Ppt on particle size distribution curve

Maria Grazia Pia, INFN Genova Distributed Processing, Monte Carlo and CT interface for Medical Treatment Plans F. Foppiano 3, S. Guatelli 2, J. Moscicki.

sets: Cross section data sets: transparent and interchangeable Final state calculation: Final state calculation: models by particle, energy, material Electromagnetic Physics Hadronic physics Maria Grazia Pia, INFN Genova Interface to external tools no dependence/Oncological Regional Center 2 LIP - Lisbon Central-Axis depth dose curve for a 10x10 cm2 field size, compared with experimental data (ionisation chamber ) Validation of phase-space distributions from a Siemens KD2 linear accelerator at 6 MV photon /


13 Lecture in physics Quantum physics Elementary particles Astrophysics Cosmology.

the star to gradually grow in size, passing through the subgiant stage until/ relativitymassevent horizonblack bodyquantum field theory in curved spacetimeHawking radiationthe same spectrumblack holes of /distribution of hot gas in galaxies and clusters of galaxies, and more recently the pattern of anisotropies in the cosmic microwave background. According to consensus among cosmologists, dark matter is composed primarily of a not yet characterized type of subatomic particle. The search for this particle/


1 SOIL CLASSIFICATION. 2 According to their particle sizes, soils are divided into two: Coarse grained soils: Gravel » Sand Fine grained soils: Silt &

in the classification of soils. Effective size, D 10 : The size such that 10% of the particles are smaller than that size. D 60 : The size such that 60% of the particles are smaller than that size. D 30 : The size such that 30% of the particles are smaller than that size. 18 19 Parameters Obtained From Grain Size Distribution Curve: 1- Uniformity Coefficient Cu (measure of the particle size range) C u = D 60/


G. Cowan Weizmann Statistics Workshop, 2015 / GDC Lecture 21 Statistical Methods for Particle Physics Lecture 2: hypothesis tests I; multivariate methods.

is a constant chosen to give a test of the desired size. Equivalently, optimal scalar test statistic is N.B. any monotonic/2 nd ed., Wiley, 2002. Ilya Narsky and Frank C. Porter, Statistical Analysis Techniques in Particle Physics, Wiley, 2014. 朱永生 (编著),实验数据多元统计分析, 科学出版社 , 北京, 2009 。 G. Cowan Weizmann Statistics Workshop/curve is better; usually analysis focused on a small part of the curve. G. Cowan Weizmann Statistics Workshop, 2015 / GDC Lecture 2page 88 2D Example: discussion Even though the distribution/


U NIVERSITA DEGLI S TUDI DI P ADOVA Corso CFMA. LS-SIMat1 Chimica Fisica dei Materiali Avanzati Part 6.a – Size effects and applications of metal and semiconductor.

LS-SIMat11 Dispersion Curves Propagation curve in 1 (dielectric medium) does not cross the surface plasmon dispersion curve U NIVERSITA DEGLI /adsorbates e.g. biomolecules. Surface plasmon changes with particle size. Surface plasmon changes with particle shape. Single Electron Effects: Coulomb Blockade. U /size distributions must be very narrow. The growth kinetics must be carefully controlled. Quantum Size Effect produces Artificial Atoms U NIVERSITA DEGLI S TUDI DI P ADOVA Corso CFMA. LS-SIMat38 Size/


Soil water retention curve

Chan, T. P. , and R. S. Govindaraju. 2004 Chan, T.P., and R.S. Govindaraju. 2004. Estimating soil water retention curve from particle-size distribution data based on polydisperse sphere systems. Vadose Zone J. 3:1443-1454. The measured and estimated soil water retention curves of Troup loamy sand (code no. 1012) (a) with fitted α and (b) with theoretical α. The fitted α value is higher than/


Soil Types Soil – all unconsolidated material in the earth’s crust Soil includes – Mineral particles – sand and clay Organic Materials – found in topsoil.

clays Sedimentation test Rate at which particles settle Strokes law states –that particles in a suspension settle out at a rate that varies with their size Plasticity – to measure grain types Grain Size Distribution Curve Used to help describe and classify a soil Shape – Uniform soil –curve a on page 19 Well graded – curve b on page 19 Effective size 10% size is considered effective size – page 19 – sample b.09mm/


Lecture (3). Mechanical Analysis of Soil is the determination of the size range of soil particles, expressed as a percentage of total dry weight. The.

