Σχεδιασμός Χημικών Προϊόντων

1. Σχεδιασμός Χημικών Προϊόντων Δημήτρης Χατζηαβραμίδης Σχολή Χημικών Μηχανικών Εθνικό Μετσόβιο Πολυτεχνείο ΔΧ

2. Μοριακά Προϊόντα • Φάρμακα: Φαρμακευτικά δραστικές ουσίες (Αctive PharmaceuticalIngredients) • Νανοϋλικά, νανοσωματίδια • Βιολογικά μόρια ΔΧ

3. Νανοσωματίδια • Νανοκλίμακα: 1 nm = 10-9m = 10-3mm = 10 Å • Ατομική κλίμακα (~ Å )<Νανοκλίμακα(~ nm) < Mακροκλίμακα(> 1 mm ) • Γιατί είναι σπουδαία; Γιατί: • Κβαντομηχανικές (κυμματικές)ιδιότητεςτωνηλεκτρονίωνμέσα στο υλικό επιρρεάζονταιαπόδιακυμάνσειςστη νανοκλίμακα⇒ είναι δυνατό ναμεταβληθούν μακροσκοπικές ιδιότητες του υλικού (π.χ., ειδική θερμότητα, θερμοικρασία τήξης, μαγνητική επαγωγή, κλπ.) χωρίς να αλλάξει η σύσταση • Κύριο χαρακτηριστικό τωνβιολογικών συστημάτων είναιη οργάνωσητηςύληςσε νανοκλίμακα ⇒ να κατασκευστούν νέα υλικάκάνοντας χρήση τηςαυτοδιάταξης (self-assembly)τηςφύσης • Τα διάφορα στοιχεία συστημάτων σε νανοκλίμακαέχουν πολύ υψηλό λόγο επιφάνειας προς όγκο ⇒ ιδανικάγια χρήση σε σύνθετα (composite)υλικά, αντιδρώντα συστήματα, χορήγηση φαρμάκων (drug delivery),αποθήκευση χημικής ενέργειας (υδρογόνο, φυσικό αέριο) • Συστήματα που αποτελούνται από νανοδομέςμπορεί να έχουν υψηλότερεςπυκνότητεςκαιαγωγιμότητες από αυτές συστημάτων με μικροδομές • Οι μακροσκοπικές ιδιότητες(μηχανικές, θερμικές, οπτικές, μαγνητικές, ηλεκτρικές, • κλπ.)για συστήματα σενανοκλίμακαείναιαρκετάδιαφορετικέςαπό εκείνες • μακροσκοπικών ήογκώδη (bulk) συστήματα ΔΧ

4. NANOPARTICLES Nanotechnology: The technology to build macro and micro materials and structures with atomic precision According to Feynman (1959), the laws of nature do not limit our ability to work at the molecular level, atom by atom; instead, it was our lack of appropriate equipment and techniques for doing so ⇒ challenge for miniaturization Scientists at IBM (1999) used a nanotechnology tool called Atomic Force Microscope to perform Dip Pen Nanolithography (AFM tip coated with molecular ink and brought into contact with surface to be patterned) Thermodynamics and Statistical Mechanics of small systems, introduced by T. L. Hill in the 1963 to deal with colloidal particles, macromolecules and their mixtures, after formulation of key concepts for nonextensive systems, i.e., systems away from the thermodynamic limit (N → ∞ , V → ∞ , N / V = rN finite), (C. Tsallis, 1988), became Nanothermodynamics Interparticle Potentials for prediction of macroscopic properties Atoms or simple molecules - quantum mechanical ab initio calculations Macrosystems - classical potentials, e.g.,Coulomb, LJ, for ( 1023 particles) covalent and noncovalent interactions Nanosystems - experimental and theoretical development ( finite number of particles) ΔΧ

5. iso skew anti NANOPARTICLES Molecular Building Blocks Diamondoids Buckyballs Carbon nanotubes Cyclodextrins Liposomes Monoclonal Antibodies Diamondoids, also known as cage hydrocarbons, are saturated, polycyclichydrocarbons with diamond-like fused structures (nanostructures that can be superimposed upon a diamond lattice) and highly unusual physical and chemical properties. The common formula for the group is C4n+6H4n+12 , n=1 for adamantane, n=2 for diamantane, n=3 for trimentane, n=4 for tetramentane, etc. First 3 compounds of the group do not possess isomeric forms When n>4, the number of isomersincreases significantly Chirality occurs first in tetramantane Divided into (a) lower diamondoids, diameter 1-2 nm, and (b) higher diamondoids, diameter > 2 nm In solid state, diamondoids melt at much higher temperatures than other hydrocarbon molecules (adamantane, Tm= 266-268oC; diamantane Tm= 241-243oC) with the same number of carbon atoms They possess high density and low-strain energy, and are more stable and stiff ΔΧ

