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Theory of Condensed Matter
Theoretical Condensed Matter physics is about building models of physical processes, often driven by experimental data, generalising the solutions of those models to make experimental predictions, and transferring the concepts gained into other areas of research. Theory plays an important role in understanding known phenomena and in predicting new ones.
With over seventy members, the TCM Group is one of the largest research Groups in the Cavendish Laboratory, and the largest university Condensed Matter Theory group in the country. Able to trace its history back for over sixty years, it has been home to many leading theoreticians.
Starting at the first principles microscopic level - with the Schrödinger equation - many properties of materials can now be calculated with a high degree of accuracy. We work on refining and developing new calculational tools and applying them to problems in physics, chemistry, materials science and biology.
Solids often show unusual collective behaviour resulting from cooperative quantum or classical phenomena. For this type of physics a more model-based approach is appropriate, and we are using such methods to attack problems in magnetism, superconductivity, nonlinear optics, mesoscopic systems, polymers, and colloids.
Collective behaviour comes even more to the fore in systems on a larger scale. As examples, we work on self-organising structures in "soft" condensed matter systems, non-linear dynamics of interacting systems, the observer in quantum mechanics, and models of biophysical processes, from the molecular scale up to neural systems.
A pioneering application of machine learning by Gareth Conduit has been experimentally proven to predict accurately the properties of metal-organic frameworks. This class of materials has many promising applications including the extraction of water from the air in the desert and the storage of dangerous gases including in hydrogen-based cars.
News archive(Click the above tab to reload the Seminars list.)
More seminars- Identification of a regeneration-organizing cell in the Xenopus tail. Science 364 653 - 658 (2019)
- Molecules with dipoles in periodic boundary conditions in a tetragonal cell. J. Phys. - Condens. Mat. (2019)
- Computational Fluorine Scanning Using Free-Energy Perturbation. J. Chem. Inf. Model. acs.jcim.9b00228 (2019)
- Prediction of the near-IR spectra of ices by ab initio molecular dynamics. Phys. Chem. Chem. Phys. 21 9433 - 9440 (2019)
- Pattern selection when a layer buckles on a soft substrate. Soft Matter 15 3751 - 3770 (2019)
- Optical backaction-evading measurement of a mechanical oscillator. Nature Comm. 10 2086 (2019)
- Large-Scale Study of Hydration Environments through Hydration Sites. J. Phys. Chem. B acs.jpcb.9b02490 (2019)
- Structure prediction drives materials discovery Nat. Rev. Mater. 4 331 - 348 (2019)
- Probabilistic neural network identification of an alloy for direct laser deposition Mater. Des. 168 107644 (2019)
- Nuclear Magnetic Resonance Spectroscopy as a Dynamical Structural Probe of Hydrogen under High Pressure. Phys. Rev. Lett. 122 135501 (2019)
- Topological bands for ultracold atoms Rev. Mod. Phys. 91 015005 (2019)
- Theory of mechanochemical patterning in biphasic biological tissues. P. Natl Acad. Sci. USA 116 5344 - 5349 (2019)
- Intratumoral genetic and functional heterogeneity in pediatric glioblastoma. Cancer Research canres.3441.2018 (2019)
- Crypt fusion as a homeostatic mechanism in the human colon. Gut (2019)
- Rod motifs in neutron scattering in spin ice Phys. Rev. B 99 121102 (2019)
- Classification of topological insulators and superconductors out of equilibrium Phys. Rev. B 99 075148 (2019)
- First-principles study of localized and delocalized electronic states in crystallographic shear phases of niobium oxide Phys. Rev. B 99 075151 (2019)
- The proneural wave in the Drosophila optic lobe is driven by an excitable reaction-diffusion mechanism. Elife 8 (2019)
- Imputation of Assay Bioactivity Data Using Deep Learning. J. Chem. Inf. Model. acs.jcim.8b00768 (2019)
- Peristaltic elastic instability in an inflated cylindrical channel Phys. Rev. Lett. 122 068003 (2019)
Theoretical Condensed Matter physics is about building models of physical processes, often driven by experimental data, generalising the solutions of those models to make experimental predictions, and transferring the concepts gained into other areas of research. Theory plays an important role in understanding known phenomena and in predicting new ones.
