and machine learning, in order to begin to answer these questions:

    - How can we design intelligent experiments, which aim from the ground up to accelerate the pace of discovery and optimization of functional materials?

    - Could we program a machine to perform growth and characterization sequences of arbitrary composition and structure, in order to optimize known properties, or discover interesting new ones?

    - What computing tools are needed to manage and cross-correlate properties across many sample morphologies, compositions, and spatial dimensions?

    - How can we bring the information together in an accessible way to encourage tight-knit collaborations of stakeholders from these different fields?

Speakers are encouraged to propose imaginative uses of such a unique facility;  the output of this workshop will contribute to the science case for a major new facility at LBNL.

How to participate

Attendance to the workshop is open to any registered ALS user meeting attendee.  We welcome suggestions from the community for speakers; please click on one of the organizers name below to submit a recommendation for speaker, or for any questions. 

Eli Rotenberg or Alex Hexemer, Advanced Light Source (ALS)

Alex Weber-BargioniShaoul Aloni, or Adam Schwartzberg, Molecular Foundry (MF)

Tentative Workshop Schedule

All talks (except intros) 30 minutes + 10 minutes discussion

Location: B50 Auditorium (same as the main ALS Users' Meeting)

 Tuesday, Oct 4th      
10:35 Chris Roat, Google Plenary TalkHow Google is Accelerating Science 
 14:15  Alex Weber Bargioni, LBNL  Welcome Comments    talk
 14:20  Eli Rotenberg, LBNL  X-LAB Overview  talk
14:40  Emory Chan, LBNL Synthesis-Combinatorial High-throughput design of doped colloidal nanocrystals  talk
 15:20  coffee break + workshop photo      
 15:40  Alex Hexemer  Machine Learning: Expt  
 16:20 John Gregoire, Caltech-JCAP  Synthesis/Discovery High Throughput Synthesis, Screening and Characterization for the Discovery of Solar Fuels Materials  talk
 17:00  ALS Users Meeting Banquet

 Wednesday, Oct 5th       Download
 8:20  coffee      
 8:40 Alex Weber Bargioni    Overview   talk
 9:00 Dula Parkinson, LBNL Data Mining: Expt Gathering, linking, organizing, and mining data at the ALS talk
 9:40  Ali Javey UCB/LBNL     Synthesis / Characterization Characterization and Passivation of Defects in Monolayer Semiconductors  talk
 10:20 coffee break      
 10:40 Ryan (Young-kook) Yoo, Park Systems Inc.   Characterization High Accuracy Atomic Force Microscope with Self-Optimizing Scan Control  
 11:20 Sean Fackler LBNL-JCAP      Discovery / User Tools Developing software for NEXAFS analysis and results dissemination  talk
 12:00 Joey Montoya LBNL-MP   Materials Genome Project  The Materials Project: Opportunities and Challenges in High-throughput Computational Materials Science  talk
 12:40 Lunch      
 13:40 Steve Louie UCB/LBNL  Computer Design of Materials C2SEPEM: Center for Computational Study of Excited-State Phenomena in Energy Materials  talk
 14:20 Martin Cenek, U. Alaska  Discovery / Characterization Salmon and Functional Materials: Knowledge Discovery in Coupled Socio-Ecological Systems and Big Data.  talk
 15:00 Kyle Michel, Citrine Informatics Data Mining / Search The Citrination Platform: Materials Data Storage, Search, and Analytics talk
 15:40 coffee break      
 16:00 Chris Tassone, SLAC  Data Mgmt/Machine Learning SMASH-ML: Building a pipeline to enable automated data analysis and experimental control  talk
 16:40 Nicolas Schwarz, APS Data Mgmt/Machine Learning  Advances in Data Analysis and Management for Materials Exploration at the APS  talk
 17:20 Kevin Yager, BNL-CFN Data Mgmt/Machine Learning Towards an Autonomous X-ray Scattering Beamline  talk
 18:00 Workshop Ends      

user meeting main page: here
Subpages (1): abstract_r_yoo