/ D10 Cc Gradation coeff. = (D30 )2/ (D60 * D10 ) 11/16 PARTICLE-SIZE ANALYSIS ASTM D 422 12/16 13/16 PARTICLE-SIZE ANALYSIS ASTM D 422 14/16 PARTICLE-SIZE ANALYSIS ASTM D 422 15/16 16/16 Pharos University Faculty of Engineering CV 256: Soil/2244523.5 * Determine the percent finer than each sieve and plot a Grain -Size Distribution Curve for all the samples. * Calculate D 10, D 30 & D 60 form the Grain - Size Distribution Curve for all the samples * Calculate the uniformity coefficient, C u * Calculate the /


Fatigue Life is a Statistical Quantity Introduction to the Weibull distribution.

size of particles generated by grinding, milling and crushing operations, the 2-Parameter Weibull distribution is used, and in these applications it is sometimes known as the Rosin-Rammler distribution. (In this context it predicts fewer fine particles than the Log-normal distribution and it is generally most accurate for narrow particle size distributions/a good idea to make the primitive plot we started out and decide what other curves might “reasonably” be drawn to the data. This will give you a rough /


1 Observationally Verifiable Predictions of Modified Gravity Talk given at Topical Conference on Elementary Particles, Astrophysics, and Cosmology, Miami.

r=0, preventing particles from reaching the singularity at r=0. Geodesically complete spacetime. /curves become the Kepler-Newtonian curves at large distances from the galaxies (satellites). For every feature in the surface brightness distribution, MOG produces a corresponding feature in the predicted rotation curve (matching the observed rotation curve/oscillations may become observable as the galaxy surveys increase in size and the window functions narrow in size. 31 5. MOG Verifiable Predictions The matter power /


The link between particle properties (size, packaging, composition, shape, internal structure) and their IOPs. In order for us to be able to use optical.

al 2001  Flatter beam attenuation spectra (small γ ) implies flatter particle size distribution (small  ) (2) Assuming spherical non- absorbing particles  c p (λ) is described well as a power law function of wavelength (λ) c p (λ) ~ λ -γ γ ≈  - 3 Relationship between optical properties size b bp /Volume b p /Volume b sp /Mass All curves are ‘resonant’ curves Highest sensitivity for micron sized particles Size of max response varies 1/D D3D3 Instruments are consistent/


G. Cowan Statistical Methods in Particle Physics1 Statistical Methods in Particle Physics Day 1: Introduction 清华大学高能物理研究中心 2010 年 4 月 12—16 日 Glen Cowan.

number u uniformly distributed between 0 and f max, i.e. (3) If u < f (x), then accept x. If not, reject x and repeat. G. Cowan Statistical Methods in Particle Physics44 Example with acceptance-rejection method If dot below curve, use x /1/2. G. Cowan Statistical Methods in Particle Physics56 Example of variance by graphical method ML example with exponential: Not quite parabolic ln L since finite sample size (n = 50). G. Cowan Statistical Methods in Particle Physics57 The method of least squares Suppose we /


G. Cowan iSTEP 2015, Jinan / Statistics for Particle Physics / Lecture 21 Statistical Methods for Particle Physics Lecture 2: multivariate methods iSTEP.

. G. Cowan iSTEP 2015, Jinan / Statistics for Particle Physics / Lecture 211 Classification viewed as a statistical test Probability to reject H 0 if true (type I error): α = size of test, significance level, false discovery rate Probability to/) versus signal efficiency ε s. Higher curve is better; usually analysis focused on a small part of the curve. G. Cowan iSTEP 2015, Jinan / Statistics for Particle Physics / Lecture 2page 68 2D Example: discussion Even though the distribution of x 2 is same for signal/


Milling II Dr. Myasr Alkotaji. Methods for Size Distribution Measurement: 1- Microscopy: It is the most direct method for size distribution measurement.

