30 research outputs found
Oral POLYMER BASED ELECTRO-ACTIVE MICRO-AND NANO-COMPOSITES
Abstract Polymeric materials filled with micro and nanoparticles have been widely investigated in the last few years. Till recently, mainly the mechanical reinforcement effect of these nanofillers was highlighted. Nowadays, several composites and nano-composites of electroactive polymers have been investigated due to their potential applications. In this way, carbon nanotubes/ polymer nanocomposites with high dielectric constant; electroactive polymers with metallic nanoparticles in order to tune electro-optic properties, magnetostrictive nanoparticles inducing magntoelectric response, and the introduction of ceramic microparticles to tune dielectric and piezoelectric properties have been investigated. In order to achieve the desired electromechanical, magnetoelectric and electro-optical properties, the composites have to poled The general issues related to the processing of the electroactive composites such as dispersion, stretching and poling will be presented and discussed. The influence of these parameters on some key macroscopic properties such as the electrical and mechanical properties will be also presented. Particular attention will be drawn on the stretching and poling process necessary to achieve NanoSpain2008 14-18 April, 2008 Braga-Portugal Oral polar β-phase within the polymeric matrix, as this critical step shows specific issues within the different nanocomposites. Acknowledgement
Dielectric relaxation dynamics of high-temperature piezoelectric polyimide copolymers
Polyimide co-polymers have been prepared based on different diamines as co-monomers:
a diamine without CN groups and a novel synthesized diamine with two CN groups
prepared by polycondensation reaction followed by thermal cyclodehydration. Dielectric
spectroscopy measurements were performed and the dielectric complex function, ac
conductivity and electric modulus of the co-polymers were investigated as a function of
CN group content in the frequency range from 0.1 Hz to 107
Hz at temperatures from 25
to 260 °C.
For all samples and temperatures above 150ºC, the dielectric constant increases with
increasing temperature due to increaseing conductivity. The α-relaxation is just detected
for the sample without CN groups, being this relaxation overlapped by the electrical
conductivity contributions in the remaining samples. For the copolymer samples and the
polymer with CN groups an important Maxwell-Wagner-Sillars contribution is detected.
The mechanisms responsible for the dielectric relaxation, conduction process and electric
modulus response have been discussed as a function of the CN groups content present in
the samples.This work was supported by FEDER through the COMPETE Program and by the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Project PESTC/FIS/UI607/2011 and grants SFRH/BD/ 62507/2009 (A.C.L.) SFRH/BD/68499/2010 (C.M.C.). The authors also thank funding from “Matepro – Optimizing Materials and Processes”, ref. NORTE-07-0124-FEDER-000037”, co-funded by the “Programa Operacional Regional do Norte” (ON.2 – O Novo Norte), under the “Quadro de Referência Estratégico Nacional” (QREN), through the “Fundo Europeu de Desenvolvimento Regional” (FEDER). RSS acknowledge the support of the Spanish Ministry of Economy and Competitiveness through the project MAT2012-38359-C03-01 (including the FEDER financial support). Authors also thank the Basque Country Government for financial support (ACTIMAT project, ETORTEK Program, IE13-380, and Ayudas para Grupos de Investigación del Sistema Universitario Vasco Program, IT718-13)
Política linguística e internacionalização: a língua portuguesa no mundo globalizado do século XXI
Fungal diversity notes 929–1035: taxonomic and phylogenetic contributions on genera and species of fungi
This article is the ninth in the series of Fungal Diversity Notes, where 107 taxa distributed in three phyla, nine classes, 31 orders and 57 families are described and illustrated. Taxa described in the present study include 12 new genera, 74 new species, three new combinations, two reference specimens, a re-circumscription of the epitype, and 15 records of sexualasexual morph connections, new hosts and new geographical distributions. Twelve new genera comprise Brunneofusispora, Brunneomurispora, Liua, Lonicericola, Neoeutypella, Paratrimmatostroma, Parazalerion, Proliferophorum, Pseudoastrosphaeriellopsis, Septomelanconiella, Velebitea and Vicosamyces. Seventy-four new species are Agaricus memnonius, A. langensis, Aleurodiscus patagonicus, Amanita flavoalba, A. subtropicana, Amphisphaeria mangrovei, Baorangia major, Bartalinia kunmingensis, Brunneofusispora sinensis, Brunneomurispora lonicerae, Capronia camelliaeyunnanensis, Clavulina thindii, Coniochaeta simbalensis, Conlarium thailandense, Coprinus trigonosporus, Liua muriformis, Cyphellophora filicis, Cytospora ulmicola, Dacrymyces invisibilis, Dictyocheirospora metroxylonis, Distoseptispora thysanolaenae, Emericellopsis koreana, Galiicola baoshanensis, Hygrocybe lucida, Hypoxylon teeravasati, Hyweljonesia indica, Keissleriella caraganae, Lactarius olivaceopallidus, Lactifluus midnapurensis, Lembosia brigadeirensis, Leptosphaeria urticae, Lonicericola hyaloseptispora, Lophiotrema mucilaginosis, Marasmiellus bicoloripes, Marasmius indojasminodorus, Micropeltis phetchaburiensis, Mucor orantomantidis, Murilentithecium lonicerae, Neobambusicola brunnea, Neoeutypella baoshanensis, Neoroussoella heveae, Neosetophoma lonicerae, Ophiobolus malleolus, Parabambusicola thysanolaenae, Paratrimmatostroma kunmingensis, Parazalerion indica, Penicillium dokdoense, Peroneutypa mangrovei, Phaeosphaeria cycadis, Phanerochaete australosanguinea, Plectosphaerella kunmingensis, Plenodomus artemisiae, P. lijiangensis, Proliferophorum thailandicum, Pseudoastrosphaeriellopsis kaveriana, Pseudohelicomyces menglunicus, Pseudoplagiostoma mangiferae, Robillarda mangiferae, Roussoella elaeicola, Russula choptae, R. uttarakhandia, Septomelanconiella thailandica, Spencermartinsia acericola, Sphaerellopsis isthmospora, Thozetella lithocarpi, Trechispora echinospora, Tremellochaete atlantica, Trichoderma koreanum, T. pinicola, T. rugulosum, Velebitea chrysotexta, Vicosamyces venturisporus, Wojnowiciella kunmingensis and Zopfiella indica. Three new combinations are Baorangia rufomaculata, Lanmaoa pallidorosea and Wojnowiciella rosicola. The reference specimens of Canalisporium kenyense and Tamsiniella labiosa are designated. The epitype of Sarcopeziza sicula is re-circumscribed based on cyto- and histochemical analyses. The sexual-asexual morph connection of Plenodomus sinensis is reported from ferns and Cirsium for the first time. In addition, the new host records and country records are Amanita altipes, A. melleialba, Amarenomyces dactylidis, Chaetosphaeria panamensis, Coniella vitis, Coprinopsis kubickae, Dothiorella sarmentorum, Leptobacillium leptobactrum var. calidus, Muyocopron lithocarpi, Neoroussoella solani, Periconia cortaderiae, Phragmocamarosporium hederae, Sphaerellopsis paraphysata and Sphaeropsis eucalypticola
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4
While the increasing availability of global databases on ecological communities has advanced our knowledge
of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In
the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of
Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus
crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced
environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian
Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by
2050. This means that unless we take immediate action, we will not be able to establish their current status,
much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio
Acúmulo de matéria seca e óleo nas sementes de pinhão-manso e qualidade do óleo extraído
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost