Gareth Conduit
Email  gjc29abc@a@bc.comcam.ac.uk

Publications

My publications are curated below in six categories: materials & chemicals, alloy design, pharmaceuticals & healthcare, solid state quantum physics, ultracold atomic gases, and visual perception. Publication metrics are available at Google Scholar. Six of these publications compose my PhD thesis. A pdf copy of any publication may be downloaded by clicking on the image of the paper.

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Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

M.L. Evans, J. Bergsma, A. Merkys, C.W. Andersen, O.B. Andersson, D. Beltrán, E. Blokhin, T.M. Boland, R. Castañeda-Balderas, K. Choudhary, A. Díaz Díaz, R. Domínguez-García, H. Eckert, K. Eimre, M.E.F. Montero, A.M. Krajewski, J.J. Mortensen, J.M. Nápoles-Duarte, J. Pietryga, J. Qi, F.J.T. Carrillo, A. Vaitkus, J. Yu, A. Zettel, P.B. Castro, J. Carlsson, T.F.T. Cerqueira, S. Divilov, H. Hajiyani, F. Hanke, K. Jose, C. Oses, J. Riebesell, J. Schmidt, D. Winston, C. Xie, X. Yang, S. Bonella, S. Botti, S. Curtarolo, C. Draxl, L.E. Fuentes-Cobas, A. Hospital, Z.-K. Liu, M.A.L. Marques, N. Marzari, A.J. Morris, S.P. Ong, M. Orozco, K.A. Persson, K.S. Thygesen, C. Wolverton, M. Scheidgen, C. Toher, G.J. Conduit, G. Pizzi, S. Gražulis, G.-M. Rignanese & R. Armiento

Digital Discovery 3, 1509 (2024)

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Artificial Intelligence (AI) Futures: India-UK Collaborations Emerging from the 4th Royal Society Yusuf Hamied Workshop

Y.K. Dwivedi, L. Hughes, H.K.D.H. Bhadeshia, S. Ananiadou, A.G. Cohn, J.M. Cole, G.J. Conduit, M.S. Desarkar & X. Wang

International Journal of Information Management 76 (2024)

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A game theory-inspired algorithm for automating the design of non-periodic integral 3D woven composite preforms without scale limitations using a manufacturing-based parameterization

Z. Wang, B.N. Cox, S.J.S/O. Kuehsamy, M.H. Jhon, O. Sudre, N. Sridhar & G.J. Conduit

Computer-Aided Design 167, 103637 (2023)

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Probabilistic selection and design of concrete using machine learning

J.C. Forsdyke, B. Zviazhynski, J.M. Lees & G.J. Conduit

Data-Centric Engineering 4, e9 (2023)

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Unveil the unseen: exploit information hidden in noise

B. Zviazhynski & G.J. Conduit

Applied Intelligence 53, 11966 (2023)

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Formulation and manufacturing optimization of lithium-ion graphite-based electrodes via machine learning

S.X. Drakopoulos, A. Gholamipour-Shirazi, P. MacDonald, R.C. Parini, C.D. Reynolds, D.L. Burnett, B. Pye, K.B. O'Regan, G. Wang, T.M. Whitehead, G.J. Conduit, A. Cazacu & E. Kendrick

Cell Reports Physical Science 2, 100683 (2021)

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OPTIMADE: an API for exchanging materials data

C.W. Andersen, R. Armiento, E. Blokhin, G.J. Conduit, S. Dwaraknath, M.L. Evans, A. Fekete, A. Gopakumar, S. Gražulis, A. Merkys, F. Mohamed, C. Oses, G. Pizzi, G.-M. Rignanese, M. Scheidgen, L. Talirz, C. Toher, D. Winston, R. Aversa, K. Choudhary, P. Colinet, S. Curtarolo, D. Di Stefano, C. Draxl, S. Er, M. Esters, M. Fornari, M. Giantomassi, M. Govoni, G. Hautier, V. Hegde, M.K. Horton, P. Huck, G. Huhs, J. Hummelshøj, A. Kariryaa, B. Kozinsky, S. Kumbhar, M. Liu, N. Marzari, A.J. Morris, A. Mostofi, K.A. Persson, G. Petretto, T. Purcell, F. Ricci, F. Rose, M. Scheffler, D. Speckhard, M. Uhrin, A. Vaitkus, P. Villars, D. Waroquiers, C. Wolverton, M. Wu & X. Yang

Nature Scientific Data 8, 217 (2021) and Research Highlight in Nature Review Materials (2021)

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OPTIMADE API specification

C. Andersen, R. Armiento, E. Blokhin, G.J. Conduit, S. Dwaraknath, M.L. Evans, A. Fekete, A. Gopakumar, S. Gražulis, V. Hegde, M. Horton, A. Merkys, F. Mohamed, A. Morris, C. Oses, G. Pizzi, T. Purcell, G.-M. Rignanese, M. Scheffler, M. Scheidgen, L. Talirz, C. Toher, M. Uhrin; D. Winston & C. Wolverton

doi:10.5281/zenodo.4195050

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Enhancing NEMD with improved sampling of shear rates to model viscosity and correction of systematic errors in modelling density: Application to linear and light branched alkanes

P. Santak & G.J. Conduit

Journal of Chemical Physics 153, 014102 (2020)

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Predicting the State of Charge and Health of Batteries using Data-Driven Machine Learning

M.-F. Ng, J. Zhao, Q. Yan, G.J. Conduit & Z.W. Seh

Nature Machine Intelligence 2, 161 (2020)

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Fragment Graphical Variational AutoEncoding for Screening Molecules with Small Data

J. Armitage, L.J. Spalek, M. Nguyen, M. Nikolka, I. Jacobs, L. Marañón, I. Nasrallah, G. Schweicher, I. Dimov, D. Simatos, I. McCulloch, C.B. Nelson, G.J. Conduit & H. Sirringhaus

arXiv:1910.13325

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Predicting physical properties of alkanes with neural networks

P. Santak & G.J. Conduit

Fluid Phase Equilibria 501, 112259 (2019)

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Structure–Mechanical Stability Relations of Metal-Organic Frameworks via Machine Learning

P.Z. Moghadam, S.M.J. Rogge, A. Li, C.-M. Chow, J. Wieme, N. Moharrami, M. Aragones-Anglada, G.J. Conduit, D.A. Gomez-Gualdron, V.V. Speybroe & D. Fairen-Jimenez

Matter 1, 219 (2019) and accompanying commentary Matter 1, 26 (2019)

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Materials data validation and imputation with an artificial neural network

P.C. Verpoort, P. MacDonald & G.J. Conduit

Computational Materials Science 147, 176 (2018)

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Method and system for designing a material

G.J. Conduit & B.D. Conduit

Patents GB1302743, EP14153898, US2014/177578 (2013)

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Machine learning superalloy microchemistry and creep strength from physical descriptors

P. Taylor & G.J. Conduit

Computational Materials Science 227, 112265 (2023)

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Design of a Ni-based Superalloy for Laser Repair Applications using Probabilistic Neural Network Identification

J.F.S. Markanday, G.J. Conduit, B.D. Conduit, J.T. Pürstl, K.A. Christofidou, L. Chechik, G.J. Baxter, C.P. Heason & H.J. Stone

Data Centric Engineering 3, e30 (2022)

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Design of Materials with Alchemite™

J. Stuckner, T.M. Whitehead, R.C. Parini, G.J. Conduit, O. Benafan & S.M. Arnold

NASA Technical Memorandum, 20220008637

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Accelerating the Design of Automotive Catalyst Products Using Machine Learning

T.M. Whitehead, F. Chen, C. Daly & G.J. Conduit

Johnson Matthey Technology Review 66, 130 (2022)

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Machine learning predictions of superalloy microstructure

P. Taylor & G.J. Conduit

Computational Materials Science 201, 110916 (2021)