6. NANOPARTICLES • Diamondoids exist as physical components in crude oil, discovered in 1933 in • Czechoslovakia . Adamantine canbe synthesized with zeolites as catalysts • Diamondoid Applications • Three adamantane derivatives, amantadine (1-adamantaneamine hydrochloride), rimantadine (a-methyl-1-adamantane methylamine hydrochloride) and memantine (1-amino-3,5-dimethyladamantane) have been used as antiviral drugs, e.g., prevention and treatment of influenza A viral infections. Also used in treatment of Parkinson’s disease and inhibition of hepatitis C virus (HCV). Reported to be effective in slowing progression of Alzheimer disease. Half-life of derivatives is long (adamandine 12-18 h; rimandine 24-36 h) • Monocationic and dicationic adamantane derivatives block AMPA (A-Amino-3-Hydroxy-5-Methyl-4-Isoxazolepropionic Acid; receptor for glutamatefast synaptic transmission), NMDA(N-methyl D-aspartate mimics action of glutamate on receptor )and 5-HT3 (5-Hydroxytryptamine3; serotonin inhibitor) receptors. Attaching short peptide chains to adamantane makes it possible to design antagonists, e.g., Bradykinin and vasopressin receptor antagonists • Adamantane derivatives can be employed as carriers for drug delivery and targeting systems. Due to their high lipophilicity, attachmentof diamondoids to drugs with low hydrophobicity would lead to increase of drug solubility in lipid membranes and thus increase in drug uptake ΔΧ

7. NANOPARTICLES • DiamondoidApplications • Shortpeptide sequences, lipids and polysaccharides bound to adamantine and provide a binding site for connection of macromolecular drugs and small molecules. Ex. Brain delivery drugs that can pass Brain Blood Barrier, 1-Adamantyl moiety attached to AZT (azidothymidine) drugs (for AIDS) via ester spacer • Adamantane derivatives attached to nucleic acid sequences via an amidelinker used for gene delivery (which has problems with low uptake of nucleic acids by cells, and instabilities in blood stream). DNA and RNA exhibit binding selectivity to polyamine adamantane derivatives (DNA and RNA can be stabilized by binding) • DNA fragments, because of DNA’s unique feature for site-selective immobilization, are used as linkers in DNA-adamantane-proteinnanaostructures. Knowledge of protein folding and conformations in biological systems can help us designnanostructures with desired and predictable conformation in a biomimetic way. Thus, adamantane can be used to construct peptide scaffolding and in synthesis of artificial proteins ΔΧ

8. NANOPARTICLES Buckyballs A Buckyball or Buckminsterfullerene molecule, an allotropic form of carbon, is the most popular discovery in Nanotechnology For this discovery, Kroto and Smalley were awarded the 1996 Nobel Prize in Chemistry Buckyballs are Cn clusters with n>20 ( most common C60 , C70 ; later fullerenes C76 , C80 , C240 , etc). Originally made by laser evaporation of graphite. More efficient and less expensive methods for making them found later A molecule should have at least 2 linking groups to be considered as M(olecular) B(uilding) B(lock). The presence of 3 linking groups would lead to 2-D or a tubular structure formation. Presence of 4 or more linking groups lead to a 3-Dstructure. Molecules with 5linking groups can form a 3-D solid structure; those with 6 linking groups can be attached in a cubic structure. Functionalization of buckyballs with 6 functional groups (for positional or roboticassembly) is presently possible ΔΧ

9. NANOPARTICLES Carbon Nanotubes discovered by Iijima in 1991. He used an electron microscope while studying cathodic material deposition through vaporizing carbon graphite in an electric arc-evaporation reactor under an inert atmosphere during synthesis of fullerenes They appeared to be made of a perfect network of hexagonal graphiterolled up to form a hollow tube The nanotubediameter range, from one to several nm, is much smaller than its length range, from one to several mm Laser ablation chemical vapor deposition joined with metal-catalyzed disproportionation of suitable carbonaceous feedstock are often used to produce carbon nanotubes Carbon nanotubes exhibit unusual photochemical, electronic, thermal and mechanical properties Single-Walled Carbon NanoTubes could behave as metallic, semi-metallic, or semiconductive1-D objects. They have high tensile strength, ~ 100 times that of steel ΔΧ

10. NANOPARTICLES Cyclodextrins are cyclic oligosaccharides in the shape of a truncated cone with a relatively hydrophobic interior. They have the ability to form inclusion complexes with a wide range of substrates in aqueous solutions⇒ encapsulation of drugs for drug delivery Liposomes Spherical synthetic lipid bilayer vesicles, created by dispersion of a phospholipid in aqueous salt solutions. Quite similar to micelles with an internal aqueous compartment Used as carriers for a variety ofdrugs, small molecules, proteins, nucleotides (has nitrogenous base, sugar and phosphate group), even plasmids (extrachromosomal DNA molecule having ability to replicate independently of chromosomal DNA), to tissues and into cells ΔΧ

11. NANOPARTICLES Monoclonal Antibodies A monoclonal antibody protein molecule consists of four protein chains, two heavy and two light, which are folded to form a Y-shaped structure. The small size, 10 nm in diameter, ensures that intravenously administered monoclonal antibodies can penetrate small capillaries and reach cells in tissues where they are needed. Nanostructures smaller than 20 nm can transit out of blood vessels ΔΧ