are falling at a constant rate. The pipette method (Andreasen) Sedimentation methods may be used over a size range from 1-200 microns to obtain a size- weight distribution curve and to permit calculation of the particle size. The pipette method (Andreasen) is the simplest means of incremental particle size analysis. A 1% suspension of the powder in a suitable liquid medium is placed in the pipette. At/


G. Cowan Aachen 2014 / Statistics for Particle Physics, Lecture 11 Statistical Methods for Particle Physics Lecture 1: probability, random variables, MC.

the covariances of the original variables. Limitations: exact only iflinear. Approximation breaks down if function nonlinear over a region comparable in size to the  i. N.B. We have said nothing about the exact pdf of the x i, e.g., /curve, use x value in histogram. G. Cowan Aachen 2014 / Statistics for Particle Physics, Lecture 157 Improving efficiency of the acceptance-rejection method The fraction of accepted points is equal to the fraction of the box’s area under the curve. For very peaked distributions/


G. Cowan IHEP seminar / 19 August 2015 1 Some Developments in Statistical Methods for Particle Physics Particle Physics Seminar IHEP, Beijing 19 August,

2015 1 Some Developments in Statistical Methods for Particle Physics Particle Physics Seminar IHEP, Beijing 19 August, 2015/ IHEP seminar / 19 August 2015 5 Confidence interval from inversion of a test Carry out a test of size α for all values of μ. The values that are not rejected constitute a confidence interval for μ at/ ε s. Higher curve is better; usually analysis focused on a small part of the curve. G. Cowan IHEP seminar / 19 August 2015 57 2D Example: discussion Even though the distribution of x 2 is/


AGE 411: Hydrology Introduction Hydrology is an earth science. It encompasses the occurrence, distribution, movement and properties of the waters of the.

recorder which indicates stage versus time and is then transformed to a discharge hydrograph by application of a rating curve. Hydrograph Analysis Contd. Components of Hydrograph Components of Hydrograph A hydrograph has 4 components: 1). Direct surface / Values of specific yield depend upon the soil particle size, shape and distribution of pores and degree of compaction of the soil. Values of specific yield depend upon the soil particle size, shape and distribution of pores and degree of compaction of the/


Contents of today’s lesson 1.Frequentist probabilities of Poisson-distributed data -with and without nuisances 2.Weighted average in presence of correlations.

N-P likelihood-ratio test outperforms others in the figure [James 2006] – reason is N-P lemma As data size increases, power curve becomes closer to step function The power of a test usually also depends on the parameter of interest: different methods may/The distribution of residuals of 306 measurements in [20] x1000! Eye fitting: Sensitivity to bumps I will discuss the quantification of a signal’s significance later on. For now, let us only deal with our perception of it. In our daily job as particle /


 Powdered solids are heterogeneous because they are composed of individual particles of widely differing sizes, shape and air spaces.  So it is virtually.

his coworker interpreted the plot of specific surface area vs. compressional force.  Armstrong and coworkers described similar curves, at higher compressional forces (dotted lines) some materials shows increase in specific surface area due to lamination of/flow properties of the bulk material with individual granule strength and porosity.  Particle shape and size distribution are important factors in packing and flow.  Particles of more regular shape (nearly spherical) have low angles of response and high/


Collisional Cascades Size distributions Scaling from observables Size distribution in asteroid belt and Kuiper belt Dust destruction, PR drag, dust dynamics,

tend to get information about a ~ λ Evolution of size distribution dN(a)/dt = -rate of destruction + rate of production of bodies with radius a Larger particles destroyed by collisions create smaller particles Smallest particles can be removed or destroyed by drag, blowout, /not precisely known Complications As Q * D depends on sizescale. Refinements include taking this into account -> A curve or two power laws instead of one Actually Q parameter is perhaps only a poor approximation of real parameters/


The Theory of Charged Particle Energy Loss and Multiple Scattering in Materials and its Application to Muons in Liquid Molecular Hydrogen W W M Allison,

Photoabsorption cross section of medium Density & refractive index Incident particle momentum, P Incident particle mass (muon) Overview Input theory Maxwell’s equations Causality/which is well known and includes the finite proton size as well (see Perkins, 3rd edn.). Nuclear/1 vs. log 10 P where P is muon momentum Curve = Bethe Bloch with Mean Ionisation Potential = 18.59eV/ respectively. 3.Statistical effects remain slippery to handle. Distributions of variables, not their simple means and standard deviations/


