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Silicon Valley meets the ivory tower: Searchable data repositories for experimental nanomaterials research
Current Opinion in Solid State & Materials Science ( IF 11.0 ) Pub Date : 2016-06-14 , DOI: 10.1016/j.cossms.2016.06.002
Nils Persson , Michael McBride , Martha Grover , Elsa Reichmanis

Centralized data repositories have proven useful in promoting reproducibility and transparency in many fields of research, particularly the life sciences. Nanomaterials research is frequently difficult to reproduce because of the complexity of the systems under study and a lack of standardization due to the exploratory nature of the field. One system that exemplifies this problem is that of the poly(3-hexylthiophene)-based organic field effect transistor, a platform used to study the process-structure-property relationships in semicrystalline polymeric semiconductors. Performance in this system is judged principally by charge carrier mobility, a fitted model parameter that describes how quickly charge can move through the active layer of a given transistor. Reported values of this electrical property vary by over six orders of magnitude for one material and are impacted by intrinsic material properties, processing conditions, device architectures and calculation methods. A database containing over 200 of these devices from 19 studies was compiled to demonstrate the impact of these parameters on reported performance as well as the utility of having such a database to search and explore. We confirm well-known trends such as the effect of polymer molecular weight, transistor channel length and thin film deposition method before going on to identify a standard device that can be compared across multiple studies. We find that an organized database of process-property information can be used to identify unpublished heuristic knowledge, to help authors standardize their reporting of methods, and to guide hypothesis generation and experimental design. A repository of the data used in this study is available at [http://www.github.com/Imperssonator/OFET-Database].



中文翻译:

硅谷与象牙塔相遇:用于实验性纳米材料研究的可搜索数据存储库

事实证明,集中式数据存储库有助于提高许多研究领域(尤其是生命科学)的可重复性和透明度。由于所研究系统的复杂性以及由于该领域的探索性质而缺乏标准化,因此纳米材料的研究通常难以重现。一个例证该问题的系统是基于聚(3-己基噻吩)的有机场效应晶体管的系统,该平台用于研究半结晶聚合物半导体中的过程-结构-性质关系。该系统的性能主要由电荷载流子迁移率来判断,电荷迁移率是一个拟合的模型参数,该参数描述电荷可以在给定晶体管的有源层中移动的速度。对于一种材料,此电气特性的报告值变化超过六个数量级,并且受固有材料特性,加工条件,器件架构和计算方法的影响。汇编了一个数据库,其中包含来自19个研究的200多种此类设备,以证明这些参数对报告的性能的影响以及使用这种数据库进行搜索和探索的实用性。在确定可以在多项研究中进行比较的标准器件之前,我们确认了众所周知的趋势,例如聚合物分子量,晶体管沟道长度和薄膜沉积方法的影响。我们发现,可以使用有组织的过程属性信息数据库来识别未发布的启发式知识,以帮助作者标准化其方法报告,并指导假设的产生和实验设计。可在[http://www.github.com/Imperssonator/OFET-Database]上获得本研究中使用的数据的存储库。

更新日期:2016-06-14
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