12. NANOPARTICLES Nano Thermodynamics and Statistical Mechanics The principles of thermodynamics and statistical mechanics are well defined for macroscopic systems and relations between macroscopic properties and molecular characteristics can be derived Basic concepts in Thermodynamics for macroscopic systems are System & Surroundings State of the System & Equilibrium Process & Reversibility / Irreversibility Energy, Heat and Work Properties (extensive and intensive) & Relations among them Axiomatic Basis, i.e., Laws of Thermodynamics Degrees of Freedom of a System Phase Transitions Basic concepts in Statistical Mechanics for macroscopic systems are Ensembles and Averaging Ergodicity PhaseSpace (coordinates) Ground State Correlated and Interacting Systems ΔΧ

13. Nano Thermodynamics and Statistical Mechanics • Differences between Macroscopic and Nanoscale systems • Macroscopic systems can be in any of the three states of matter, gas, liquid, and solid. Nanoscale systems, i.e., isolated nanostructures and their assemblies, small drops, bubbles, clusters, aggregates, nanocrystals, nanowires, etc., are made of condensed (liquid or solid) matter • Macroscopic system size: > 1 mm; 1023 particles in 1 cm3 (thermodynamic limit: N → ∞ , V → ∞ , N / V = rN finite) • Nanoscale system size: > 1 nm; N = finite • Thermodynamic properties, e.g., temperature, for macroscopic systems are well-defined and their fluctuations in time and space are negligible. This is not the case for nanoscale systems the size of which is of the same order as the size of fluctuations. Pressure in nanosystems is not isotropic and must be treated as a tensor • Because of the large size fluctuations in properties, static equilibrium cannot be defined in nanosystems as in macroscopic systems. The states of a nanoscale system can only be in dynamic equilibrium • Because of the large size fluctuations in properties, over short periods of time, processes in nanosystemscannot be reversible as in macroscopic systems However, over long periods of time, processes in nanosystems are expected to be closer to reversibility than those in macroscopic systems ΔΧ

14. Nano Thermodynamics and Statistical Mechanics • Differences between Macroscopic and Nanoscale systems • The definitions of extensive, i.e., system-size-dependent, and intensive , i.e., system-size-independent, properties for macroscopicsystemsdon’t seem to be satisfied in nanosystems • Thermodynamic property relations in macroscopic systems are independent of their surroundings (environment); they are environment-dependent for nanosystems, e.g.,depend on the geometry, size and walls of the confining structure • Energy and mass are mutually interchangeable and the laws of theirconservation are combined into the First Law of Thermodynamics which is universal. Energy measures the ability of the system to induce a change which is visible at the scale of the system. Work and heat, on the other hand, are means of energy exchange between the system and its surroundings. Transfer of energy through work or heat is a visible phenomenon in macroscopic systems but not in nanosystems ⇒ conversion of thermal to mechanical energy in nanosystems ??? • Entropy definition for macroscopic systemscannot be extended to nanosystems • If a macroscopic system is divided into parts, the sum of the entropies of its parts is equal to the entropy of the original system. This is not the case for nanosystems. Macroscopic systems are extensive; nanosystems are • nonextensive ΔΧ

15. Nano Thermodynamics and Statistical Mechanics • Differences between Macroscopic and Nanoscale systems • Phase transitions in macroscopic systems are different than in nanosystems • In first order phase transitions (FOPT)in macroscopic systems, we observe abrupt changes (discontinuities) in entropy and energy associated with the phases, and physically, there is a distinct separating boundary (meniscus in the case of liquid and vapor transition) apparent between the phases. Second order transitions (SOPT), on the other hand, do not exhibit discontinuities in entropy and energy but in their derivatives, e.g., heat capacity = derivative of energy w.r.t. temperature SOPT S FOPT L L ΔΧ

16. Nanothermodynamics and Statistical Mechanics • Differences between Macroscopic and Nanoscale systems • First Order Phase Transitions in macroscopic systems are different than in nanosystems Small system Large system ΔΧ

17. Nanothermodynamics and Statistical Mechanics • Differences between Macroscopic and Nanoscale systems • Phase transitions in nanosystems also include • Fragmentation, a real phase transition of the first order in nuclei, e.g., boiling, liquid fragmentation when the ratio of viscous-to-capillary forces exceeds a critical value, and • Self-assembly, a process in which a set of components or constituentsspontaneouslyforms an ordered aggregate through their global energy minimization ΔΧ

18. Nanothermodynamics and Statistical Mechanics • The Laws of Thermodynamics • Zeroth Law: establishment of an absolute temperature scale • Temperature in a macroscopic system is a well defined property, its fluctuations are negligible and it is a measure of thermal equilibrium or lack of it • In nanosystems, space and time fluctuations cannot be neglected • In view of • temporal scale ~ N (number of particles) • spatial scale ~ N logN, • accuracy scale ~ N7 to N! • Fluctuations in nanosystems are not yet correlated to their properties • Customaryin Statistical Mechanics to express fluctuations in properties in terms ofdistribution functions or as derivatives of other properties • First Law: combination of conservation of mass and energy, both of which are • interchangeable • In macroscopic systems, reversibility is equivalent to thermal equilibrium • Nanosystems may be reversible but not in thermal equilibrium • Similar to macro systems, nanosystems can be open, closed, adiabatic, isothermal, isochoric (constant volume) or isobaric (constant pressure) ΔΧ

