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The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future.
The locus model of search and its use in image interpretation
Rubin, S. M. and Reddy, R · 1977
Earlier work this paper cites.
Smiles, a chemical language and information system. 1. introduction to methodology and encoding rules
Weininger, D · 1988
Earlier work this paper cites.
Smiles. 2. algorithm for generation of unique smiles notation
Weininger, D., Weininger, A., and Weininger, J. L · 1989
Earlier work this paper cites.
Generalized gradient approximation for the exchange-correlation hole of a many-electron system
Perdew, J. P., Burke, K., and Wang, Y · 1996
Earlier work this paper cites.
Biodiesel production viaacid catalysis
Canakci, M. and Van Gerpen, J · 1999
Earlier work this paper cites.
Electronic structure and catalysis on metal surfaces
Greeley, J., Nørskov, J. K., and Mavrikakis, M · 2002
Earlier work this paper cites.
In-situ xps study for reaction mechanism of methanol decomposition over cu-ni/zn catalyst
Xi, J., Wang, Z., Wang, W., and Lu, G · 2002
Earlier work this paper cites.
Principles of heterogeneous catalysis
Dumesic, J. A., Huber, G. W., and Boudart, M · 2008
Earlier work this paper cites.
Quantum espresso: a modular and open-source software project for quantum simulations of materials
Giannozzi, P., Baroni, S., Bonini, N., Calandra, M., Car, R., Cavazzoni, C., Ceresoli, D., Chiarotti, G. L., Cococcioni, M., Dabo, I., et al · 2009
Earlier work this paper cites.
The open catalyst 2020 (oc20) dataset and community challenges. arxiv
Chanussot, L., Das, A., Goyal, S., Lavril, T., Shuaibi, M., Riviere, M., Tran, K., Heras-Domingo, J., Ho, C., Hu, W., et al · 2010
Earlier work this paper cites.
A consistent and accurate ab initio parametrization of density functional dispersion correction (dft-d) for the 94 elements h-pu
Grimme, S., Antony, J., Ehrlich, S., and Krieg, H · 2010
Earlier work this paper cites.
Density functional theory in surface chemistry and catalysis
Nørskov, J. K., Abild-Pedersen, F., Studt, F., and Bligaard, T · 2011
Earlier work this paper cites.
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
Jain, A., Ong, S. P., Hautier, G., Chen, W., Richards, W. D., Dacek, S., Cholia, S., Gunter, D., Skinner, D., Ceder, G., and Persson, K. A · 2013
Earlier work this paper cites.
Pseudopotentials periodic table: From h to pu
Dal Corso, A · 2014
Earlier work this paper cites.
A review of dry (co2) reforming of methane over noble metal catalysts
Pakhare, D. and Spivey, J · 2014
Earlier work this paper cites.
The cu–zno synergy in methanol synthesis from CO 2 \text{CO}{\vphantom{\text{X}}}_{\smash[t]{\text{2}}} , part 2: Origin of the methanol and co selectivities explained by experimental studies and a sphere contact quantification model in randomly packed binary mixtures on cu–zno coprecipitate catalysts
Tisseraud, C., Comminges, C., Belin, T., Ahouari, H., Soualah, A., Pouilloux, Y., and Le Valant, A · 2015
Earlier work this paper cites.
Co 2 conversion by reverse water gas shift catalysis: comparison of catalysts, mechanisms and their consequences for co 2 conversion to liquid fuels
Daza, Y. A. and Kuhn, J. N · 2016
Earlier work this paper cites.
Advanced capabilities for materials modelling with quantum espresso
Giannozzi, P., Andreussi, O., Brumme, T., Bunau, O., Nardelli, M. B., Calandra, M., Car, R., Cavazzoni, C., Ceresoli, D., Cococcioni, M., et al · 2017
Earlier work this paper cites.
Tuning selectivity of co2 hydrogenation reactions at the metal/oxide interface
Kattel, S., Liu, P., and Chen, J. G · 2017
Earlier work this paper cites.
The atomic simulation environment—a python library for working with atoms
Larsen, A. H., Mortensen, J. J., Blomqvist, J., Castelli, I. E., Christensen, R., Dułak, M., Friis, J., Groves, M. N., Hammer, B., Hargus, C., Hermes, E. D., Jennings, P. C., Jensen, P. B., Kermode, J., Kitchin, J. R., Kolsbjerg, E. L., Kubal, J., Kaasbjerg, K., Lysgaard, S., Maronsson, J. B., Maxson, T., Olsen, T., Pastewka, L., Peterson, A., Rostgaard, C., Schiøtz, J., Schütt, O., Strange, M., Thygesen, K. S., Vegge, T., Vilhelmsen, L., Walter, M., Zeng, Z., and Jacobsen, K. W · 2017
Earlier work this paper cites.