Soil Texture, Particle Size Distribution and Soil Classification

impedance are proportional to the volume of particles. Measurement range of 0.6 to 1200mm. Particle-Size Diagram Particle size distribution (PSD) is often expressed as particle diameter as a function of soil mass fraction of smaller particles. The curve is equivalent to cumulative statistical distribution of particle diameters in the sample (note log scale for particle sizes). Comparison of methods for PS analyses Six methods for particle size analysis were compared in recent study/


Malvern Instruments Training Course.

that for large particles all distribution coincide and are therfore not dependent on optical properties. The red curve has the wron refractive index and shows some departure to the blue correct curve. The green curve has been generated by/2% 0.5 - 2% Users Sampling Sample Handling Units 1 - 2% Optical Bench 0.5 - 2% Characterising distributions A particle size distribution contains a large amount of data. To assist comparisons and examination we extract simpler quantities from the data known as averages /


Sedimentary Analysis. Types of Sedimentary Material Terrigenous Clastics (TC) –Detrital Particles –Derived from pre-existing rocks –Derived external to.

from right to left, f ines to right, coarse to left Graphically represent grain size distribution –mean grain size –standard deviation from a normal distribution (sorting) –symmetry (skewness) –flatness of curve (kurtosis) Describing Siliciclastics Grain size analysis- graphic analysis Different depositional environments exhibit different grain size distributions Glacial sediments poorly sorted River sediments moderately sorted Beach sediments well sorted Statistical/Graphic Presentation of Texture/


Queensland University of Technology CRICOS No. 000213J INB382/INN382 Real-Time Rendering Techniques Lecture 11: Non- Photorealistic Rendering, Particle.

by quantising textures applied to geometry from truecolor to lower bit size samples Or, can quantise the values generated by normal lighting techniques/ sparks, fireworks etc. Colour and visibility attenuates over time Curves – for plants, render entire temporal existence of particle as stems Textured Quads – for smoke, flames, blood plant/CRICOS No. 000213J a university for the world real R Bidirectional Surface Scattering Distribution Function The BSSRDF, S, relates the outgoing radiance L o, at the/


Lecture (4).

size range of soil particles, expressed as a percentage of total dry weight. The particle size distribution of soil can be fined by two methods. • The sieve analysis technique is applicable for soil grains larger than No. 200 (0.075 mm) sieve size/.5 * Determine the percent finer than each sieve and plot a Grain -Size Distribution Curve for all the samples. * Calculate D10, D30 & D60 form the Grain -Size Distribution Curve for all the samples * Calculate the uniformity coefficient, Cu * Calculate the /


量子力學發展史 近代科學發展之三. 物理模型 粒子模型 Allowed us to ignore unnecessary details of an object when studying its behavior 系統與剛體 Extension of particle model 波動模型 兩種新模型.

, the scattered wave frequency at a given angle should be a distribution of Doppler- shifted values Compton Effect, Observations Compton’s experiments showed/particles In this model, entities have both particle and wave characteristics We much choose one appropriate behavior in order to understand a particular phenomenon Ideal Particle vs. Ideal Wave An ideal particle has zero size/ well is the upward-facing region of the curve in a potential energy diagram The particle in a box is sometimes said to be /


Physics-Informatics Looking for Higgs Particle Counting Errors (Continued) January 28 2013 Geoffrey Fox

event represents p p  Reasonably stable particles “charged particles” (with energy measured by magnetic field), “neutral particles” (with energy measured in a calorimeter / events in them The red curve is naïve expected number of events in each bin – Normal distribution Good but not perfect as /curve and 250 is expected number of events with an error of √250 ≈ 16 The one sigma line runs from 250- √250 to 250 + √250 The plots get rough if reduce number of events from 40000 to 400 or 4000 Use larger bin size/


CHEMICAL REACTION ENGINEERING LABORATORY CARPT Calibration Issues Poster 1 Bad Reconstruction Calibration Curve Counts Distance (cms) Photo Peak Compton.