19. Nanothermodynamics and Statistical Mechanics • The Laws of Thermodynamics • First Law: combination of conservation of mass and energy, both of which are • interchangeable • dE = dQ + dW (1) • Macroscopic systems: dQ = cdT dW = p dV (2a) • Nanosystems: dW = tij deijdij V (2b) • (tij external stress tensor; eij deformation tensor; dij Kronecker delta, dij = 1 iff i = j) • Second Law: For a closed system entropy production is always nonnegative • dS – dQ / Tex> 0 (3) • Applies both to macroscopic and nano systems, if the concept of entropy is redefined to • include nonextensive systems • Boltzmann defined the entropy of the systems as • S = kB lnW (4) • where W is the number of possible configurations of a system of particles consistent • with the properties of the system. The Boltzmann entropy has two important features: • Non-decrease, i.e. if no heat enters or leaves the system its entropy cannot decrease, • Additivity, i.e, the entropy of systems taken together is the sum of their individual entropies ΔΧ

20. Nanothermodynamics and Statistical Mechanics The Laws of Thermodynamics Entropy The Boltzmann entropy, otherwise called entropy of a coarse-grain distribution is for a macroscopic state over a statistical ensemble with equiprobability. For non- equiprobability, Gibbs consider a system of a large number of particles (e.g., molecules), N, distributed in W classes (e.g., energy states) with non equal probability. If pi = Wi / W (SWi = W), is the probability of the distribution of i particles in the system, the entropy of the system is given by the Boltzmann-Gibbs formula With equiprobability, pi = 1 / W, Eq.(5) reduces to Eq.(4), i.e., the Gibbs-defined entropy becomes the Boltzmann-defined entropy The problem with these definitions of entropy is that they apply to homogeneoussystems with a large number of particles. i.e., systems at the thermodynamic limit. For those systems, the notions of extensivity (additivity) and intensivitiy (averaging) of thermodynamic properties also apply Nanosystems, consist of a finite number of particles and their spatial scale is of the same order of magnitude as the correlation length for their thermodynamic properties ΔΧ

21. Nanothermodynamics and Statistical Mechanics The Laws of Thermodynamics Entropy A new formulation of entropy to include extensive (e.g., macroscopic) as well nonextensive (e.g., nanosystems) was introduced by Tsallis (1988) We need to start with the definition of homogeneous function of degree l f(tx1 , tx2 , tx3 , …, txr) = tl f(x1 , x2 , x3 , …, xr) (6) and Euler’s theorem x1(∂ f / ∂ x1 ) + x2(∂ f / ∂ x2 ) + … + xr(∂ f / ∂ xr ) = l f (7) A thermodynamic variable is intensive when l = 0 , and extensive if l= 1 Tsallis (1988)expressed the entropy as ΔΧ

22. Nanothermodynamics and Statistical Mechanics • The Laws of Thermodynamics • Entropy • q is called entropicindex; q >1 represents frequent events; q < 1 represents rareevents • (piq < pi ) • q is also called extensivityindex; q >1 represents superextensivity (superadditivity), • q = 1 represents extensivity (additivity of entropy), and q < 1 represents subextensivity • (subadditivity) • Depending on the entropic index q, Eq.(8) ⇒ • For q > 0, Sq > 0, i.e., entropy is always positive • For q→ 1, , i.e., the Gibbs-Boltzmann formula • For q = 1, S1 = k lnW , i.e., the Boltzmann formula • Also • For equiprobability, i.e., pi = 1 / W, Eq.(8) ⇒ • 2. In the case of certainty, i.e., all but one probabilities vanish, p1 =1, pi = 0 for i>1, • Eq.(8) ⇒ entropy is zero, Sq = 0 ΔΧ

23. Nanothermodynamics and Statistical Mechanics • The Laws of Thermodynamics • Entropy • When two (statistically) independent systemsA and B join, Eq.(8) ⇒ • If the set of possibilities W is arbitrarily separated into two subsets WL and WM(WL+WM = W), Eq.(8) ⇒ ΔΧ

24. Nanothermodynamics and Statistical Mechanics • The Laws of Thermodynamics • Entropy • The Tsallis entropy has two more additional properties: • Can be tested under translation as well as under dilation • The Boltzmann-Gibbs formula satisfies • Eq.(8) ⇒ • Is alwaysconvex, when q<0, and alwaysconcave, when q > 0 • This is not the case for other definitions of entropy, e.g., Renyi definition of entrolpy for fractal geometries • does not have this property for all values of q ΔΧ

25. Nanothermodynamics and Statistical Mechanics Microcanonical Ensemble for Nonextensive Systems Consider a nanosystem at fixedN, V and T, isolated (no energy exchange) from its surroundings . The entropy of this system, which is given by the Tsallis formula, becomes maximum when the probabilities piare all equal. If W = W (e ) is the number of states with energies centered around e, then pi = 1 / W . For this system, W is called degeneracy and is related to entropy through When the system is at equilibrium, dU = T dS – p dV (12) From (11) and (12) ⇒ i.e., k T W q ∂W is related to the energy change dU. Eq.(13) is a fundamental equation of Statistical Mechanics for nonextensive systems ΔΧ

