Structure-Property Correlation on Solvent-Fractionated Lignin to Functional Materials

The abundance of lignin in combination with its impressive properties, i.e., a macromolecule with multifunctional groups, an amphiphilic molecular structure, and a unique nanotechnological advantage of forming nanospheres, have attracted an intensified interest in engaging this natural polyphenol in functional materials. However, native lignin is not the lignin that is available for applications, and the structure of lignin may significantly change during pulping or other biorefinery processes. In this scenario, a given sample of lignin possesses significant variability concerning impurities (e.g., extractives and carbohydrates) and has heterogeneous structural features. These aspects, together with the underlying analytical challenges, have substantially constrained the valorization of lignin. Therefore, fractionation of lignin to produce fractions with decreased heterogeneity and well-defined properties is of utmost importance, leading to breakthroughs in efficiently integrating lignin in functional materials. This thesis is dedicated to using a sequential solvent fractionation approach (isopropyl alcohol, ethanol, and methanol) to establish correlations between the structural characteristics of the lignin fractions and material properties of lignin and to reveal the determining factors of lignin utilization in certain applications. Furthermore, the lignin structure-property correlation will be used to tailor the properties of lignin integrated functional materials. The effectiveness of this strategy was validated in the fractionation of birch and spruce alkaline lignin, where lignin fractions with well-defined properties, e.g., molar mass, content of functional groups, and degree of condensation, were obtained. The deployed lignin solvent fractionation strategy revealed fundamental insights into the correlation between the molar-mass-dependent differences of lignin fractions and the chemical accessibility to synthesize a thermosetting lignin-containing phenol-formaldehyde adhesive. In the current work, up to 70% of phenols could be replaced by birch alkaline lignin fractions. Nano-sized lignin, such as lignin nanoparticles (LNPs), is rising as a class of sustainable nanomaterials, which can function as a template to modulate surface functionalization via interfacial interactions. This thesis proposed a high-efficacy route to integrate lignin as a bioplastic in poly (butyl acrylate-comethyl methacrylate) acrylic latex formulation by fabricating polymerizationactive LNPs with surface-arranged allyl groups. The interfacial-modulating function on the LNPs regulated the core-shell emulsion polymerization of acrylate monomers and successfully produced a multi-energy dissipative latex film structure containing a lignin-dominating core. Depending on the surface chemistry metrics of LNPs, such as the abundance of polymerization-active anchors, polymeric flexibility, and surface hydrophobicity, the LNP-integrated latex film could achieve a high toughness almost three times higher than that of the neat latex film. In addition to chemical functionalization, this thesis also upgraded lignin through a biochemical functionalization strategy. First, a lignin solvent fractionation approach was successfully applied to reveal fundamental insights on the correlation between the lignin structural characteristics and the laccaseassisted oxidation/polymerization properties. The fractionation-dependent lignin polymerization kinetics also brought new insights into in situ polymerization of lignin fractions on nanocellulose templates, where the dispersion of nanocellulose with its fiber evenly decorated by aligned LNPs was obtained. Moreover, the cellulose-lignin nanocomposite film exhibited enhanced water barrier properties when compared to the neat cellulose film, which provides a sustainable solution for the development of functional biobased packaging materials. Second, the lignin reactivity could be fine-tuned using solvent fractionation in combination with the laccase-catalyzed polymerization approach, which endowed LNPs from laccase-polymerized lignin (L-LNPs) with dispersion durability and surface functionality in highly alkaline conditions. Subsequently, the L-LNP was utilized as a highly dispersible and nano-sized polymeric template for in situ reduction of Ag+ from silver ammonia solution (pH 11), which resulted in a uniform surfaceembedded hierarchical nanostructure of lignin-silver nanosphere. The durable dispersibility and optical properties of lignin-silver nanospheres endowed the photo-crosslinkable resin of methacrylated O-acetyl-galactoglucomannan with improved printing fidelity in three-dimensional printing. In general, this thesis provides green solutions for upgrading lignin with desired properties for efficient chemical integration in functional materials.