Collaborative Research: Integrated Biorefinery for Pyrolysis Biofuels and Biotemplated Nanomaterials

作为世界？随着人口和能源需求的增加，我们对化石燃料资源的全球依赖给环境带来了难以置信的压力。现代生物精炼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，从而生产可持续能源。然而，使用热解（在无氧条件下加热）作为热化学转化技术的主要问题之一是需要对燃料进行重大升级，以提高稳定性并增加油的热值。虽然生物油可以在生产后进行升级，但目前的方法存在催化剂中毒、材料和操作成本高的问题。该研究项目旨在通过将无机化合物（如金属硝酸盐和醋酸盐）加入纤维素原料中来解决这些问题，同时通过生物模板和催化升级热解生物油来设计高价值的纳米材料，从而减少对昂贵的下游升级的需求。利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本知识体系，同时为计算信息和实验验证的可再生燃料设计提供新的范例。拟议的研究将侧重于在热解过程中通过同时制造生物模板纳米颗粒来升级生物燃料。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）潜在的反应途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（热解过程中氧气的去向，以及催化剂加入后标记化合物的产量如何变化），主要研究人员的目标是合成一种讨论生物燃料升级途径的新方法，帮助标准化被认为是良好途径的相当多样化的文献。该项目还旨在通过与皇后玛丽大学（英国）的一个小组的国际合作，利用operando拉曼光谱阐明金属浸渍生物质热解过程中发生的物理变化。目的是提高我们对哪些反应途径对脱挥发最关键的认识，以及如何更好地设计催化剂来改善初级热解和限制二次反应，如再冷凝，并促进裂解，从而减少焦油的形成。本研究还涉及纳米材料表征，以了解影响生物模板纳米材料尺寸、形态和结晶度的工艺变量。基础科学的进步源于所提出的工作，可能会导致优化的集成生物精炼厂的设计，将可再生资源转化为能源和材料。除了培训研究生和本科生进行研究外，还计划吸引和指导代表性不足的学生，并在康奈尔大学、波士顿大学和玛丽皇后大学之间开展国际研究生交流。三所参与的大学将开发、实施和评估可再生能源应用的主动学习模块。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.