26. Nanothermodynamics and Statistical Mechanics Canonical Ensemble for Nonextensive Systems Consider now a nanosystem at fixedN, V and T, exchanging energy with its surroundings. We’d like to maximize the entropy of this system, under the constraint that the average energy of the system is constant For a nonextensive system, the internal energy constraint is The other constraint on the system is We employ the method of Lagrange multipliers to minimize the function where b has units of inverse temperature and q is dimensionless. Minimization ⇒ ΔΧ

27. Nanothermodynamics and Statistical Mechanics Canonical Ensemble for Nonextensive Systems Consider now a nanosystem at fixedN, V and T, exchanging energy with its surroundings. We’d like to maximize the entropy of this system, under the constraint that the average energy of the system is constant Eq.(16) ⇒ where Zq is the canonical ensemble partition function for nonextensive systems Intermolecular Potentials Thedatabaseof intermolecular potentials of simple fluids and solids to be used in predicting properties of macroscopic systems is rather complete. These potentials cannot be used for predictions of properties of nanosystems The nature and role of intermolecular interactions, needed for formulation of intermolecular potentials, in nanostructures is challenging and not well understood Direct measurements of interparticle force vs. distance dataand quantum mechanical ab initio calculations are needed to generate intermolecular poltentials for nanosystems consisting of a few hundred to a few thousand particles ΔΧ

28. Simulation Methods for Nanosystems Monte Carlo (MC) simulations generally follow the evolution of a system in which change proceeds not in a predefined but rather a random manner Considering the fact that there are several thousands of atoms or molecules in a 10 nm cube, there are significant challenges in using MC techniques to predict the properties of nanosystems Molecular Dynamics simulations consist of the numerical solution of Newton’s equation of motion for a system of particles (atoms, molecules, aggregates, etc.) to obtain information about their time-dependent properties. MD are an ideal to relate the collective dynamics of a finite number of particles in nanosystems to single-particle Dynamics Optimization methods help us achieve several goals, (a) to develop a controlled simulation scheme to obtain different nanostructures, (b) to study the most stable conditions for nanosystems ΔΧ

29. Experimental Tools in Nanotechnology S(canning) T(unneling) M(icroscope) discovered by Binning and Rohrer at IBM Zurich (Binning and Rohrer received the Nobel prize in 1986). It allows imaging of solid surfaces with atomic scale precision. Its operation is based on tunneling current which is initiated when a tip mounted on a piezoelectric scanner approaches a conducting surface at a distance of 1 nm It was followed by the S(canning) P(robe) M(icroscope) and the A(tomi) F(orce) M(icroscope) The AFM enables one to study non-conducting surfaces, as it scans van der Waals forces with its “atomic” tips ΔΧ

30. Experimental Tools in Nanotechnology Both the STM and AFT are used for positional or robotic assembly,the ultimate goal of which is to build with molecules nanostructures in the same way we build macroscopic structures with macroscopic building blocks, e.g., bricks If we achieve sufficient control over the positioning of the right molecules in the right places, we may be able to alter materials to those with desired properties Assemblers or positional devices are made to position and hold Molecular Building Blocks in positional assemblies. The most basic form of an assembler is the Stewart Platform, a rigid and flexiblepolyhedron with all its faces being triangular. Two of the faces, designated as base and platform, and are connected by six struts of varying length. Changing the lengths of the struts changes the orientation and position of the platform with respect to the base To restore MBBs to their desired positions, assemblers utilize a spring force, F = s x where x is the distance between the original and the desired position of the MBB and s is the stiffness of the spring The positional uncertainty (mean error in position), e, is given by e2 = kB T / s The STM has s ~ 10 nm, hence, e ~ 0.02 nm ΔΧ

31. Self-Assembly This is a remarkable property of systems at the nanoscale. It is believed to be the basic process that led up to the evolution of the biological world from inanimate matter. There two kinds of self-assembly, (1) occurring on a fluid / solid interface, and (2)occurring in the bulk of a fluid phase An example of self assembly occurring in the bulk of a fluid phase is the micellization of asphaltene macromolecules, followedby self assembly of micelles into micelle- coacervates Asphaltene Micelle Micelle Coacervate Self-assembly on a fluid / solid interface involves immobilizationmolecules in the fluid as an assembly on a solid surface. It can be achieved via covalent or noncovalentinteractions between molecules in the fluid and the molecules of the solid surface ΔΧ

32. Divalent metal ion Self-Assembly Covalent bonds, e.g., between a sulfide and a noble metal, produce irreversible, thus stable, immobilization at all stages. Immobilization through noncovalent bonds is reversible, thus unstable, at the onset of the self assembly process but it achieves stability upon appreciable growth of the assembly. Some common noncovalent bonds involve (1) affinity coupling via antibodies (glycoproteins produced by the immune system in response to invasion of foreign substances called antigens), (2) affinity coupling by biotin-streptavidin (avidin, a glycoprotein, combines with Biotin, a vitamin B; STreptaVidin is a tetrameric protein which has four binding sites for biotin), and (3) Immobilized Metal Ion Complexation (non-covalent binding of biomolecule by formation of a complex with metal ions) ΔΧ