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Au-Ge alloys for wide-range low-temperature on-chip thermometry

J.R.A. Dann, P.C. Verpoort, J. Ferreira de Oliveira, S.E. Rowley, A. Datta, S. Kar-Narayan, C.J.B. Ford, G.J. Conduit & V. Narayan

Physical Review Applied 12, 034024 (2019)

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Probabilistic neural network identification of an alloy for direct laser deposition

B.D. Conduit, T. Illston, S. Baker, D. Vadegadde Duggappa, S. Harding, H.J. Stone & G.J. Conduit

Materials & Design 168, 107644 (2019)

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Probabilistic design of a molybdenum-base alloy using a neural network

B.D. Conduit, N.G. Jones, H.J. Stone & G.J. Conduit

Scripta Materialia 146, 82 (2018)

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Design of a nickel-base superalloy using a neural network

B.D. Conduit, N.G. Jones, H.J. Stone & G.J. Conduit

Materials & Design 131, 358 (2017)

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Alloy composition

B.D. Conduit, G.J. Conduit, H.J. Stone & M.C. Hardy

Patents GB1307535, EP2796581, US20140322068 (2014)

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Nickel Alloy Composition

B.D. Conduit, G.J. Conduit & H.J. Stone

Patents GB201408536, EP2944704B1, US2015/0329941 (2014)

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Alloy composition

B.D. Conduit, G.J. Conduit, H.J. Stone & M.C. Hardy

Patents GB1307533, EP2796580B1, US2016/0369379 (2014)

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A nickel alloy

M.C. Hardy, H.J. Stone, P.M. Mignanelli, B.D. Conduit & G.J. Conduit

Patents GB1309404, EP2805784B1, US2014/0348689 (2014)

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Alloys based on Cr-Cr2Ta containing Si

A. Bhowmik, R.E. Bennett, B. Monserrat, G.J. Conduit, L.D. Connor, J.E. Parker, R.P. Thompson, C.N. Jones & H.J. Stone

Intermetallics 48, 62 (2014)

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Grain growth behaviour during near-γ' solvus thermal exposures in a polycrystalline nickel-base superalloy

D.M. Collins, B.D. Conduit, H.J. Stone, M.C. Hardy, G.J. Conduit & R.J. Mitchell

Acta Materialia 61, 3378 (2013)

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Molybdenum Alloy Composition

B.D. Conduit, G.J. Conduit, H.J. Stone & M.C. Hardy

Patents GB201307535D0, EP2796581B1, US9347118B2 (2013)

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Modelling nicotine pharmacokinetic profile for e-cigarette using real time monitoring of consumer’s physiological measurements and mouth level exposure

K, Prasad, A. Griffiths, K. Agrawal, M. McEwan, F. Macci, M. Ghisoni, M. Stopher, M. Napleton, J. Strickland, D. Keating, T.M. Whitehead, G.J. Conduit, S. Murray & L. Edward

BioData Mining 17, 24 (2024)

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Quantifying the Benefits of Imputation over QSAR Methods in Toxicology Data Modelling

T.M. Whitehead, J. Strickland, G.J. Conduit, A. Borrel, D. Mucs & I. Baskerville-Abraham

Journal of Chemical Information and Modeling, 64, 2624 (2024)

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Prediction of in vivo pharmacokinetic parameters and time-exposure curves in rats using machine learning from chemical structure

O. Obrezanova, A. Martinsson, T.M. Whitehead, S.Y. Mahmoud, A. Bender, F. Miljković, P. Grabowski, B.W.J. Irwin, I. Oprisiu, G.J. Conduit, M.D. Segall, G. Smith, B. Williamson, S. Winiwarter & N. Greene

Molecular Pharmaceutics 19, 1488 (2022)

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Imputation of Sensory Properties Using Deep Learning

S.Y. Mahmoud, B.W.J. Irwin, D. Chekmarev, S. Vyas, J. Kattas, T.M. Whitehead, T. Mansley, J. Bikker, G.J. Conduit & M.D. Segall