With over seventy members, the TCM Group is one of the largest research Groups in the Cavendish Laboratory, and the largest university Condensed Matter Theory group in the country. Able to trace its history back for over sixty years, it has been home to many leading theoreticians.
Starting at the first principles microscopic level - with the Schrödinger equation - many properties of materials can now be calculated with a high degree of accuracy. We work on refining and developing new calculational tools and applying them to problems in physics, chemistry, materials science and biology.
Solids often show unusual collective behaviour resulting from cooperative quantum or classical phenomena. For this type of physics a more model-based approach is appropriate, and we are using such methods to attack problems in magnetism, superconductivity, nonlinear optics, mesoscopic systems, polymers, and colloids.
Collective behaviour comes even more to the fore in systems on a larger scale. As examples, we work on self-organising structures in "soft" condensed matter systems, non-linear dynamics of interacting systems, the observer in quantum mechanics, and models of biophysical processes, from the molecular scale up to neural systems.
News
A pioneering application of machine learning by Gareth Conduit has been experimentally proven to predict accurately the properties of metal-organic frameworks. This class of materials has many promising applications including the extraction of water from the air in the desert and the storage of dangerous gases including in hydrogen-based cars.
Recent Publications
- Identification of a regeneration-organizing cell in the Xenopus tail. Science 364 653 - 658 (2019)
- Molecules with dipoles in periodic boundary conditions in a tetragonal cell. J. Phys. - Condens. Mat. (2019)
- Computational Fluorine Scanning Using Free-Energy Perturbation. J. Chem. Inf. Model. acs.jcim.9b00228 (2019)
- Prediction of the near-IR spectra of ices by ab initio molecular dynamics. Phys. Chem. Chem. Phys. 21 9433 - 9440 (2019)
- Pattern selection when a layer buckles on a soft substrate. Soft Matter 15 3751 - 3770 (2019)
- Optical backaction-evading measurement of a mechanical oscillator. Nature Comm. 10 2086 (2019)
- Large-Scale Study of Hydration Environments through Hydration Sites. J. Phys. Chem. B acs.jpcb.9b02490 (2019)
- Structure prediction drives materials discovery Nat. Rev. Mater. 4 331 - 348 (2019)
- Probabilistic neural network identification of an alloy for direct laser deposition Mater. Des. 168 107644 (2019)
- Nuclear Magnetic Resonance Spectroscopy as a Dynamical Structural Probe of Hydrogen under High Pressure. Phys. Rev. Lett. 122 135501 (2019)
- Topological bands for ultracold atoms Rev. Mod. Phys. 91 015005 (2019)
- Theory of mechanochemical patterning in biphasic biological tissues. P. Natl Acad. Sci. USA 116 5344 - 5349 (2019)
- Intratumoral genetic and functional heterogeneity in pediatric glioblastoma. Cancer Research canres.3441.2018 (2019)
- Crypt fusion as a homeostatic mechanism in the human colon. Gut (2019)
- Rod motifs in neutron scattering in spin ice Phys. Rev. B 99 121102 (2019)
- Classification of topological insulators and superconductors out of equilibrium Phys. Rev. B 99 075148 (2019)
- First-principles study of localized and delocalized electronic states in crystallographic shear phases of niobium oxide Phys. Rev. B 99 075151 (2019)
- The proneural wave in the Drosophila optic lobe is driven by an excitable reaction-diffusion mechanism. Elife 8 (2019)
- Imputation of Assay Bioactivity Data Using Deep Learning. J. Chem. Inf. Model. acs.jcim.8b00768 (2019)
- Peristaltic elastic instability in an inflated cylindrical channel Phys. Rev. Lett. 122 068003 (2019)