Sustainable conversion of carbon dioxide: an integrated review of catalysis and life cycle assessment
Artz, J., Müller, T. E., Thenert, K., Kleinekorte, J., Meys, R., Sternberg, A., Bardow, A., and Leitner, W · 2018
Earlier work this paper cites.
Challenges and prospects in solar water splitting and co2 reduction with inorganic and hybrid nanostructures
Stolarczyk, J. K., Bhattacharyya, S., Polavarapu, L., and Feldmann, J · 2018
Earlier work this paper cites.
Theoretical insights into heterogeneous (photo) electrochemical co2 reduction
Xu, S. and Carter, E. A · 2018
Earlier work this paper cites.
Pytorch: An imperative style, high-performance deep learning library
Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., Desmaison, A., Kopf, A., Yang, E., DeVito, Z., Raison, M., Tejani, A., Chilamkurthy, S., Steiner, B., Fang, L., Bai, J., and Chintala, S · 2019
Earlier work this paper cites.
Molecular transformer: a model for uncertainty-calibrated chemical reaction prediction
Schwaller, P., Laino, T., Gaudin, T., Bolgar, P., Hunter, C. A., Bekas, C., and Lee, A. A · 2019
Earlier work this paper cites.
Ensemble effect in bimetallic electrocatalysts for co2 reduction
Wang, Y., Cao, L., Libretto, N. J., Li, X., Li, C., Wan, Y., He, C., Lee, J., Gregg, J., Zong, H., Su, D., Miller, J. T., Mueller, T., and Wang, C · 2019
Earlier work this paper cites.
Chemberta: Large-scale self-supervised pretraining for molecular property prediction
Chithrananda, S., Grand, G., and Ramsundar, B · 2020
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Improving the cu/zno-based catalysts for carbon dioxide hydrogenation to methanol, and the use of methanol as a renewable energy storage media
Etim, U. J., Song, Y., and Zhong, Z · 2020
Cited alongside, same era.
Molecular representation learning with language models and domain-relevant auxiliary tasks
Fabian, B., Edlich, T., Gaspar, H., Segler, M., Meyers, J., Fiscato, M., and Ahmed, M · 2020
Cited alongside, same era.
Aiida 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance
Huber, S. P., Zoupanos, S., Uhrin, M., Talirz, L., Kahle, L., Häuselmann, R., Gresch, D., Müller, T., Yakutovich, A. V., Andersen, C. W., et al · 2020
Cited alongside, same era.
Self-referencing embedded strings (selfies): A 100% robust molecular string representation
Protranslator: zero-shot protein function prediction using textual description
Xu, H. and Wang, S · 2022
Later among the works it cites.
A deep-learning system bridging molecule structure and biomedical text with comprehension comparable to human professionals
Zeng, Z., Yao, Y., Liu, Z., and Sun, M · 2022
Later among the works it cites.
Emergent autonomous scientific research capabilities of large language models
Boiko, D. A., MacKnight, R., and Gomes, G · 2023
Later among the works it cites.
Chemcrow: Augmenting large-language models with chemistry tools
Bran, A. M., Cox, S., White, A. D., and Schwaller, P · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
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Krenn, M., Häse, F., Nigam, A., Friederich, P., and Aspuru-Guzik, A · 2020
Cited alongside, same era.
An introduction to electrocatalyst design using machine learning for renewable energy storage
Zitnick, C. L., Chanussot, L., Das, A., Goyal, S., Heras-Domingo, J., Ho, C., Hu, W., Lavril, T., Palizhati, A., Riviere, M., et al · 2020
Cited alongside, same era.
Open catalyst 2020 (oc20) dataset and community challenges
Chanussot*, L., Das*, A., Goyal*, S., Lavril*, T., Shuaibi*, M., Riviere, M., Tran, K., Heras-Domingo, J., Ho, C., Hu, W., Palizhati, A., Sriram, A., Wood, B., Yoon, J., Parikh, D., Zitnick, C. L., and Ulissi, Z · 2021
Cited alongside, same era.
Text2Mol: Cross-modal molecule retrieval with natural language queries
Edwards, C., Zhai, C., and Ji, H · 2021
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Gemnet: Universal directional graph neural networks for molecules
Gasteiger, J., Becker, F., and Günnemann, S · 2021
Cited alongside, same era.
