Alexei Lapkin

University of Cambridge

United Kingdom

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Articles (28)

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Collaborators (12)

Connor Taylor

Assistant Professor

University of Nottingham

UNITED KINGDOM

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Magda H. Barecka

Assistant Professor

Northeastern University

UNITED STATES

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Wen Liu

Assistant Professor

Nanyang Technological University (NTU)

SINGAPORE

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Simon Rihm

University of Cambridge

UNITED KINGDOM

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Shinichiro Fuse

Professor

Nagoya University

JAPAN

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Jonathan Goodman

Professor of Chemistry

University of Cambridge

UNITED KINGDOM

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Tej Choksi

Assistant Professor

Nanyang Technological University (NTU)

SINGAPORE

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Richard Bourne

Professor of Digital Chemical Manufacturing

University of Leeds

UNITED KINGDOM

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David Woods

University of Southampton

UNITED KINGDOM

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Joel Ager

University of California, Berkeley

UNITED STATES

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Danilo Russo

Assistant Professor

University of Naples Federico II

ITALY

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Kedar Hippalgaonkar

Assistant Professor

Nanyang Technological University (NTU)

SINGAPORE

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Alexei Lapkin

Research Interests

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Articles (28)

Automated generation of mechanistic models for chemical process digital twins using reinforcement learning part II: Compartmentalization and learning-based recalibration

Machine Learning-Driven Optimization of Continuous-Flow Photoredox Amine Synthesis

Investigating the Kinetics of CO2 Mineralization via the Carbonation of CaO in Ammonium Carbonate Solution by Reaction Heat Flow Calorimetry

Tailoring the Morphology of Cellulose Nanocrystals via Controlled Aggregation

Beyond Butler-Volmer equation for CO2 electro-reduction on Cu-based gas diffusion electrodes

Machine learning-guided space-filling designs for high throughput liquid formulation development

RO performance in a mixed solvent system: Analysis of nopinone concentration from a methanol-water solution

Multi-objective Bayesian optimisation using q-noisy expected hypervolume improvement (qNEHVI) for the Schotten–Baumann reaction

Accelerating Formulation Design via Machine Learning: Generating a High-throughput Shampoo Formulations Dataset

ML-SAFT: A machine learning framework for PCP-SAFT parameter prediction

ORDerly: Data Sets and Benchmarks for Chemical Reaction Data

Completing and Balancing Database Excerpted Chemical Reactions with a Hybrid Mechanistic-Machine Learning Approach

pHbot: Self‐Driven Robot for pH Adjustment of Viscous Formulations via Physics‐informed‐ML**

A dynamic knowledge graph approach to distributed self-driving laboratories

A machine learning-enabled process optimization of ultra-fast flow chemistry with multiple reaction metrics

The design and optimization of heterogeneous catalysts using computational methods

A Multi Clone Kinetic Model for characterizing Chinese hamster ovary cell line variability

Energy-Efficient Ethanol Concentration Method for Scalable CO2 Electrolysis

Quantitative In Silico Prediction of the Rate of Protodeboronation by a Mechanistic Density Functional Theory-Aided Algorithm

A Brief Introduction to Chemical Reaction Optimization

Micro-kinetics analysis based on partial reaction networks to compare catalysts performances for methane dry reforming reaction

Reaction Impurity Prediction using a Data Mining Approach**

Accelerated Chemical Reaction Optimization Using Multi-Task Learning

Scalable Palladium-Catalyzed C(sp3)–H Carbonylation of Alkylamines in Batch and Continuous Flow

ERnet: a tool for the semantic segmentation and quantitative analysis of endoplasmic reticulum topology

Shear and Solvent‐Mediated Fabrication of Layered Double‐Hydroxide Superstructures for High‐Rate Supercapacitor Cathodes

Boosting autonomous process design and intensification with formalized domain knowledge

Multiscale modelling of species transport in hydrophilic Nafion®-coated Cu catalysts for CO2 electro-reduction

Collaborators (12)

Connor Taylor

Magda H. Barecka

Wen Liu

Simon Rihm

Shinichiro Fuse

Jonathan Goodman

Tej Choksi

Richard Bourne

David Woods

Joel Ager

Danilo Russo

Kedar Hippalgaonkar

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