Periodic Reporting for period 2 - A-TO-B (A Theory of Organic Bioelectronics Materials)
Berichtszeitraum: 2023-04-01 bis 2024-09-30
Bioelectronics materials are used as interface between human-made electronic devices and biological cells, tissues or fluids for applications such as diagnostics/sensing or monitoring/stimulating neural activity. Organic (often polymeric) materials able to conduct both ionic and electronic current are emerging as the ideal choice for bioelectronics because of an enhanced biocompatibility, flexibility and, most of all, the ability to fine tune their property through the control of their chemical composition. However, despite the excellent proof of concepts available, there is no systematic approach to improve this class of materials because there is no approach currently available to model and design them. No existing methodology enables the study of electronic motion in soft-materials concurrently with the motion of ions: the timescales of the relevant phenomena are very different and a new approach should be constructed drawing elements from different areas of modelling science.
Developing a methodology that establishes a link between the chemical composition and the behaviour of organic bioelectronics materials will accelerate their development and bring to fruition the benefits of this technology in terms of improved healthcare. The areas of proposed applications are ever growing and, in addition to diagnostics, they now include controlled drug delivery and tissue reparation to treat, for example, spinal cord injuries or certain types of blindness.
The overall goal of this proposal is (i) to lay the foundations for atomistic modelling of polymeric organic bioelectronics materials, (ii) to derive structure-property relationship from the study a range of experimentally relevant systems and (iii) to elucidate the microscopic mechanism of operation of bioelectronics devices.
Developing a methodology that establishes a link between the chemical composition and the behaviour of organic bioelectronics materials will accelerate their development and bring to fruition the benefits of this technology in terms of improved healthcare. The areas of proposed applications are ever growing and, in addition to diagnostics, they now include controlled drug delivery and tissue reparation to treat, for example, spinal cord injuries or certain types of blindness.
The overall goal of this proposal is (i) to lay the foundations for atomistic modelling of polymeric organic bioelectronics materials, (ii) to derive structure-property relationship from the study a range of experimentally relevant systems and (iii) to elucidate the microscopic mechanism of operation of bioelectronics devices.
The work performed follows closely the original work-plan and resulted in 12 peer-reviewed publications and is summarized accordingly.
WP1 focuses on the study of the coupled dynamics on ions (which moves slowly in timescale of tens of nanoseconds) and electron which can hop between different states within few picoseconds in these systems. The challenges is to develop a method suited for the quantum motion of the electrons and the classical motion of the nuclei. A method was developed to study how the excess charge respond to the motion of the electrons and this key milestone of the proposal has been published and used for subsequent projects.
WP2 focuses on the development of rapid methods to perform simulation of semiconducting polymers and their composites, enabling discovery and exploration beyond modelling benchmark system. A range of technical innovations have been introduced and they ultimately permit the simulation of semiconducting polymers from their chemical drawing in just two days per polymer while the typical time is several months per polymers. The innovation have appeared in the peer reviewed literature and the key ones are available through a software that is freely distributed. In parallel, a model reduction scheme has been developed to link the results of such simulation with the main measurable observable: the charge mobility. The new combination of methods as unlocked new collaborations (Stanford, Koeln, Manchester) that have results in several additional peer-reviewed articles.
WP3 plans to look at the microscopic models of bioelectronics interfaces, i.e. how they can perform sensing. An initial study focused on one of the benchmark materials in organic bioelectronics is the composited PDOT:PSS, a material with a complex two-phase microstructure which had to be characterized before any study of further interfaces. We are currently preparing for publication the study of interfaces with water and electrolytes, where we have given the first microscopic insight on the sensing mechanism of organic electrochemical devices.
WP4 is to be developed in the last phase of the project and focuses on the modelling of the devices. We observed from WP1+WP2 an unusual feature deriving from the coupling between electronic and ionic degrees of freedom: the motion of the electron is “gated” by the motion of the ions, i.e. transition are activated and de-activated by ionic motions. This requires a completely new approach to the study of transport in bioelectronics devices.
WP1 focuses on the study of the coupled dynamics on ions (which moves slowly in timescale of tens of nanoseconds) and electron which can hop between different states within few picoseconds in these systems. The challenges is to develop a method suited for the quantum motion of the electrons and the classical motion of the nuclei. A method was developed to study how the excess charge respond to the motion of the electrons and this key milestone of the proposal has been published and used for subsequent projects.
WP2 focuses on the development of rapid methods to perform simulation of semiconducting polymers and their composites, enabling discovery and exploration beyond modelling benchmark system. A range of technical innovations have been introduced and they ultimately permit the simulation of semiconducting polymers from their chemical drawing in just two days per polymer while the typical time is several months per polymers. The innovation have appeared in the peer reviewed literature and the key ones are available through a software that is freely distributed. In parallel, a model reduction scheme has been developed to link the results of such simulation with the main measurable observable: the charge mobility. The new combination of methods as unlocked new collaborations (Stanford, Koeln, Manchester) that have results in several additional peer-reviewed articles.