33. Mήτρα: Άμορφο πολυμερές Πληρωτικό: Σφαιρικά νανοσωματίδια, ακτίνας Rn  1 nm Κλάσμα όγκου: Συγκέντρωση σωματιδίων: Διεπιφάνεια ανά μονάδα όγκου: Απόσταση επιφανειών γειτον. σωματιδίων: Γυροσκοπική ακτίνα αλυσίδων: ΝΑΝΟΣΥΝΘΕΤΑ ΠΟΛΥΜΕΡΙΚΗΣ ΜΗΤΡΑΣ ΔΧ

34. Δονητικές κινήσεις 10-14s Μήκη δεσμών, ατομικές ακτίνες ~ 0.1 nm Μεταπτώσεις διαμόρφωσης 10-11s Μήκος στατιστικού τμήματος (Kuhn) b ~ 1 nm Μέγιστος χρόνος χα-λάρωσης10-3s Τήγμα Γυροσκοπική ακτίνα αλυσίδας ~ 10nm Διαχωρισμός σε φάσεις/ μικροφάσεις 1 s Μέγεθος περιοχών σε φασικά διαχω-ρισμένο υλικό~ 1 m Υαλώδης κατάσταση Φυσική γήρανση(Τ < Τg-20οC) 1 yr ΚΛΙΜΑΚΕΣ ΜΗΚΟΥΣ ΚΑΙ ΧΡΟΝΟΥ ΣΤΑ ΠΟΛΥΜΕΡΗ ΔΧ

35. Επεξεργασία Ιδιότητες Υλικού Καταστ. Εξισώσεις, Υλικές Σχέσεις Μοριακές Προσομοι-ώσεις, Εφαρμ. Στατιστική Μηχανική π.χ. Monte Carlo, Μοριακή δυναμική, Μοριακή μηχανική, Θεωρία μεταβατικών καταστάσεων Μοριακή γεωμετρία, Ηλεκτρο- νικές ιδιότητες Πεδία δυνάμεων μοριακών αλληλεπι-δράσεων Αδροποι- ημένες παράμετροιαλληλεπί-δρασης π.χ. Σταθερές ρυθμού, συντελε- στές τριβής Μεσοσκο- πικές Προσομοι-ώσεις π.χ. Κινητική Monte Carlo, Θεωρίες αυτo-συνεπούς πεδίου, Dynamic density functional theory, Dissipative particle dynamics Κβαντο- μηχανι-κοί Υπολο-γισμοί χημική σύσταση Μακροσκο-πικοί Υπολογισμοί, Σχεδιασμός π.χ. Εφαρμοσμένη θερμοδυναμική, Φαινόμενα μεταφοράς, Χημική κινητική, Μηχανική του συνεχούς, Ηλεκτρομαγνη- τική θεωρία Επιδόσεις υλικού υπό συγκε-κριμένες συνθήκες εφαρμογής Μοριακή οργάνωση και κίνηση Μικροσκοπικοί μηχανισμοί υπεύθυνοι για μακροσκοπική συμπεριφορά Μορφολογία Μικροδομή IΕΡΑΡΧΙΚΗ ΣΤΡΑΤΗΓΙΚΗ ΓΙΑ ΤΗΝ ΥΠΟΛΟΓΙΣΤΙΚΗ ΕΠΙΣΤΗΜΗ ΚΑΙ ΤΕΧΝΙΚΗ ΤΩΝ ΥΛΙΚΩΝ Οι υπολογισμοί κατευθύνουν και συμπληρώνουν πειραματικές προσπάθειες για την ανάπτυξη νέων υλικών, διεργασιών και προϊόντων. ΔΧ

36. Ατομιστικό(~10-10 m) Προσομοιώσεις MD Λεπτομέρειες δομής, τοπική δυναμική Αδροποιημένο(~10-9 m) Monte Carlo μεταβλητής συνδετικότητας Καλά εξισορροπημένες διαμορφώσεις σε συστήματα μακριών αλυσίδων Δυναμικά Hamakerγια αλληλεπιδράσεις νανοσωματιδίου-νανοσωματιδίου και νανοσωματιδίου–πολυμ. τμήματος Εμπνευσμένο από τη θεωρία πεδίου (FTiMC) (~10-7 m) Προσομοιώσεις Monte Carlo με απλοποιημένη Χαμιλτονιανή Μεγάλα νανοσωματίδια, πολλά νανοσωματίδια NAΝΟΣΥΝΘΕΤΑ: EΠΙΠΕΔΑ ΜΟΝΤΕΛΟΠΟΙΗΣΗΣ ΔΧ

37. new chain jch’ is formed DB IDR new chain ich’ is formed ΕΞΙΣΟΡΡΟΠΗΣΗ ΠΥΚΝΩΝ ΠΟΛΥΜΕΡΙΚΩΝ ΦΑΣΕΩΝ :MONTE CARLO REPT FLIP CONROT CB L.R. Dodd, T.D. Boone, DNT, Mol. Phys., 78, 961 (1993) N. Karayiannis, V.G. Mavrantzas , DNT, Phys. Rev. Lett.88, 105503 (2002) • Κινήσεις μεμονωμένων τμημάτων: • Περιστροφή εσωτερικού ατόμου (FLIP) • Ερπυσμός (REPT) • Τοπικές ανακατατάξεις διαμόρφωσης: • Μεροληψία απεικόνισης (CB) • Συντονισμένη περιστροφή (CONROT) [1] • Μεταβολές συνδετικότητας: • Διπλή γεφύρωση (DB) [2] • Ενδομοριακή διπλή αναγεφύρωση (IDR) [2] • Διακύμανση όγκου ΔΧ