Överskottet av lignin i kombination med dess imponerande egenskaper, det vill säga en makromolekyl med multifunktionella grupper, amfifila egenskaper och en unik nanoteknisk fördel vid bildandet av nanosfärer, har väckt ett intensifierat intresse att dra nytta av denna naturliga polyfenol i funktionella material. Naturligt lignin finns dock inte tillgängligt för dessa applikationer, och strukturen hos lignin kan förändras avsevärt under massatillverkning eller andra bioraffinaderiprocesser. Tekniskt lignin har betydande variationer i avseende på föroreningar (till exempel extraktivämnen och kolhydrater) och har heterogena strukturella egenskaper. Dessa aspekter, tillsammans med de analytiska utmaningarna, har väsentligt begränsat valoriseringen av lignin. Därför är fraktionering av lignin för att producera ligninfraktioner med minskad heterogenitet och väldefinierade egenskaper av största vikt för att leda till genombrott i att effektivt integrera lignin i funktionella material. I denna avhandling användes en fraktioneringsstrategi med sekventiell lösningsmedelsextraktion (isopropylalkohol, etanol och metanol) för att fastställa korrelationer mellan de strukturella egenskaperna hos ligninfraktionerna och materialegenskaperna hos fraktionerna, och för att avslöja de avgörande faktorerna för ligninanvändning i vissa applikationer. Vidare användes ligninstrukturegenskaps-korrelationen för att skräddarsy egenskaperna hos ligninintegrerade funktionella material. Effektiviteten av denna strategi validerades genom fraktionering av alkaliskt lignin utvunnet från björk eller gran. Ligninfraktionerna som erhölls hade väldefinierade egenskaper, som till exempel molmassa, innehåll av funktionella grupper och kondensationsgrad. Den använda fraktioneringsstrategin med olika lösningsmedel gav grundläggande insikter i korrelationen mellan molmassa hos fraktionen och den kemiska tillgängligheten för att syntetisera ett värmehärdande lignininnehållande fenolformaldehydlim. I detta arbete visades att upp till 70 % fenolerna kunde ersättas med alkaliska ligninfraktioner från björk. Lignin i nanostorlek, till exempel ligninnanopartiklar (LNP), blir allt viktigare som en klass av hållbara nanomaterial. Dessa kan fungera som en mall för att modulera ytfunktionaliseringen via gränssnittsinteraktioner. I denna avhandling beskrivs en högeffektiv väg att integrera lignin som bioplast i poly(butylakrylat-co-metylmetakrylat)akryllatex genom att tillverka polymerisationsaktiva LNP med allylgrupper på ytan. Genom att modifiera gränsytan på ligninnanopartiklarna kunde kärnemulsionspolymerisationen av akrylatmonomerer regleras och en multienergidissipativ latexfilmstruktur innehållande en lignindominerande kärna framgångsrikt produceras. Beroende på de ytkemiska egenskaperna för LNP, såsom överskottet av polymerisationsaktiva ankare, polymerflexibilitet och ythydrofobicitet, kan den LNP-integrerade latexfilmen uppnå en hög seghet som är nästan tre gånger högre än den ursprungliga latexfilmens. I tillägg till kemisk funktionalisering, visar denna avhandling också att lignin kan uppgraderas genom en biokemisk funktionaliseringsstrategi. För det första tillämpades fraktioneringsmetoden av lignin med olika lösningsmedel framgångsrikt för att avslöja grundläggande insikter om korrelationen mellan ligninets strukturella egenskaper och prestandan för lackasassisterad ligninoxidation och -polymerisation. Den fraktioneringsberoende ligninpolymerisations-kinetiken gav också nya insikter i in situ polymerisering av ligninfraktioner på nanocellulosamallar, där en dispersion av nanocellulosa på vars fibrer LNP förekom regelbundet, erhölls. Dessutom uppvisade nanokompositfilmen av cellulosa-lignin förbättrade vattenbarriäregenskaper jämfört med den ursprungliga cellulosafilmen, vilket ger en hållbar lösning för utveckling av funktionella biobaserade förpackningsmaterial. För det andra kunde ligninreaktiviteten finjusteras med hjälp av lösningsmedelsfraktionering i kombination med en lackaskatalyserad polymerisationsmetod, som gav LNP från lackaspolymeriserat lignin (L-LNP) med hög dispersionshållbarhet och ytfunktionalitet vid extrema alkaliska förhållanden. Därefter användes L-LNP som en polymermall i nanostorlek med hög dispergerbarhet för ”in situ”-reduktion av Ag+ från en silverammoniaklösning (pH 11), vilket resulterade i en enhetlig ytinbäddad hierarkisk nanostruktur av lignin-silvernanosfärer. Den durabla dispergerbarheten och de optiska egenskaperna hos nanosfärer av lignin-silver gav det fototvärbindningsbara hartset av metakrylerad O-acetylgalaktoglukomannan en förbättrad tillförlitlighet vid tredimensionell utskrift. Generellt ger denna avhandling gröna lösningar för uppgradering av lignin med önskade egenskaper för effektiv kemisk integration i funktionella material