Journal of Computer-Aided Molecular Design 35, 1125 (2021)

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An Open Drug Discovery Competition: Experimental Validation of Predictive Models in a Series of Novel Antimalarials

E.G. Tse, L. Aithani, M. Anderson, J. Cardoso-Silva, G. Cincilla, G.J. Conduit, M. Galushka, D. Guan, I. Hallyburton, B.W.J. Irwin, K. Kirk, A.M. Lehane, J.C.R. Lindblom, R. Lui, S. Matthews, J. McCulloch, A. Motion, H. Leung Ng, M. Öeren, M.N. Robertson, V. Spadavecchio, V.A. Tatsis, W.P. van Hoorn, A.D. Wade, T.M. Whitehead, P. Willis & M.H. Todd

Journal of Medicinal Chemistry 64, 16450 (2021)

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Deep Imputation on Large-Scale Drug Discovery Data

B.W.J. Irwin, T.M. Whitehead, S. Rowland, S.Y. Mahmoud, G.J. Conduit & M.D. Segall

Applied AI Letters 2, e31 (2021)

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Data Imputation Through Deep Learning

M. Segall, B. Irwin, T. Whitehead, S. Mahmoud, G. Shields, G. Turner, A. Elliott, S.-B. Marcu, R. Parini, E. Champness & G.J. Conduit

Innovations in Pharmaceutical Technology Autumn/Winter, 42 (2020)

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Machine learning to predict mesenchymal stem cell efficacy for cartilage repair

Y.Y.F. Liu, Y. Lu, S. Oh & G.J. Conduit

PLOS Computational Biology 16, 1008275 (2020)

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Practical Applications of Deep Learning to Impute Heterogeneous Drug Discovery Data

B.W.J. Irwin, J. Levell, T.M. Whitehead, M.D. Segall & G.J. Conduit

Journal of Chemical Information and Modeling 60, 2848 (2020)

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Imputation versus prediction: applications in machine learning for drug discovery

B.W.J. Irwin, S. Mahmoud, T.M. Whitehead, G.J. Conduit & M.D. Segall

Future Drug Discovery 2 (2020)

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Imputation of Assay Bioactivity Data using Deep Learning

T.M. Whitehead, B.W.J. Irwin, P.A. Hunt, M.D. Segall & G.J. Conduit

Journal of Chemical Information and Modeling, 59, 1197 (2019)

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Absence of diagonal force constants in cubic Coulomb crystals

B. Andrews & G.J. Conduit

Proceedings of the Royal Society A 476, 20200518 (2020) and Supplemental Material

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A tail-regression estimator for heavy-tailed distributions of known tail indices and its application to continuum quantum Monte Carlo data

P. López Ríos & G.J. Conduit

Phys. Rev. E 99, 063312 (2019)

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Long-lived non-equilibrium superconductivity in a non-centrosymmetric Rashba semiconductor

V. Narayan, P.C. Verpoort, J.R.A. Dann, D. Backes, C.J.B. Ford, M. Lanius, A.R. Jalil, P. Schüffelgen, G. Mussler, G.J. Conduit & D. Grützmacher

Phys. Rev. B 100, 024504 (2019)

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Direct evaluation of the force constant matrix in quantum Monte Carlo

Y.Y.F. Liu, B. Andrews & G.J. Conduit

Editor's Pick in J. Chem. Phys. 150, 034104 (2019)

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Band structure interpolation using optimized local orbitals from linear-scaling density functional theory

L.E. Ratcliff, G.J. Conduit, N.D.M. Hine & P.D. Haynes

Phys. Rev. B 98, 125123 (2018)

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Multi-particle instability in a spin-imbalanced Fermi gas

T.M. Whitehead & G.J. Conduit

Phys. Rev. B 97, 014502 (2018)

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Quantum Order-by-Disorder in Strongly Correlated Metals