38. ΕΞΙΣΟΡΡΟΠΗΣΗ ΠΟΛΥΣΤΥΡΕΝΙΟΥ (PS) Rg R αυξάνει μονότονα προς μία ασυμπτωτική τιμή. Εξαιρετική συμφωνία με σκέδαση νετρονίων σε μικρές γωνίες (SANS). T. Spyriouni, C. Tzoumanekas, DNT, F. Müller-Plathe, G. Milano, Macromolecules40, 3876 (2007) G. G. Vogiatzis and DNT, Macromolecules47, (2014), in press. DOI: 10.1021/ma402214r ΔΧ

39. αδροποιημένομοντέλο ΝΑΝΟΣΥΝΘΕΤΑ ΠΟΛΥΣΤΥΡΕΝΙΟΥ - C60 ατομιστικό από αντίστρ. απεικόνιση • Πεδίο δυνάμεων ενοποιημένων ατόμων για πολυστυρένιο: A.V. Lyulin, M.A.J. Michels, Macromolecules35, 1463 (2002). • Πεδίο δυνάμεων C60: S.L. Mayo, B.D. Olafson, W.A. Goddard, J. Phys. Chem. 94, 8897 (1990); L.A. Girifalco,J. Phys. Chem.96, 858 (1992). ΔΧ

40. Προσαρμογή σε τροποποιημένη έκφραση Kohlrausch – Williams – Watts (mKWW): • Χρόνος συσχέτισης για τμηματική κίνηση δίνεται από το ολοκλήρωμα: ΔΥΝΑΜΙΚΗ ΤΜΗΜΑΤΩΝ: ΤΗΓΜΑ PS συγκρινόμενο μεΝΑΝΟΣΥΝΘΕΤΟ PS-C60 ΔΧ G. G. Vogiatzis and DNT, Macromolecules47, (2014), in press. DOI: 10.1021/ma402214r

41. ΔΥΝΑΜΙΚΗ ΤΜΗΜΑΤΩΝ: ΤΗΓΜΑ PS συγκρινόμενο μεΝΑΝΟΣΥΝΘΕΤΟ PS-C60 Προσαρμογή εμπειρικής εξίσωσης Williams–Landel–Ferry (WLF)[1]: Συντελεστές WLF σε πολύ καλή συμφωνία με το πείραμα [2]. Πειραματικό σημείο υαλώδους μετάπτωσης ατακτ. πολυστυρενίου: 372.6 – 373.3 K [3]. Σύστημα πολυστυρενίου – C60επιδεικνύει λίγο υψηλότερο Tgαπό ό,τι το καθαρό πολυστυρένιο. Ανύψωση του Tg κατά 1 Κ έχει αναφερθεί από τους Green και συνεργάτες[4]. • J.D. Ferry, Viscoelastic Properties of Polymers, 3rd ed., Wiley, NewYork, 1980. • S.K. Kumar, R.H. Colby, S.H. Anastasiadis, G. Fytas, J. Chem. Phys. 105, 3777 (1996). • J. Hintermeyer, A. Herrmann, R. Kahlau, C. Goiceanu, E.A. Rössler, Macromolecules 41, 9335 (2008). • J.M. Kropka, V.G. Sakai, P.F. Green, Nano Lett. 8, 1061 (2008). ΔΧ

42. Προσαρμογή σε τροποποιημένη έκφραση Kohlrausch – Williams – Watts (mKWW): • Χαρακτηριστικός χρόνος χαλάρωσης δίνεται από το ολοκλήρωμα: G. G. Vogiatzis and DNT, Macromolecules47, (2014), in press. DOI: 10.1021/ma402214r ΔΥΝΑΜΙΚΗ ΤΜΗΜΑΤΩΝ: ΤΗΓΜΑ PS συγκρινόμενο μεΝΑΝΟΣΥΝΘΕΤΟ PS-C60 • Καλή συμφωνία με μετρήσεις Πυρηνικού Μαγνητικού Συντονισμού (NMR) και παλαιότερες προσομοιώσεις MD[1,2] • Y. He, T.R. Lutz, M.D. Ediger, C. Ayyagari, D. Bedrov, G.D. Smith, Macromolecules 37, 5032 (2004). • H.W. Spiess, H. Sillescu, J. Magn. Reson.42, 381 (1981). ΔΧ

43. ΔΟΜΗ ΝΑΝΟΣΥΝΘΕΤΩΝ ΠΥΡΙΤΙΑΣ-ΠΟΛΥΣΤΥΡΕΝΙΟΥ • Νανοσωματίδια: • Πυριτία με αλυσίδες PS επιφανειακά εμφυτευμένες κατά το ένα άκρο • Μονοδιάσπαρτο ατακτικό PS: • Ελεύθερες αλυσίδες: 20 - 100 kg mol-1 • Εμφυτευμένες αλυσίδες: 20 - 100 kg mol-1 • Προσομοιώσεις NVTυπό T = 500 K • Ακτίνα νανοσωματιδίων: 8 ή 13 nm • Κυβικά κουτιά προσομοίωσης: • Μήκος ακμής 100-200 nm • Επιφανειακή πυκνότητα εμφύτευσης: 0.2 – 0.7 αλυσίδες nm-2 100 nm G.G. Vogiatzis and DNT Macromolecules 46, 4670 (2013) ΔΧ