Showing more kindness to disabled tourists because of understanding: The interaction among the perceived level of information, affection and altruistic behavior intention

It is the common responsibility of the whole society to provide friendly and appropriate help for disabled tourists.However, the altruistic behavior of ordinary tourists towards disabled tourists has been ignored in academia, and few studies have focused on the internal factors that affect the altruistic behavior of ordinary tourists. To fill in these gaps, planning to investigate 500 respondents, based on The Tri-component attitude model, this study, applying SEM, will examine the effect of ordinary tourists\u27 perceived level of information about the travel barriers faced by physical disabled tourists on their empathy and discomfort, which positively affected their altruistic behavior intention to physical disabledtourists. Moreover, the contents of ordinary tourists\u27 perceived level of information and information source will be explored through 10 in-depth interviews. Theoretical and practical implications of this research were discussed as well

COMPARATIVE KINEMATIC ANALYSIS OF ENQVIST AND MOYA’S TENNIS SERVE TECHNOLOGY

Serving occupies a more important role in the modern tennis. The tennis serve of two players, Thomas Enqvist and Carles Moya, were filmed in the semifinals of Chengdu Open-ATP Champions Tour and analysed with three-dimensional video analysis. The serve was divided into three stages as follows: throwing ball rising racket stage, backward swing stage, forward swing hitting stage. It is found that: in the first stage, the maximum value of shoulder-hip level projection angle of Enqvist and Moya are 18.5° and 28.7° respectively. In the second stage, Enqvist and Moya’s extension range of left knee joint were 55.1° and 34.6°.Their e angular velocity were 182.6°/s and 170.4°/s. In the third stage, Enqvist and Moya’s hitting height were 2.23m and 2.15m, Hitting height and body height ratio were 1.18 and 1.13, there are significant differences

Improving the Generalizability of Trajectory Prediction Models with Frenet-Based Domain Normalization

Predicting the future trajectories of nearby objects plays a pivotal role in Robotics and Automation such as autonomous driving. While learning-based trajectory prediction methods have achieved remarkable performance on public benchmarks, the generalization ability of these approaches remains questionable. The poor generalizability on unseen domains, a well-recognized defect of data-driven approaches, can potentially harm the real-world performance of trajectory prediction models. We are thus motivated to improve generalization ability of models instead of merely pursuing high accuracy on average. Due to the lack of benchmarks for quantifying the generalization ability of trajectory predictors, we first construct a new benchmark called argoverse-shift, where the data distributions of domains are significantly different. Using this benchmark for evaluation, we identify that the domain shift problem seriously hinders the generalization of trajectory predictors since state-of-the-art approaches suffer from severe performance degradation when facing those out-of-distribution scenes. To enhance the robustness of models against domain shift problem, we propose a plug-and-play strategy for domain normalization in trajectory prediction. Our strategy utilizes the Frenet coordinate frame for modeling and can effectively narrow the domain gap of different scenes caused by the variety of road geometry and topology. Experiments show that our strategy noticeably boosts the prediction performance of the state-of-the-art in domains that were previously unseen to the models, thereby improving the generalization ability of data-driven trajectory prediction methods.Comment: This paper was accepted by 2023 IEEE International Conference on Robotics and Automation (ICRA