Curve CHEMICAL REACTION ENGINEERING LABORATORY Gas Liquid Studies in Stirred Tank Reactor New techniques in CT implementation result in better reconstruction!!! How ??? Cross sectional gas holdup distributions/ REACTION ENGINEERING LABORATORY  bubble dynamics, i.e. bubble size distribution, bubble velocity distribution, specific interfacial area and gas holdup are among the key/The Present Work  To demonstrate the ability of single particle CARPT technique to visualize 3D flow patterns inside a simulated/


CHAPTER 2.3 PROBABILITY DISTRIBUTIONS. 2.3 GAUSSIAN OR NORMAL ERROR DISTRIBUTION  The Gaussian distribution is an approximation to the binomial distribution.

50 % probability limit we can see that the probable error is given by  pe = 0.6745 . Comparison of Gaussian and Poisson Distributions  A comparison of the Poisson and Gaussian curves reveals the nature of the Poisson distribution.  It is the appropriate distribution for describing experiments in which the possible values of the data are strictly bounded on one side but not on the other/


Linear momentum and Collisions Chapter 9. Center of mass and linear momentum I.The center of mass - System of particles / - Solid body II.Newton’s Second.

: 3D: The vector form Position of the particle: M = mass of the object object System of particles: Position COM: Solid bodies: Continuous distribution of matter. Particles = dm (differential mass elements). 3D: M/m 1 = 0.500 kg is released from rest at the top of a curve-shaped frictionless wedge of mass m 2 = 3.00 kg, which sits on/ (a) Thrust (b) Model rocket engines are sized by thrust, thrust duration, and total impulse, among other characteristics. A size C5 model rocket engine has an average thrust of 5/


What are viruses? Viruses are very small (submicroscopic) infectious particles (virions) composed of a protein coat and a nucleic acid core. They carry.

the genes are translated into protein from an RNA strand complementary to that of the genome (as packaged in the virus particle). There are some plant viruses in this group and it also includes the viruses that cause measles, influenza and rabies./papaya. DISTRIBUTION: Where papaya is grown. 10 TRANSMISSION: White fly, Bemissia tabacci. SYMPTOMS: Almost all the leaves of the plant are reduced in size and show malformation and sever curling, crinkling and distortion. The margins of the leaves are curved or /


Micromeritics. Definition: It is the science and technology of small particles. The unit of particle size used in the micrometer (µm), micron (µ) and.

. Thus, we need an estimate of the size range present and the number or weight fraction of each particle size. This is the particle-size distribution and from it we can calculate an average particle size for the sample. Particle Size Distribution When the number or weight of particles lying within a certain size range is plotted against the size range or mean particle size, a so-called frequency distribution curve is obtained. This is important because it/


Kinetics and Statistical Methods for Complex Particle Systems

pairs j=i,l with σ in a compact set) dσ ΩdN 2 ΩdN x Sd-1 Introducing a one-particle distribution function (by setting v1 = v) and the hierarchy reduction for B= -∞ or B=0 B B B The / where self-similar asymptotics is possible: M , M whose spectral function is Where μ(p) is a curve with a unique minima at p0>1 and approaches + ∞ as p 0 and μ’(1) < 0/ next two pages: Mean free path l0 = 1. Number of Fourier modes N = 243, Spatial mesh size Δx = 0.01 l0 . Time step Δt = r mft Sudden heating problem (BGK eq. with/


For quality compressed air

roof must be protected from the weather and emissions from ducting and chimneys Distribution Distribution Ring main installation Dead leg with a drip leg drain on each corner to/ Relieving G1/4 Spring range 0-10 bar Primary pressure 10 bar The curves show the characteristics and hysteresis of pressure from a set value for increasing /cylinders etc. Oil drips are broken up in the main air stream and all particle sizes carried in the air Drip rate is adjustable Oil fog lubricator Oil drips visible through/


Evolution of statistical models of non-conservative particle interactions Irene M. Gamba Department of Mathematics and ICES The University of Texas at.

assumed rules lead (formally, under additional assumptions) to molecular chaos, that is Introducing a one-particle distribution function (by setting v 1 = v) and the hierarchy reduction The corresponding “weak formulation/being under discussion where self-similar asymptotics is possible, M Where μ(p) is a curve with a unique minima at p 0 >1 and approaches + ∞ as p / simplest setting: N= Number of Fourier modes in each j-direction in 3D Spatial mesh size Δx = O.O1 mfp Time step Δt = r mft, mft= reference time/


An argument that the dark matter is axions Pierre Sikivie Center for Particle Astrophysics Fermilab, March 17, 2014 Collaborators: Ozgur Erken, Heywood.

