RECOVERING AND UPGRADING KRAFT LIGNIN FOR APPLICATION IN FLEXIBLE POLYURETHANE FOAM

Lignin is the second abundant natural polymer and has been highlighted as a potential substitute for fossil-based raw materials. However, the inherent molecular heterogeneity and the complex recovery processes result in the challenge of controlling the molecular properties and value-added applications of lignin in large scale. To address those issues, a novel acid-liquefaction process was developed in this study to recover Kraft lignin with improved molecular homogeneity directly from black liquor. In the first study, the liquefaction parameters were screened based on yield and molecular weight properties of the recovered lignin. Then, the recovered lignin samples were used to replace 20 wt% of the fossil-based polyols to prepare flexible polyurethane foams. It was found that most of the recovered lignin had improved molecular uniformity (polydispersity (PDI) value \u3c 2) than the traditional acid-precipitated lignin (PDI = 2.2~5.4). Also, the recovered lignin with the Mw value of 1600 Da and the PDI value of 1.8 could maintain the major properties of the flexible PU foams. In the second study, the Box-Behnken response surface methodology (RSM) was employed to investigate the effects of the liquefaction parameters (pH, reaction temperature, and reaction time) on the yield, molecular weights, polydispersity, and quantities of different types of hydroxyl groups of the lignin. Computational models were developed and refined to establish the relationships between the liquefaction parameters and the lignin properties. The yield, molecular weight, and polydispersity of the lignin could be predicted by the optimized models with high R2(pred) values of 87.5-91.5%. An iron-based desulfurization process was developed in third study to remove covalently bonded sulfur in the lignin. The effects of the desulfurization parameters, including reaction temperature, time, and amount of iron, on the sulfur content and desulfurization rate of the lignin were studied. It was found that the highest desulfurization rate was 39.3% at 90 ℃, 16 h, and 0.3 g iron. A life cycle assessment on the lignin production processes and its comparison to the fossil-based polyols were demonstrated in the last study. The lignin produced from the liquefaction process with 140 ℃, pH = 7, and 9 min was more suitable for replacing the fossil-based polyols due to lower CO2 emissions and energy consumptions

The spin alignment of galaxies with the large-scale tidal field in hydrodynamic simulations

The correlation between the spins of dark matter halos and the large-scale structure (LSS) has been studied in great detail over a large redshift range, while investigations of galaxies are still incomplete. Motivated by this point, we use the state-of-the-art hydrodynamic simulation, Illustris-1, to investigate mainly the spin--LSS correlation of galaxies at redshift of $z=0$. We mainly find that the spins of low-mass, blue, oblate galaxies are preferentially aligned with the slowest collapsing direction ($e_3$) of the large-scale tidal field, while massive, red, prolate galaxy spins tend to be perpendicular to $e_3$. The transition from a parallel to a perpendicular trend occurs at $\sim10^{9.4} M_{\odot}/h$ in the stellar mass, $\sim0.62$ in the g-r color, and $\sim0.4$ in triaxiality. The transition stellar mass decreases with increasing redshifts. The alignment was found to be primarily correlated with the galaxy stellar mass. Our results are consistent with previous studies both in N-body simulations and observations. Our study also fills the vacancy in the study of the galaxy spin--LSS correlation at $z=0$ using hydrodynamical simulations and also provides important insight to understand the formation and evolution of galaxy angular momentum.Comment: 9 pages, 6 figures, 1 table. Accepted for publication in ApJ, match the proof versio

Multiagent Bidirectionally-Coordinated Nets: Emergence of Human-level Coordination in Learning to Play StarCraft Combat Games

Many artificial intelligence (AI) applications often require multiple intelligent agents to work in a collaborative effort. Efficient learning for intra-agent communication and coordination is an indispensable step towards general AI. In this paper, we take StarCraft combat game as a case study, where the task is to coordinate multiple agents as a team to defeat their enemies. To maintain a scalable yet effective communication protocol, we introduce a Multiagent Bidirectionally-Coordinated Network (BiCNet ['bIknet]) with a vectorised extension of actor-critic formulation. We show that BiCNet can handle different types of combats with arbitrary numbers of AI agents for both sides. Our analysis demonstrates that without any supervisions such as human demonstrations or labelled data, BiCNet could learn various types of advanced coordination strategies that have been commonly used by experienced game players. In our experiments, we evaluate our approach against multiple baselines under different scenarios; it shows state-of-the-art performance, and possesses potential values for large-scale real-world applications.Comment: 10 pages, 10 figures. Previously as title: "Multiagent Bidirectionally-Coordinated Nets for Learning to Play StarCraft Combat Games", Mar 201

Foreclosure of Securitized Commercial Mortgages - A Model of the Special Servicer

The decision to foreclose on a CMBS mortgage is made by the special servicer. A mortgage loan is in special servicing when it is either delinquent or in a state of imminent default. A special servicer should represent the interests of the underlying CMBS bondholders by returning the highest possible value to the investors. In this paper, we show that a special servicer\u27s compensation structure results in an incentive for her to extend a loan beyond the time desired by its bondholders. We develop a model and demonstrate how compensation incentives interact and influence a special servicer\u27s foreclosure decisions. Our model takes into consideration the dynamic nature of such a decision by viewing is as a dynamic programming problem whereby foreclosure represents a discrete terminal state of an optimal stopping problem. This model thus captures the trade-off between continuation of a loan and termination and we use this model to determine how the stopping rule changes under various compensation structures

R&D, intellectual capital, organizational learning, and firm performance: a study of Chinese software companies

This research establishes a theoretical model to test the interrelationships among R&D investment, intellectual capital, organizational learning, and firm performance. Based on the collection and investigation of a panel dataset gleaned from 26 software companies in 28 time periods, we find that: (1) R&D investment of software enterprises and firm performance are positively correlated; (2) intellectual capital fully mediates the R&D investment– performance relationship; and (3) organizational learning of software security vulnerabilities moderates the relationship between R&D investment and intellectual capital in the form of human capital. Based on our findings, we draw both theoretical and managerial implication

The Strength Of Individual Relationships And Employee Knowledge Sharing Behavior

Firm’s core competitiveness results primarily from its ability to innovate. Knowledge sharing plays an important role in promoting sustained innovation. This research examines the factors enabling knowledge sharing in a Research and Development (R&D) department of a Chinese commercial elevator firm. We find that the strength of individual relationships, contextual performance, and IT capability are positively correlated with the strong knowledge sharing behavior, while controlling for gender, education, and job tenure. Based on our findings, we draw both theoretical and managerial implications