A.G. Green, G.J. Conduit & F. Krüger

Annual Review of Condensed Matter Physics 9, 59 (2018)

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Jastrow correlation factor for periodic systems

T.M. Whitehead, M.H. Michael & G.J. Conduit

Phys. Rev. B 94, 035157 (2016)

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Pseudopotential for the electron-electron interaction

J.H. Lloyd-Williams, R.J. Needs & G.J. Conduit

Phys. Rev. B 92, 075106 (2015)

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Extracting semiconductor band gap zero-point corrections from experimental data

B. Monserrat, G.J. Conduit & R.J. Needs

Phys. Rev. B 90, 184302 (2014)

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High-fidelity contact pseudopotentials and p-wave superconductivity

P.O. Bugnion, R.J. Needs & G.J. Conduit

arXiv:1403.0047

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Quantum Monte Carlo study of the two-dimensional ferromagnet

G.J. Conduit

Phys. Rev. B 87, 184414 (2013)

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Fluctuation-induced pair density wave in itinerant ferromagnets

G.J. Conduit, C.J. Pedder & A.G. Green

Phys. Rev. B 87, 121112(R) (2013)

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Itinerant ferromagnetism with finite ranged interactions

C.W. von Keyserlingk & G.J. Conduit

Phys. Rev. B 87, 184424 (2013)

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Field-Tuned Quantum Phase Transition in the Insulating Regime of Ultrathin Amorphous Bi Films

G.J. Conduit & Y. Meir

Phys. Rev. Lett. 108, 159701 (2012)

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Microscopic theory of the magnetoresistance of disordered superconducting films

G.J. Conduit & Y. Meir

arXiv:1111.2941

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Resistance jumps and the nature of the finite-flux normal phase in ultra-thin superconducting cylinders

G.J. Conduit & Y. Meir

arXiv:1107.1246

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Strategies for improving the efficiency of quantum Monte Carlo calculations

R.M. Lee, G.J. Conduit, N. Nemec, P. López Ríos & N.D. Drummond

Phys. Rev. E 83, 066706 (2011)

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First principles calculation of conductance and current flow through low-dimensional superconductors

G.J. Conduit & Y. Meir

Phys. Rev. B 84, 064513 (2011)

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Theory of quantum paraelectrics and the metaelectric transition

G.J. Conduit & B.D. Simons

Editors' Suggestion in Phys. Rev. B 81, 024102 (2010)

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Inhomogeneous phase formation on the border of itinerant ferromagnetism

G.J. Conduit, A.G. Green & B.D. Simons

Editors' Suggestion in Phys. Rev. Lett. 103, 207201 (2009) and Spotlight Viewpoint Commentary Physics 2, 93 (2009)

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Diffusion Monte Carlo study of a valley degenerate electron gas and application to quantum dots

G.J. Conduit & P.D. Haynes

Phys. Rev. B 78, 195310 (2008) and Virtual Journal of Nanoscale Science & Technology 18, 21 (2008)

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Many-flavor electron gas approach to electron-hole drops

G.J. Conduit

Phys. Rev. B 78, 035111 (2008)

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Temporal fluctuation induced order in conventional superconductors

D.C.W. Foo & G.J. Conduit

Phys. Rev. A. 103, 043303 (2021)

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Diffusion Monte Carlo study of a spin-imbalanced two-dimensional Fermi gas with attractive interactions

D.C.W. Foo & G.J. Conduit

Phys. Rev. A. 100, 063602 (2019)

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Communal pairing in spin-imbalanced Fermi gases

D.C.W. Foo, T.M. Whitehead & G.J. Conduit

Europhysics Letters 126, 67003 (2019)

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Effective-range dependence of two-dimensional Fermi gases

L.M. Schonenberg, P.C. Verpoort & G.J. Conduit

Phys. Rev. A 96, 023619 (2017)

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Effective range dependence of resonant Fermi gases

L.M. Schonenberg & G.J. Conduit

Phys. Rev. A 95, 013633 (2017)