WP3 plans to look at the microscopic models of bioelectronics interfaces, i.e. how they can perform sensing. An initial study focused on one of the benchmark materials in organic bioelectronics is the composited PDOT:PSS, a material with a complex two-phase microstructure which had to be characterized before any study of further interfaces. We are currently preparing for publication the study of interfaces with water and electrolytes, where we have given the first microscopic insight on the sensing mechanism of organic electrochemical devices.
WP4 is to be developed in the last phase of the project and focuses on the modelling of the devices. We observed from WP1+WP2 an unusual feature deriving from the coupling between electronic and ionic degrees of freedom: the motion of the electron is “gated” by the motion of the ions, i.e. transition are activated and de-activated by ionic motions. This requires a completely new approach to the study of transport in bioelectronics devices.
[1] High-Throughput simulation of semiconducting polymers are now possible.
Before our development it has been possible to perform the simulation of a single polymer in several months of human and computing time meaning that (i) only benchmark polymers could be studied (ii) simulations cannot be used to study hypothetical polymers (i.e. to design new polymers) (iii) simulations are inconsistent with each other and cannot be used in machine learning approaches to derive general trends and design principles. Our development resolves all these problems. We are now able to build complete polymer model at the pace of one polymer every 2 days. By the end of this ERC we will have developed models of microstructure and electronic properties of hundreds of polymers, a valuable dataset that can be exploited by machine learning methods. This innovation will change the way hypotheses of structure-property relations are formulated.
[2] Ion-Electron coupled transport can be studied with a microscopic model and the results are surprising.
We have solved the technical aspects and provided a methodology to simulate such systems with mixed ionic and electronic transport. The method can accompany the development of organic bioelectronics but one initial finding has already had a main impact on our understanding. It was not understood how the highly disordered materials used in bioelectronics could display high charge mobility. Our simulations reveal that the disorder of these materials is dynamical: trap states are deep in energy but short-lived because of the soft nature of the polymer. At the same time we have (i) discovered a new charge transport regime and (ii) demonstrated that the approach proposed in this ERC research is central for the future study or organic bioelectronics materials.
[3] Impact on polymer science outside organic electronics and bioelectronics
Thanks to a workshop organized with industry stakeholders we concluded that the generation of high-throughput simulation workflows is a critical methodology to enable the computer-aided design of any polymer. Such simulations can produce homogeneous datasets (which can be corrected automatically for systematic errors) that are critical for the development of novel materials with better technical performance or improved environmental credentials (e.g. biodegradability). This ERC research will therefore become a case study for a broader multi-institution initiative on “digitalization” of polymer research where the approaches we have introduced can benefit a multitude of sectors.
Before our development it has been possible to perform the simulation of a single polymer in several months of human and computing time meaning that (i) only benchmark polymers could be studied (ii) simulations cannot be used to study hypothetical polymers (i.e. to design new polymers) (iii) simulations are inconsistent with each other and cannot be used in machine learning approaches to derive general trends and design principles. Our development resolves all these problems. We are now able to build complete polymer model at the pace of one polymer every 2 days. By the end of this ERC we will have developed models of microstructure and electronic properties of hundreds of polymers, a valuable dataset that can be exploited by machine learning methods. This innovation will change the way hypotheses of structure-property relations are formulated.
[2] Ion-Electron coupled transport can be studied with a microscopic model and the results are surprising.
We have solved the technical aspects and provided a methodology to simulate such systems with mixed ionic and electronic transport. The method can accompany the development of organic bioelectronics but one initial finding has already had a main impact on our understanding. It was not understood how the highly disordered materials used in bioelectronics could display high charge mobility. Our simulations reveal that the disorder of these materials is dynamical: trap states are deep in energy but short-lived because of the soft nature of the polymer. At the same time we have (i) discovered a new charge transport regime and (ii) demonstrated that the approach proposed in this ERC research is central for the future study or organic bioelectronics materials.
[3] Impact on polymer science outside organic electronics and bioelectronics
Thanks to a workshop organized with industry stakeholders we concluded that the generation of high-throughput simulation workflows is a critical methodology to enable the computer-aided design of any polymer. Such simulations can produce homogeneous datasets (which can be corrected automatically for systematic errors) that are critical for the development of novel materials with better technical performance or improved environmental credentials (e.g. biodegradability). This ERC research will therefore become a case study for a broader multi-institution initiative on “digitalization” of polymer research where the approaches we have introduced can benefit a multitude of sectors.