本科化学实践教学体系的改革与探索

以创新型、应用型、复合型优秀人才培养为目标,提出并构建了“一体化、多层次、开放式、研究型”的实践教学体系。结合本学科优势和化学类专业特色,通过优化实践课程体系,改革实践教学内容与方法,加强师资与条件保障,推动学生参与创新及实践等举措,有力地支持了高水平本科化学人才的培养,提升了学生的创新精神和实践能力。

《高分子结构与性能的现代测试技术》教材的建设

为了提升化学学科本硕贯通高层次人才的培养质量,我们编写了实验课程“现代化学实验与技术”教材——《高分子结构与性能的现代测试技术》。本教材构建了本硕贯通实验课程教学的新模式,体现出夯实专业基础知识、面向高分子学科前沿性科学研究、注重“个性化”培养学生科研实践能力以及通识性和实用性的特色。

N/S co-doped 3D carbon framework prepared by a facile morphology-controlled solid-state pyrolysis method for oxygen reduction reaction in both acidic and alkaline media

Developing high-performance non-precious metal electrocatalysts for oxygen reduction reaction(ORR)is crucial for the commercialization of fuel cells and metal-air batteries.However,doped carbon-based materials only show good ORR activity in alkaline medium,and become less effective in acidic environment.We believe that an appropriate combination of both ionic and electronic transport path,and well dopant distribution of doped carbon-based materials would help to realize high ORR performance un-der both acidic and alkaline cond让ions.Accordingly,a nitrogen and sulfur co-doped carbon framework with hierarchical through-hole structure is fabricated by morphology-controlled solid-state pyrolysis of poly(aniline-co-2-ami no thiophenol)foam.The uniform high concentrations of nitrogen and sulfur,high intrinsic conductivity,and integrated three dimensional ionic and electronic transfer passageways of the 3D porous structure lead to synergistic effects in catalyzing ORR.As a result,the limiting current density of the carbonized poly(aniline-co-2-aminothiophenol)foam is equivalent to commercial Pt/C in acidic environment,and twice the latter in alkaline medium.

Injection molding of highly filled microcrystalline cellulose/polycaprolactone composites with the aid of reversible Diels-Alder reaction

To tackle the challenge of producing highly filled polymer composites using the traditional injection molding technique,which is characterized by the fairly high melt viscosity that makes mold filling difficult,the authors propose a solution based on dynamic covalent chemistry.As demonstrated by the proof-of-concept experiments,the 4-arm starshaped polycaprolactone(PCL)oligomers and microcrystalline cel-lulose(MCC)are crosslinked by the reversible Diels-Alder(DA)bonds.The flowability of the compounds greatly decreases due to the dissociation of the intercomponent DA bonds at the retro-reaction tempera-ture,and the networked architecture is reconstructed during cooling as a result of the forward DA reaction.Consequently,the high-loading MCC fillers are well distributed in the matrix and covalently bonded to the nearby PCL,forming a striking contrast to the control in which linear PCL acts as the matrix.The DA bonds crosslinked biodegradable PCL composites exhibit decent mechanical strength(20.7 MPa)even at the MCC fraction of 65 wt%,which is superior to those(5-12.2 MPa)of the highly filled PCL composites(with filler contents of 50-63.8 wt%)reported so far.The proposed approach has sufficient expansibility for the fabrication of the highly filled polymer composites constructed by other types of matrix and fillers.

Stepless shape morphing polymer

To change the situation of shape memory polymers(SMPs)that can only remember very few shapes and enable discretional morphing for practical application,the authors report a reversible stepless multiple SMP derived from ultrahigh molecular weight polyethylene(UHMWPE).As the crystals of semicrystalline polymers are assembled by those with slightly different melting temperatures,and each type of crystal can remember a single shape,the crystalline region of UHMWPE is allowed to remember plenty of temporary shapes after programming.Changing the temperature of the programmed polymer within the melting/crystallization temperature ranges would lead to releasing/recovery of the memorized temporary shapes.Accordingly,multiple shape memory effects can be easily realized without an elaborate design of material structure and training process in advance as before.The temperaturedependent adjustability of the analog capacitor and soft lens with embedded programmed UHMWPE as actuators,characterized by the continuous/random/proportional responsivity,further reveals the utilization prospects of the controllable reversible stepless discretionary morphing effect.Moreover,the maximum work density of the programmed UHMWPE is found to be 210 kJ/m_(3),which is more than 10 times of piezoelectric ceramics,so that it can serve as a proof-of-concept mechanical driver for reversibly pumping of ethanediol-droplet upon heating/cooling.

Synthesis of novel hierarchical porous polymers with a nanowire-interconnected network structure from core-shell polymer nanoobjects

Design and fabrication of the micro/nanostructures of the network units is a critical issue for porous nanonetwork structured materials. Significant progress has been attained in construction of the network units with zero-dimensional spherical shapes.However, owing to the limitations of synthetic methods, construction of porous building blocks in one dimension featuring high aspect ratios for porous nanonetwork structured polymer(PNSP) remains largely unexplored. Here we present the successful design and preparation of PNSP with a novel type of one-dimensional network unit, i.e., microporous heterogeneous nanowire. Well-defined core-shell polymer nanoobjects prepared from a gelable block copolymer, poly(3-(triethoxysilyl)propyl methacrylate)-block-polystyrene are employed as building blocks, and facilely transformed into PNSP via hypercrosslinking of polystyrene shell. The as-prepared PNSP exhibits unique three-dimensional hierarchical nanonetwork morphologies with large surface area. These findings could provide a new avenue for fabrication of unique well-defined PNSP, and thus generate valuable breakthroughs in many applications.

Modeling and simulation of temperature control system in plant factory using energy balance

Closed production systems,such as plant factories and vertical farms,have emerged to ensure a sustainable supply of fresh food,to cope with the increasing consumption of natural resource for the growing population.In a plant factory,a microclimate model is one of the direct control components of a whole system.In order to better realize the dynamic regulation for the microclimate model,energy-saving and consumption reduction,it is necessary to optimize the environmental parameters in the plant factory,and thereby to determine the influencing factors of atmosphere control systems.Therefore,this study aims to identify accurate microclimate models,and further to predict temperature change based on the experimental data,using the classification and regression trees(CART)algorithm.A random forest theory was used to represent the temperature control system.A mechanism model of the temperature control system was proposed to improve the performance of the plant factories.In terms of energy efficiency,the main influencing factors on temperature change in the plant factories were obtained,including the temperature and air volume flow of the temperature control device,as well as the internal relative humidity.The generalization error of the prediction model can reach 0.0907.The results demonstrated that the proposed model can present the quantitative relationship and prediction function.This study can provide a reference for the design of high-precision environmental control systems in plant factories.