925 research outputs found
Bionanocomposites based on 3-hydroxybutyrate-co-3-hydroxyvalerate (PHBV) and cellulose nanowhiskers (CNWs)
Over the past decade, bio-based polymers, especially in packaging, have gained a bigger role due to the over consuming of petrol derivates and the gradually growing concerns relating environment and sustainability issues. The urgent need to have high-performance renewable and natural-base polymers is increasing world-wide. At the same time, the price of those polymers is rising in direct proportion of its studies. Therefore, many researchers have focused in combining those polymers with other natural materials such as cellulose fibers to reduce its cost while maintaining or enhancing their properties. Here, we reproduce a system to obtain the functional reinforcement cellulose nanowhiskers (CNWs) for enhancing mechanical behavior and understanding the interaction between the CNWs PHBV. We divide the main objective in two parts: manufacturing the CNWs and the composite with PHBV of it in the lab, and an evaluation of the mechanical and thermal properties of the composite. The result shows that the CNWs can be obtained by acid hydrolysis in lab and can enhance part of the physical properties of PHBV.En la darrera década, el biopolímers, sobretot en el negoci de l'empaquetatge, han adquirit una major importancia, degut al consum massiu de derivats del petroli i la creixent preocupació per temes com el medi ambient i la sostenibilitat. La urgent neccessitat de tenir polímers d'alta eficiencia, renovables i de base natural, s'està expandint mundialment. Al mateix temps, el preu d'aquests polímers augmenta proporcionalment al nombre d'estudis que hi ha sobre aquests. Per aquesta raó, molt investigadors s'han centrar en la combinació de polímers amb materials naturals com fibras de celulosa, per així reduir el seu cost, mantenint i fins i tot millorar les seves propietats. En aquest projecte, reproduïm un sistema d'obtenció de CNWs per a millorar el comportament mecànic i la comprensió de les interaccions entre CNWs i PHBV. Dividim el treball en dos sub-objectius: la manufacturació de CNWs i el composit amb PHBV, i la avaluació de les propietats mecàniques i tèrmiques del composit.En la última década, bio-polímeros, sobretodo en embalajes, han adquirido mayor importancia, debido al sobre consumo de los derivados del petróleo y la creciente preocupación por temas como el medio ambiente y la sostenibilidad. La urgente necesidad de tener polímeros de alta eficiencia, renovables y de base natural, está expandiéndose mundialmente. Al mismo tiempo, el precio de esos polímeros aumenta proporcionalmente al número de estudios sobre estos. Por esa razón, muchos investigadores se han centrado en la combinación de polímeros con materiales naturales como fibras de celulosa, para así reducir su coste, manteniendo o incluso mejorando sus propiedades. En este proyecto, reproducimos un sistema de obtención de CNWs para mejora de comportamiento mecánico y la comprensión de las interacciones entre CNWs y PHBV. Dividimos el trabajo en dos sub-objetivos: la manufacturación de CNWs i el composit con PHBV, y la evaluación de las propiedades mecánicas y términcas del composit
Verification of Solutions for Almost Linear Complementarity Problems
We present a computational enclosure method for the solution of a class of nonlinear complementarity problems.
The procedure also delivers a proof for the uniqueness of the solution
Beamforming and Power Splitting Designs for AN-aided Secure Multi-user MIMO SWIPT Systems
In this paper, an energy harvesting scheme for a multi-user
multiple-input-multiple-output (MIMO) secrecy channel with artificial noise
(AN) transmission is investigated. Joint optimization of the transmit
beamforming matrix, the AN covariance matrix, and the power splitting ratio is
conducted to minimize the transmit power under the target secrecy rate, the
total transmit power, and the harvested energy constraints. The original
problem is shown to be non-convex, which is tackled by a two-layer
decomposition approach. The inner layer problem is solved through semi-definite
relaxation, and the outer problem, on the other hand, is shown to be a single-
variable optimization that can be solved by one-dimensional (1- D) line search.
To reduce computational complexity, a sequential parametric convex
approximation (SPCA) method is proposed to find a near-optimal solution. The
work is then extended to the imperfect channel state information case with
norm-bounded channel errors. Furthermore, tightness of the relaxation for the
proposed schemes are validated by showing that the optimal solution of the
relaxed problem is rank-one. Simulation results demonstrate that the proposed
SPCA method achieves the same performance as the scheme based on 1-D but with
much lower complexity.Comment: 12 pages, 6 figures, submitted for possible publicatio
Parallel Graph Connectivity in Log Diameter Rounds
We study graph connectivity problem in MPC model. On an undirected graph with
nodes and edges, round connectivity algorithms have been
known for over 35 years. However, no algorithms with better complexity bounds
were known. In this work, we give fully scalable, faster algorithms for the
connectivity problem, by parameterizing the time complexity as a function of
the diameter of the graph. Our main result is a
time connectivity algorithm for diameter- graphs, using total
memory. If our algorithm can use more memory, it can terminate in fewer rounds,
and there is no lower bound on the memory per processor.
We extend our results to related graph problems such as spanning forest,
finding a DFS sequence, exact/approximate minimum spanning forest, and
bottleneck spanning forest. We also show that achieving similar bounds for
reachability in directed graphs would imply faster boolean matrix
multiplication algorithms.
We introduce several new algorithmic ideas. We describe a general technique
called double exponential speed problem size reduction which roughly means that
if we can use total memory to reduce a problem from size to , for
in one phase, then we can solve the problem in
phases. In order to achieve this fast reduction for graph
connectivity, we use a multistep algorithm. One key step is a carefully
constructed truncated broadcasting scheme where each node broadcasts neighbor
sets to its neighbors in a way that limits the size of the resulting neighbor
sets. Another key step is random leader contraction, where we choose a smaller
set of leaders than many previous works do
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