Digital Discovery
Digital Discovery
The journal publishes research related to chemical, materials, biochemical, biomedical, or biophysical sciences and specific topics include:
Artificial intelligence and other high throughput computational methodologies for molecular, materials and formulation design:
Computer-assisted retrosynthesis
Generative models for scientific design
Machine learning classification and regression models
Quantum algorithms for quantum simulation and data science as applied to molecular and materials discovery
Modern molecular, materials, and biological representations
Molecular, Materials and Chemo- and Bio-informatics
Methods for Bayesian optimization and design of experiments
Advances and applications of interpretable models
Image recognition
Natural language processing
Literature mining tools
Advanced data workflows:
Databases
Data provenance tools
Computational workflow engines
Experimental control software
Ontologies for science
Advances in robotics for science
Novel experimental automation:
New robotic setups
New automated sensors and analytical workflows
Novel synthetic methodologies and workflows that enable higher throughput
High-throughput computational science
Studies where large families of electronic structure or molecular simulations are analyzed for use in experimental and automated applications
Papers at the interface of chemistry and other sciences that involve the following topics:
Directed or accelerated evolution
DNA Encoded Library Technology or novel chemical library technologies
Cryptochemistry
Blockchain-enabled science
Papers that will not be considered are in the areas of low-throughput structural or mechanistic studies using computational chemistry, QM/MM studies of biochemical mechanisms at low throughput, traditional analysis of molecular dynamics trajectory simulations to understand biological conformations, reports or comparisons of electronic structure methods that do not involve machine learning, interpretations of chemical bonding models, and quantum dynamics and spectroscopy simulations at low throughput.
Publisher: Royal Society of Chemistry
ISSN: 2653-098X
Artificial intelligence and other high throughput computational methodologies for molecular, materials and formulation design:
Computer-assisted retrosynthesis
Generative models for scientific design
Machine learning classification and regression models
Quantum algorithms for quantum simulation and data science as applied to molecular and materials discovery
Modern molecular, materials, and biological representations
Molecular, Materials and Chemo- and Bio-informatics
Methods for Bayesian optimization and design of experiments
Advances and applications of interpretable models
Image recognition
Natural language processing
Literature mining tools
Advanced data workflows:
Databases
Data provenance tools
Computational workflow engines
Experimental control software
Ontologies for science
Advances in robotics for science
Novel experimental automation:
New robotic setups
New automated sensors and analytical workflows
Novel synthetic methodologies and workflows that enable higher throughput
High-throughput computational science
Studies where large families of electronic structure or molecular simulations are analyzed for use in experimental and automated applications
Papers at the interface of chemistry and other sciences that involve the following topics:
Directed or accelerated evolution
DNA Encoded Library Technology or novel chemical library technologies
Cryptochemistry
Blockchain-enabled science
Papers that will not be considered are in the areas of low-throughput structural or mechanistic studies using computational chemistry, QM/MM studies of biochemical mechanisms at low throughput, traditional analysis of molecular dynamics trajectory simulations to understand biological conformations, reports or comparisons of electronic structure methods that do not involve machine learning, interpretations of chemical bonding models, and quantum dynamics and spectroscopy simulations at low throughput.
Publisher: Royal Society of Chemistry
ISSN: 2653-098X
Re: Digital Discovery
Thanks thompson!thompson писал(а): ↑Пт апр 11, 2025 3:06 pm2022, Vol.1, issue 1-6
https://www.mediafire.com/file/fllw41dh ... 1.zip/file
Unfold and comment LOST
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Re: Digital Discovery
Thanks thompson!thompson писал(а): ↑Пт апр 11, 2025 2:45 pm2025, Vol.4, issue 1-4
https://www.mediafire.com/file/clata6ed ... 4.zip/file
Unfold and comment 0762-0777.pdf ---> 03 0762-0775.pdf
no LOST/BAD
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Re: Digital Discovery
Thanks thompson!thompson писал(а): ↑Сб апр 12, 2025 3:19 pm2023, Vol.2, issue 1-6
https://www.mediafire.com/file/x20icx6c ... 2.zip/file
Unfold and comment 0087-0895.pdf ---> 0887-0895_GA.pdf
no LOST/BAD
У вас нет необходимых прав для просмотра вложений в этом сообщении.
У нас есть ТАКИЕ приборы! Но мы вам о них не расскажем.
Re: Digital Discovery
Thanks thompson!thompson писал(а): ↑Сб апр 12, 2025 5:46 pm2024, Vol.3, issue 1-12
https://www.mediafire.com/file/whm96k1s ... 3.zip/file
Unfold and comment no LOST/BAD
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У нас есть ТАКИЕ приборы! Но мы вам о них не расскажем.
Re: Digital Discovery
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kill all humans
Re: Digital Discovery
Thanks top_bot!top_bot писал(а): ↑Ср апр 16, 2025 3:05 amSupplements
s2022 v.01.7z s2023 v.02.7zs2024 v.03.7z s2025 v.04 i1-4.7zКод: Выделить всё
https://dropmefiles.com/c3LOV
Код: Выделить всё
https://dropmefiles.com/XI7zN
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