First-principles study, fabrication and characterization of (Zr0.25Nb0.25Ti0.25V0.25)C high-entropy ceramic

The formation possibility of a new (Zr0.25Nb0.25Ti0.25V0.25)C high-entropy ceramic (ZHC-1) was first analyzed by the first-principles calculations and thermodynamical analysis and then it was successfully fabricated by hot pressing sintering technique. The first-principles calculation results showed that the mixing enthalpy of ZHC-1 was 5.526 kJ/mol and the mixing entropy of ZHC-1 was in the range of 0.693R-1.040R. The thermodynamical analysis results showed that ZHC-1 was thermodynamically stable above 959 K owing to its negative mixing Gibbs free energy. The experimental results showed that the as-prepared ZHC-1 (95.1% relative density) possessed a single rock-salt crystal structure, some interesting nanoplate-like structures and high compositional uniformity from nanoscale to microscale. By taking advantage of these unique features, compared with the initial metal carbides (ZrC, NbC, TiC and VC), it showed a relatively low thermal conductivity of 15.3 + - 0.3 W/(m.K) at room temperature, which was due to the presence of solid solution effects, nanoplates and porosity. Meanwhile, it exhibited the relatively high nanohardness of 30.3 + - 0.7 GPa and elastic modulus of 460.4 + - 19.2 GPa and the higher fracture toughness of 4.7 + - 0.5 MPa.m1/2, which were attributed to the solid solution strengthening mechanism and nanoplate pullout and microcrack deflection toughening mechanism.Comment: 49 pages,6 figures, 4 table

Quantum Machine Learning for Recognizing Gaussian Discord

The quantum correlations measured by quantum discord have been paying significant attention since they are an essential resource for quantum information. This thesis focuses on the quantum discord in continuous-variable (CV) quantum computing systems, especially the quantum discord of the bipartite Gaussian states. We recognize the Gaussian quantum discord using quantum machine learning. We review in detail the CV quantum computing systems that implement hybrid quantum-classical machine learning algorithms. Both Gaussian and non-Gaussian transformations are necessary to construct universal quantum computing systems. The structure of quantum discord can be studied using Gaussian states. The analytical solutions of Gaussian quantum discord are the labels of Gaussian states data set used for training and evaluating machine learning models. We presented the classical machine learning optimization algorithm back-propagating (BP) of the neural network to realize quantum Gaussian discord. We proposed the supervised hybrid quantum-classical optimization performed on the variational quantum circuits for the Gaussian discord classification tasks. Moreover, we implemented a hybrid quantum-classical machine learning algorithm: Quantum Kitchen Sinks (QKS) for noisy intermediate-scale quantum (NISQ) devices. QKS uses the parametric variational quantum circuits to achieve non-linearly transformation from classical inputs to higher-dimensional feature vectors. Simulating the QKS on classical computers with the help of PennyLane, we demonstrated that the variational quantum circuits provide more excellent performance than the classical linear classification algorithm, successfully improving the classification accuracy from 70.12% up to 98.64%

The Application of Driver Models in the Safety Assessment of Autonomous Vehicles: A Survey

Driver models play a vital role in developing and verifying autonomous vehicles (AVs). Previously, they are mainly applied in traffic flow simulation to model realistic driver behavior. With the development of AVs, driver models attract much attention again due to their potential contributions to AV certification. The simulation-based testing method is considered an effective measure to accelerate AV testing due to its safe and efficient characteristics. Nonetheless, realistic driver models are prerequisites for valid simulation results. Additionally, an AV is assumed to be at least as safe as a careful and competent driver. Therefore, driver models are inevitable for AV safety assessment. However, no comparison or discussion of driver models is available regarding their utility to AVs in the last five years despite their necessities in the release of AVs. This motivates us to present a comprehensive survey of driver models in the paper and compare their applicability. Requirements for driver models in terms of their application to AV safety assessment are discussed. A summary of driver models for simulation-based testing and AV certification is provided. Evaluation metrics are defined to compare their strength and weakness. Finally, an architecture for a careful and competent driver model is proposed. Challenges and future work are elaborated. This study gives related researchers especially regulators an overview and helps them to define appropriate driver models for AVs