Collaborative Research: Integrated Biorefinery for Pyrolysis Biofuels and Biotemplated Nanomaterials

随着世界人口和能源需求的增加，我们全球对化石燃料资源的依赖给环境带来了令人难以置信的压力。现代生物炼油厂可以通过热和化学途径将木质纤维素生物质转化为燃料，从而产生可持续的能源。然而，使用热解(无氧加热)作为热化学转换技术的主要问题之一是需要大量的燃料升级以改善稳定性和增加油的热值。尽管生物油可以在生产后升级，但目前的方法存在催化剂中毒、材料和操作成本高的问题。这一研究项目旨在解决这些问题，方法是将金属硝酸盐和乙酸酯等无机化合物加入纤维素原料，通过生物模板同时设计高价值纳米材料，并对热解生物油进行催化升级，从而减少昂贵的下游升级需求。使用基于机器学习的技术，如潜在催化剂选择的材料信息学和实验的统计设计，为过程变量决策提供信息，拟议的工作将增加热化学衍生生物燃料原位升级的基础知识体系，同时为计算知情、经实验验证的可再生燃料设计提供新的范例。拟议的研究将专注于通过同时制造生物模板纳米颗粒来在热解过程中升级生物燃料。材料信息学方法将用于选择原位热解催化剂，替代反应将用于预测(然后通过集成反馈回路验证)潜在的反应路径和形成的纳米材料结构。通过开发一种新的热解产品指数，该指数着眼于例如氧气在热解过程中的去向，以及标记化合物的产率在催化剂掺入后如何变化，主要研究人员的目标是合成一种新的方法来讨论生物燃料升级途径，帮助标准化被认为是好途径的相当多样化的文献。该项目还旨在通过与(联合王国)玛丽皇后大学的一个小组的国际合作，阐明在使用欧拉曼光谱技术对金属浸渍的生物质进行热解时发生的物理变化。其目的是提高我们对哪些反应途径对脱挥最关键的认识，以及如何更好地设计催化剂来改善一次热解和限制二次反应，如再缩合，并促进裂化，从而减少焦油的生成。这项拟议的工作还涉及纳米材料的表征，以了解影响生物模板纳米材料的尺寸、形貌和结晶度的工艺变量。这项拟议工作在基础科学方面的进展可能会导致设计一种优化的综合生物精炼厂，将可再生能源转化为能源和材料。除了在研究方面培训研究生和本科生外，还计划吸引和指导代表性不足的学生，并在康奈尔大学、波士顿大学和玛丽女王大学之间开展国际研究生交流。将在三所参与的大学中开发、实施和评估可再生能源应用的主动学习模块。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

As the world?s population and energy demands increase, our global reliance on fossil fuel resources to provide this energy puts an incredible strain on the environment. The modern biorefinery could produce sustainable energy by converting lignocellulosic biomass to fuels through thermal and chemical routes. However, one of the primary issues with using pyrolysis (heating in the absence of oxygen) as a thermochemical conversion technique is the need for significant fuel upgrading to improve stability and increase the heating value of the oil. Though bio-oils can be upgraded post-production, current methods suffer from catalyst poisoning and high materials and operation costs. This research project aims to address these issues by incorporating inorganic compounds, such as metal nitrates and acetates into cellulosic feedstocks, to simultaneously engineer high-value nanomaterials via bio-templating and catalytically upgrade pyrolysis bio-oils, thus reducing the need for costly downstream upgrading. Using machine learning based techniques, such as materials informatics for potential catalyst selection and statistical design of experiments, to inform process variable decisions, the proposed work will add to a fundamental body of knowledge on in situ upgrading of thermochemically derived biofuels while offering a new paradigm in computationally informed, experimentally verified renewable fuel design.The proposed research will focus on upgrading of biofuels during pyrolysis by simultaneously making bio-templated nanoparticles. Materials Informatics approaches will be used to select in situ pyrolysis catalysts and surrogate reactions will be used to predict (and then validate via integrated feedback loop) potential reaction pathways and formed nanomaterial structure. By developing a new Pyrolysis Product Index that looks at where, for example, oxygen goes during pyrolysis, and how yields of marker compounds change upon catalyst incorporation, the principal investigators aim to synthesize a new way to discuss biofuel upgrading pathways, helping to standardize what is a rather diverse literature in terms of what is deemed to be a good pathway. The project also aims to elucidate the physical changes occurring during pyrolysis of metal-impregnated biomass using in operando Raman spectroscopy through an international collaboration with a group from Queens Mary University (United Kingdom). The objective is to improve our knowledge of which reaction pathways are most critical to devolatilization, and how to better design catalysts to improve both primary pyrolysis and to limit secondary reactions, such as re-condensation, and to promote cracking, thereby reducing tar formation. The proposed work also involves nanomaterials characterization to understand the process variables impacting size, morphology and crystallinity of bio-templated nanomaterials. Advances in fundamental science stemming from the proposed work may lead to the design of an optimized integrated biorefinery to convert renewable sources to energy and materials. In addition to training graduate and undergraduate students in research, there ae plans to engage and mentor underrepresented students and develop and international graduate student exchange between Cornell, Boston and Queen Mary Universities. An active learning module for renewable energy applications will be developed, implemented and assessed in the three participating universities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.