- in the galactic plane - with radii - with overall size consistent with tidal torque theory 5.The evidence for caustic rings / 5 states 316 251 system states Start with Number of particles Total energy Thermal averages Integrate Calculate Do the approach the on/of dark matter (A. Natarajan and P.S. ’07) Rotation curve of Andromeda Galaxy from L. Chemin, C. Carignan & T./ et al. 1979, 1987from caustic rings The specific angular momentum distribution on the turnaround sphere Is it plausible in the context of/


Some numerical issues in flow simulations using particles G.-H. Cottet, Grenoble Field calculations subgrid-scale modeling vs artificial viscosity models.

gives a 3d version of previous AV model In all particle simulations, accuracy requires frequent and accurate regridding « classical » interpolation formulas Error curves random initquiet start init with remeshing Typical example showing importance of/ designed for FD Global mapping approach: Particle grid Vorticity contours Measure of accuracy/cost: enstrophy profiles and number of particles compared to uniform size particles Dotted line: uniform particle distribution AMR approach: Conclusion : 1.About/


II. Physical Properties

-sieving procedure (section 4.6.4) should be followed for all soils (Head, 1992). (Head, 1992) Sieve analysis Hydrometer analysis 2.2 Grain Size Distribution (Cont.) Finer Effective size (D10): This parameter is the diameter in the particle-size distribution curve corresponding to 10% finer. The effective size of a granular soil is a good measure to estimate the hydraulic conductivity an ddrainage through soils. Log scale Effective/


Division of Nuclear Physics,

43% 29% 41% Lung Deposition Measurements RESPI instrument RESPI Particle Lung Deposition Validation of the Particle Lung Deposition Determined by the dry size distribution and the hygroscopic properties. H-TDMA Hygroscopic Tandem Differential Mobility Analyzer Water uptake of individualparticles Humidified particle size distribution Particle Lung Deposition Modelled Measured DMPS Differential Mobility Particle Size Dry particle size distribution DMPS – huvud saken H-TDMA – elle ranna kemiska bestämning/


Unit 2, Part 3: Characterizing Nanostructure Size Dr. Brian Grady-Lecturer

good idea for an unknown material). Particle size distribution Most spherical nanoparticle size distributions are fit well by the log normal distribution (slightly asymmetric): Y=A*exp(-0.5(log(R)-log(R o )) 2 /b 2 ) –Two parameters b (the width of the distribution) and R o (the average radius). A is set by the fact that the area under the curve is 1. Two types of/


© 2014 Pearson Education, Inc. Chapter 5 Gases. © 2014 Pearson Education, Inc. Gas  Gases are composed of particles that are moving around very fast.

balls  There is a lot of empty space between the gas particles compared to the size of the particles. © 2014 Pearson Education, Inc. Kinetic Molecular Theory (basic postulates)  The size of a particle is negligibly small. Under normal pressures, the space between atoms or/attractions we get the following equation. Used for real gases © 2014 Pearson Education, Inc. Real Gases  It reveals a curve that shows the PV/RT ratio for a real gas is generally lower than ideal for “low” pressures—meaning that the /


Quantum Dots. What is a quantum dot? In two words, a semiconductor nanocrystal. Easily tunable by changing the size and composition of the nanocrystal.

two ways: radiative and non-radiative Band gap of spherical particles The average particle size in suspension can be obtained from the absorption onset using / coherent. Balance surface energy against elastic energy. Control of self-assembly? Average size & size distribution. –Affects emission wavelength and sharpness. Density. –Affects gain of QD laser./size and density fixed by AFM). Composition is 100% In for the top curve, then 80%, 60%, 40% and 20%. Simulations of linear composition gradient QDs (curves/


Chapter 2: Probability Concepts and Distributions 2.1 Introduction 2.2 Classical probability 2.3 Probability distribution functions 2.4 Important probability.