44. MONTE CARLO ΕΜΠΝΕΥΣΜΕΝΟ ΑΠΟ ΘΕΩΡΙΑ ΠΕΔΙΟΥ 60 nm • Αλυσίδες: τυχαίοι περίπατοι απόστατιστικά τμήματα Kuhn. • Κάθε τμήμα Kuhn αντιστοιχεί σε 7 μονομερή PS. • Δεσμικές αλληλεπιδράσεις λαμβάνονται υπόψη μέσω του σταθερού μήκους του τμήματος Kuhn (b=18.3 Å). • Μή δεσμικές αλληλεπιδράσεις: • Πολυμερούς-πολυμερούς(όπως στη θεωρία πεδίου) • Πολυμερούς-νανοσωματιδίου(ολοκλήρωση Hamaker των ατομιστικών δυναμικών) • Νανοσωματιδίου-νανοσωματιδίου (Hamaker) • Τοπική πυκνότητα πολυμερούς παρακολουθείται χρησιμοποιώντας τρισδιάστατο πλέγμα. • Απεικόνιση αλυσίδων και νανοσωμα- τιδίων μεταβάλλεται με κινήσεις MC. • Χρησιμοποιούνται και μετακινήσεις του πλέγματος. ΔΧ

45. G.G. Vogiatzis and DNT Macromolecules 46, 4670 (2013) ΔΧ

46. FTiMC: ΤΟΠΙΚΗ ΔΟΜΗ σ=0.5 nm-2Mf=100kg/mol • - Silica nanoparticles, Rn=8 nm • Μήτρα ατακτικού πολυστυρενίου • Αραιή διασπορά Mg= 20kg/mol Mf=100kg/mol • Ακτινική κατανομή πυκνότητας, • Μεταβολές στη θέση και το πάχος της περιοχής αλληλεπικάλυψης εμφυτευμένων και ελεύθερων αλυσίδων συναρτήσει: • Μοριακής μάζας εμφυτευμένων αλυσίδων • Επιφανειακής πυκνότητας εμφύτευσης G.G. Vogiatzis and DNT Macromolecules 46, 4670 (2013) ΔΧ

47. FTiMC: Πάχος «ψήκτρας» εμφυτευμένων αλυσίδων G.G. Vogiatzis and DNT, Macromolecules 46, 4670 (2013) • Καλή συμφωνία με πειράματα σκέδασης νετρονίων σε μικρές γωνίες(SANS).[1] • Καλή συμφωνία με θεωρία Daoud-Cotton: [2] SiO2σε PS, Rn=8 nm Mf=100 kg/mol • Mathias Meyer, Ph. D. thesis, Westfälische Wilhelms-Universität Münster, 2012. • M. Daoud, J. Cotton, J. Phys. France 43, 531 (1982). ΔΧ

48. FTiMC: Πρόρρηση SANS από εμφυτευμένη στεφάνη SiO2 in PS, Rn=13 nm Mg = 25 kg/mol,σ = 0.5 nm-2 Πειράματα: C. Chevigny, J. Jestin, D. Gigmes, R. Schweins, E. Di-Cola, F. Dalmas, D. Bertin, F. Boué, Macromolecules, 43, 4833-4837 (2010). SiO2 in PS, Rn=8 nm Mg = 20 kg/mol, Mf= 100 kg/mol ΔΧ

49. ΔΙΑΧΥΤΟΤΗΤΑ ΑΡΩΜΑΤΙΚΩΝ ΜΟΡΙΩΝ ΣΤΟ ΖΕΟΛΙΘΟ ΣΙΛΙΚΑΛΙΤΗ-1 Τερεφθαλικό οξύ Οξείδωση PET Σιλικαλίτης-1: Μοριακό κόσκινογια διαχωρισμό π-ξυλολίου από άλλα μόρια στη νάφθα, όπως βενζόλιο, τολουόλιο, ο- και m-ξυλόλιο. Ο Σιλικαλίτης-1 είναι η καθαρά πυριτική μορφή του ZSM-5. Ζεόλιθοι MFI (Mobil Five): ευρεία χρήση στην πετροχημική βιομηχανία ZSM-5: Καταλύτης για μετατροπές αλκυλαρωματικών μορίων ZSM-5: Καταλύτης για μετατροπή μεθανόλης σε βενζίνη. ΔΧ

50. y b z a x c ΣΙΛΙΚΑΛΙΤΗΣ-1 Μοναδιαία κυψελίδα Si96O192 Pnma a = 20.07 Å b = 19.91 Å c = 13.42 Å (δείχνονται 333 κυψελίδες) Αποτελείται από τετράεδρα SiO4που μοιράζονται κορυφές. Ευθύγραμμα (S) και ημιτονοειδή (Z) κανάλια διαμέτρου≈ 5.5 Å Περιοχές διασταύρωσης καναλιών (I) διαμέτρου≈ 9Å ΔΧ