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Pseudopotential for the 2D contact interaction

T.M. Whitehead, L.M. Schonenberg, N. Kongsuwan, R.J. Needs & G.J. Conduit

Phys. Rev. A 93, 042702 (2016)

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Pseudopotentials for an ultracold dipolar gas

T.M. Whitehead & G.J. Conduit

Phys. Rev. A 93, 022706 (2016)

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High-fidelity pseudopotentials for the contact interaction

P.O. Bugnion, P. López Ríos, R.J. Needs & G.J. Conduit

Phys. Rev. A 90, 033626 (2014) and Python program for pseudopotential generation

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Inhomogeneous state of few-fermion superfluids

P.O. Bugnion, J.A. Lofthouse & G.J. Conduit

Phys. Rev. Lett. 111, 045301 (2013)

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Exploring exchange mechanisms with a cold atom gas

P.O. Bugnion & G.J. Conduit

Phys. Rev. A 88, 013601 (2013)

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Ferromagnetic spin correlations in a few-fermion system

P.O. Bugnion & G.J. Conduit

Phys. Rev. A 87, 060502(R) (2013)

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Line of Dirac monopoles embedded in a Bose-Einstein condensate

G.J. Conduit

Phys. Rev. A 86, 021605(R) (2012) and Kaleidoscope in August 2012

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Itinerant ferromagnetism in an interacting Fermi gas with mass imbalance

C.W. von Keyserlingk & G.J. Conduit

Phys. Rev. A 83, 053625 (2011)

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Effect of three-body loss on itinerant ferromagnetism in an atomic Fermi gas

G.J. Conduit & E. Altman

Phys. Rev. A 83, 043618 (2011)

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Itinerant ferromagnetism in a two-dimensional atomic gas

G.J. Conduit

Phys. Rev. A 82, 043604 (2010)

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Dynamical instability of a spin spiral in an interacting Fermi gas as a probe of the Stoner transition

G.J. Conduit & E. Altman

Phys. Rev. A 82, 043603 (2010)

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A repulsive atomic gas in a harmonic trap on the border of itinerant ferromagnetism

G.J. Conduit & B.D. Simons

Phys. Rev. Lett. 103, 200403 (2009) and Virtual Journal of Atomic Quantum Fluids 1 (2009)

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Itinerant ferromagnetism in an atomic Fermi gas: Influence of population imbalance

G.J. Conduit & B.D. Simons

Phys. Rev. A 79, 053606 (2009)

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Superfluidity at the BEC-BCS crossover in two-dimensional Fermi gases with population and mass imbalance

G.J. Conduit, P.H. Conlon & B.D. Simons

Phys. Rev. A 77, 053617 (2008)

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Visibility prediction software: five factors of contrast perception for the vision impaired in the real world

H. Dalke, A. Corso, G.J. Conduit & A. Riaz

Designing Inclusive Systems, Springer, London, pp. 93-102 (2012). ISBN: 978-1-4471-2866-3

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A Colour Contrast Assessment System: Design for People with Visual Impairment

H. Dalke, G.J. Conduit, B.D. Conduit, R. Cooper, A. Corso & D. Wyatt

Designing Inclusive Interactions, Springer Verlag, pp. 101-112 (2010). ISBN: 978-1-84996-165-3

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British Standard BS 8493:2008+A1:2010 Light reflectance value (LRV) of a surface. Method of test

H. Dalke, A. Corso, G.J. Conduit & A. Riaz

ISBN 978-0-58-067695-6 (2010)

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The Contrast Guide: Design and Contrast Specifications for Environments and Products

H. Dalke, J. Clarke, A. Corso & G.J. Conduit

Cromocon, London (2010). ISBN 978-0-95-704410-4

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Measurement for a more visible world: colour contrast and visual impairment

H. Dalke, G.J. Conduit, B.D. Conduit & A. Corso

Measurement, sensation and cognition, pp. 134-138 (2009). ISBN: 978-0-946754-56-4