Heterogeneous catalysis: enabling a sustainable future, 2021
Hu, X. and Yip, A. C · 2021
Cited alongside, same era.
Methanol economy and net zero emissions: critical analysis of catalytic processes, reactors and technologies
Mondal, U. and Yadav, G. D · 2021
Cited alongside, same era.
Mapping the space of chemical reactions using attention-based neural networks
Schwaller, P., Probst, D., Vaucher, A. C., Nair, V. H., Kreutter, D., Laino, T., and Reymond, J.-L · 2021
Cited alongside, same era.
Cao, H., Liu, Z., Lu, X., Yao, Y., and Li, Y · 2023
Later among the works it cites.
Group selfies: a robust fragment-based molecular string representation
Cheng, A. H., Cai, A., Miret, S., Malkomes, G., Phielipp, M., and Aspuru-Guzik, A · 2023
Later among the works it cites.
Unifying molecular and textual representations via multi-task language modelling
Christofidellis, D., Giannone, G., Born, J., Winther, O., Laino, T., and Manica, M · 2023
Later among the works it cites.
Mol-instructions: A large-scale biomolecular instruction dataset for large language models
Fang, Y., Liang, X., Zhang, N., Liu, K., Huang, R., Chen, Z., Fan, X., and Chen, H · 2023
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What can large language models do in chemistry? a comprehensive benchmark on eight tasks
Guo, T., Guo, K., Nan, B., Liang, Z., Guo, Z., Chawla, N. V., Wiest, O., and Zhang, X · 2023
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Reasoning with language model is planning with world model
Hao, S., Gu, Y., Ma, H., Hong, J. J., Wang, Z., Wang, D. Z., and Hu, Z · 2023
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Knowledge-enhanced biomedical language models
Lai, T. M., Zhai, C., and Ji, H · 2023
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Transition into net-zero carbon community from fossil fuels: Life cycle assessment of light-driven co2 conversion to methanol using graphitic carbon nitride
Ling, G. Z. S., Foo, J. J., Tan, X.-Q., and Ong, W.-J · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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Enhancing activity prediction models in drug discovery with the ability to understand human language
Seidl, P., Vall, A., Hochreiter, S., and Klambauer, G · 2023
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Sprueill, H. W., Edwards, C., Olarte, M. V., Sanyal, U., Ji, H., and Choudhury, S · 2023
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Unlocking the potential of CO 2 \text{CO}{\vphantom{\text{X}}}_{\smash[t]{\text{2}}} hydrogenation into valuable products using noble metal catalysts: A comprehensive review
Tawalbeh, M., Javed, R. M. N., Al-Othman, A., Almomani, F., and Ajith, S · 2023
Later among the works it cites.
Llama 2: Open foundation and fine-tuned chat models
Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., et al · 2023
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Can we quickly learn to “translate” bioactive molecules with transformer models?
Tysinger, E. P., Rai, B. K., and Sinitskiy, A. V · 2023
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High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation
Unsleber, J. P., Liu, H., Talirz, L., Weymuth, T., Mörchen, M., Grofe, A., Wecker, D., Stein, C. J., Panyala, A., Peng, B., et al · 2023
Later among the works it cites.
Protst: Multi-modality learning of protein sequences and biomedical texts
Xu, M., Yuan, X., Miret, S., and Tang, J · 2023
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Tree of thoughts: Deliberate problem solving with large language models
Yao, S., Yu, D., Zhao, J., Shafran, I., Griffiths, T. L., Cao, Y., and Narasimhan, K · 2023
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Drugassist: A large language model for molecule optimization
Ye, G., Cai, X., Lai, H., Wang, X., Huang, J., Wang, L., Liu, W., and Zeng, X · 2023
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Artificial intelligence for science in quantum, atomistic, and continuum systems
Zhang, X., Wang, L., Helwig, J., Luo, Y., Fu, C., Xie, Y., Liu, M., Lin, Y., Xu, Z., Yan, K., et al · 2023
Later among the works it cites.
Gimlet: A unified graph-text model for instruction-based molecule zero-shot learning
Zhao, H., Liu, S., Ma, C., Xu, H., Fu, J., Deng, Z.-H., Kong, L., and Liu, Q · 2023
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Chemdfm: Dialogue foundation model for chemistry
Zhao, Z., Ma, D., Chen, L., Sun, L., Li, Z., Xu, H., Zhu, Z., Zhu, S., Fan, S., Shen, G., et al · 2024
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