radioactive particles passing through a counter in 1 millisecond is 4. What is the probability that 6 particles enter the counter in any given millisecond? Using the Poisson distribution function/Reddy45 Chap 2-Data Analysis-Reddy46 Table A3. The standard normal distribution (cumulative z curve areas) Example 2.4.9. Graphical interpretation of probability using the/Reddy67 Chap 2-Data Analysis-Reddy68 portion of size 2 2.5.2 Application to discrete probability distributions Example 2.5.3. Using the Bayesian /


PARTICLE SIZE, PARTICLE SIZE DISTRIBUTION & COMPACTION AND COMPRESSION [PREFORMULATION STUDY] (1-32)

Range of analysis:- TEM :– 0.001 – 0.1 micron S E M :– 0.01 – 1000 micron Light microscope :- 1 – 1000 micron Light microscope :- Two dimensional image No of particle count for draw size distribution curve ( particle size v/s freq ) Alternative technique Two Technique (1) Scanning Electron Microscopy (SEM) (2) Transmission Electron Microscopy (TEM) SEM give three dimensional image. It has more resolution power then Light/


The Increased Biological Effectiveness of Heavy Charged Particle Radiation: From Cell Culture Experiments to Biophysical Modelling Michael Scholz GSI Darmstadt.

W. Weyrather et al. RBE depends on Ion Species  RBE maximum is shifted to higher LET for heavier particles  The shift corresponds to a shift to higher energies ~1 MeV/u ~15 MeV/u Why Carbon Ions?/ Parameters Radial Dose Distribution: Monte-Carlo (M. Krämer), Analytical Models (Katz, Kiefer), Experimental Data X-ray Survival Curves: Experimental data according to LQ; additional assumption: Transition from shoulder to exponential shape at high doses Target Size (Nuclear Size): Experimental Data Algorithms/


Fluorescence Fluctuation Spectroscopy – A tool for the detection of nanometer sized particles in living cells Michael Edetsberger Max F. Perutz Laboratories,

of nanometer sized particles in living cells Michael Edetsberger Max F. Perutz Laboratories, Department for Biomolecular Structural Chemistry, University of Vienna Introduction  Nanoparticles are extensively used in biotechnology and medicine  Nanoparticles originated from industrial or combustion processes  Nanoparticles play an important role in environmental biology, job safety and medicine Standard techniques  Microscopy (Fluorescence, Laser Scanning)  Good spatial distribution  Diffraction/


Grain size, concentration, flux and composition of Asian dust in snow and ice cores on Tibetan Plateau Guangjian Wu, Tandong Yao, Baiqing Xu, Lide Tian,

deviation (SD) and V Total the total volume. Fig. 1-1 Volume size distributions (in 50 channels on logarithmic scale) of microparticles in low- and high concentration samples (black curves) from the Muztagata and Dunde ice cores. Only the high concentration samples obey the log-normal distribution (fitted by red curves). Only particles of 1–30μm diameter were measured. 1. Only high-concentration samples obey/


Summary: Last week Viscous material and elastic material; viscoelastic Flow curve Newtonian and non-Newtonian fluid Pseudoplastic WLF equation Time-temperature.

equation Time-temperature superposition Mechanical models of viscoelastic behaviour Typical stress-strain curves for polymers in solid state Polymer dissolution Fractionation Gas permeation Polymer /to determine: –the molar mass, the particle size, the particle density and interaction parameters like virial coefficients and association constants –determination of the molar mass distribution, the particle size distribution and the particle density distribution is also possible The density gradient method /


G. Cowan Invisibles 2014 / Statistics for Particle Physics1 Statistical Methods for Particle Physics Invisibles School 8-13 July 2014 Château de Button.

Now invert the test to define a confidence interval as: set of  values that would not be rejected in a test of size  (confidence level is 1  ). The interval will cover the true value of  with probability ≥ 1 . Equivalently,/determine the distribution of upper limits μ up one would obtain under the hypothesis of μ = 0. The dashed curve is the median μ up, and the green (yellow) bands give the ± 1σ (2σ) regions of this distribution. G. Cowan Invisibles 2014 / Statistics for Particle Physics92 Choice /


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