1. A chemistry‐inspired neural network kinetic model for oxidative coupling of methane from high‐throughput data. Issue 6 (22nd January 2022) Authors: Chen, Kexin; Tian, Huijie; Li, Bowen; Rangarajan, Srinivas Journal: AIChE journal Issue: Volume 68:Issue 6(2022) Page Start: n/a Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
2. A computational workflow to discover novel liquid organic hydrogen carriers and their dehydrogenation routes. Issue 10 (10th September 2020) Authors: Paragian, Kristin; Li, Bowen; Massino, Morgan; Rangarajan, Srinivas Journal: Molecular Systems Design and Engineering Issue: Volume 5:Issue 10(2020) Page Start: 1658 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
3. A conceptual study of transfer learning with linear models for data-driven property prediction. (January 2022) Authors: Li, Bowen; Rangarajan, Srinivas Journal: Computers & chemical engineering Issue: Volume 157(2022) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
4. A deep neural network for oxidative coupling of methane trained on high-throughput experimental data. (1st January 2023) Authors: Ziu, Klea; Solozabal, Ruben; Rangarajan, Srinivas; Takáč, Martin Journal: JPhys energy Issue: Volume 5:Number 1(2023) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
5. A diversity maximizing active learning strategy for graph neural network models of chemical properties. Issue 12 (21st September 2022) Authors: Li, Bowen; Rangarajan, Srinivas Journal: Molecular Systems Design and Engineering Issue: Volume 7:Issue 12(2022) Page Start: 1697 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
6. Adsorption of nitrogen‐ and sulfur‐containing compounds on NiMoS for hydrotreating reactions: A DFT and vdW‐corrected study. Issue 12 (17th September 2015) Authors: Rangarajan, Srinivas; Mavrikakis, Manos Journal: AIChE journal Issue: Volume 61:Issue 12(2015:Dec.) Page Start: 4036 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
7. ChemInform Abstract: Computational Chemistry for NH3 Synthesis, Hydrotreating, and NOx Reduction: Three Topics of Special Interest to Haldor Topsoe. Issue 34 (August 2015) Authors: Elnabawy, Ahmed O.; Rangarajan, Srinivas; Mavrikakis, Manos Journal: ChemInform Issue: Volume 46:Issue 34(2015) Page Start: no Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
8. Designing compact training sets for data-driven molecular property prediction through optimal exploitation and exploration. Issue 5 (5th September 2019) Authors: Li, Bowen; Rangarajan, Srinivas Journal: Molecular Systems Design and Engineering Issue: Volume 4:Issue 5(2019) Page Start: 1048 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
9. Designing molecular building blocks for the self-assembly of complex porous networks. Issue 3 (3rd April 2019) Authors: Maula, T. Ann; Hatch, Harold W.; Shen, Vincent K.; Rangarajan, Srinivas; Mittal, Jeetain Journal: Molecular Systems Design and Engineering Issue: Volume 4:Issue 3(2019) Page Start: 644 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
10. DFT based microkinetic modeling of confinement driven [4 + 2] Diels–Alder reactions between ethene and isoprene in H-ZSM5. Issue 24 (9th November 2022) Authors: Rzepa, Christopher; Rangarajan, Srinivas Journal: Catalysis science & technology Issue: Volume 12:Issue 24(2022) Page Start: 7389 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