CLASSIZER ONE v0.7 key enabling solutions and TT services based on - - PowerPoint PPT Presentation
CLASSIZER ONE v0.7 key enabling solutions and TT services based on SPES patented technology for the characterization and design of micro and nanoparticles in biological, industrial and environmental complex fluids Novel Products Based On
key enabling solutions and TT services based on SPES patented technology for the characterization and design of micro and nanoparticles in biological, industrial and environmental complex fluids
Novel Products Based On Micro & NanoParticles
dynamic light scattering (DLS) single particle scattering (sSLS) coulter counter (CC)
θ e.g. . DLS
LASER ER
data manipulation
retrieve one parameter hydrodyn
amic radius us
e.g. . SLS
data manipulation
retrieve one parameter Mie radius us static light scattering (mSLS, MALS) nanoparticle tracking analysis (NTA)
Traditional Technologies For Particle Analysis Are Based On Light Scatt tter ering ing
sensor sensors LASER ER
They consider ALL particles as perfect, uniform spheres of the same material Polymer lymeric
Traditional Technologies Limits
Polymer lymeric But particles are NOT T homogeneous, perfect, uniform spheres Metalli tallic/Oxi Oxides des Enginee ineered red Ptc tcs Bio co componen ponents
Traditional Technologies Limits
r each ch partic ticle le tw two indep ependent endent parameter meters (capability foreclosed to traditional technologies)
Single gle Partic icle le Extinc nctio ion & & Scatt tter ering ing (SPES) ES) patented technology
Single gle Partic icle le Extinc nctio ion & & Scatt tter ering ing (SPES) ES) – Published Applications
SPES Key Key-Ena Enabl bling ing Tech ch
Single gle Partic icle le Extinc nctio ion & & Scatt tter ering ing (SPES) ES) – Advantages on biotech/DDS applications
Ptc Diameter [nm]
PS 600nm PMMA 600nm CeOx
Log Re S(0) Log Im S(0) PS
degradation/wetting
immiscible dropplets
Single gle Partic icle le Extinc nctio ion & & Scatt tter ering ing (SPES) ES) – Advantages on biotech/DDS applications
Impurities
Single gle Partic icle le Extinc nctio ion & & Scatt tter ering ing (SPES) ES) – Advantages on biotech/DDS applications
degradation/wetting
immiscible dropplets
CLASSIZER™ ONE v.07 – Single Particle Extinction & Scattering (SPES) patented technology
1 Sample and sample preparation dependent / preliminary tech
values
based ed on the patent nted ed Sing ngle le Partic icle le Extin inction ction and Scattering ering (SPES) ES) technolo nology gy Size measurem remen ent range nge1 Polymeric Oxide Gold 200nm-20000nm 100nm-10000nm 75nm-10000nm Size measurem remen ent resolu lutio ion1 Dielectric spheres diameter: 10% Re Refr fractiv ive e Index ex range nge1 Dielectric spheres: m = 1.0 - 2.5 Metallic or Complex Particles1 Refra ract ctiv ive e Index ex resolu lutio ion1 Dielectric spheres relative refractive index: 10% Numeric eric Partic icle le Concen entrat ratio ion1 104-107 particles/mL (typical) Fluid d Flow 0.1-100 mL/min (customizable)
CLASSIZER™ ONE v.07 – a novel device based on SPES patented technology
Potenza MAC, Sanvito T, Pullia A, J Nanopart Res 17 (2014)
CLASSIZER™ ONE v0.7 classifies the composition of single particle populations and measure with high resol
tion the particle size distribution, even for heterogeneous and polydisperse systems
Log Re S(0) Particle Diameter [nm] % ptc / BIN Log Im S(0)
PS
(PS = Polystyrene) COLLOIDS – Particle Size Distribution, Refractive Index Classification, Numerical Concentration
COLLOIDS – Analysis of heterogeneous systems
PS 600nm PMMA 600nm PS 600nm PMMA 600nm
Potenza MAC, Sanvito T, Fazio G, KONA Powder and Particle (2015)
CLASSIZER™ ONE v0.7 classifies the composition of single particle populations and measure with high resolution the particle size distribution, even for heterogeneou erogeneous and polydisperse systems
ABRASIVES – Particle Size Distribution of polydisperse samples
Potenza MAC, Sanvito T, Fazio G, KONA Powder and Particle (2015)
CLASSIZER™ ONE v0.7 classifies the composition of single particle populations and measure with high resolution the particle size distribution, even for heterogeneous and poly lydisperse disperse systems CeOx
CLASSIZER™ ONE v0.7 analyses products regardless the presence of synthesis scaps and impurities (e.g. slurry based on AlO2, CeO2 for the CMP of surfaces)
Potenza MAC, Sanvito T, Pullia A, J Nanopart Res 17 (2015) Potenza MAC, Sanvito T, Fazio G, KONA Powder and Particle (2015)
Impurities CeOx
SAVE TIME: NO PURIFICATION/FILTRATION/DIALISIS
CLASSIZER™ ONE v0.7 is able to discriminate di diff fferen erent inner nner str truct uctures ures for polymeric particles (e.g. Poly(lactic-co-glycolic acid) (PLGA) particles, D50 ~ 400nm)
Homogeneou
struc ucture ture with drug Homogeneou
struc ucture ture Core re-shel ell struc ucture ture PLGA degrada radation ion via water er inclu lusio ion
H2O H2O H2O Potenza MAC, Sanvito T, Argentiere S, Cella C, Paroli B, Lenardi C, Milani P, Scientific Reports 5 (2015)
DRUG DELIVERY SYSTEMS – Drug Loading and product stability
CLASSIZER™ ONE v0.7 discriminates between particles and murine serum components
Sanvito T, Bigini P, Cavanna MV, Fiordaliso F, Violatto M, Talamini L, Salmona M, Milani P, Potenza MAC, Nanomedicine (2017)
DRUG DELIVERY SYSTEMS: Measure stability in REAL Biological Media (PLASMA, BLOOD, …)
PLGA
CLASSIZER™ ONE v0.7 detects and monitors particles in medium as as compl complex as as unfiltered unfiltered bl bloo
cell ll ly lysates tes opening novel opportunity for understanding interaction with biocomponent
Sanvito T, Bigini P, Cavanna MV, Fiordaliso F, Violatto M, Talamini L, Salmona M, Milani P, Potenza MAC, Nanomedicine (2017)
DRUG DELIVERY SYSTEMS: Measure stability in REAL Biological Media (PLASMA, BLOOD, …)
Fi Filt ltered red Murine ne Blo lood Un Unfiltered ered Murine ne Blo lood
Potenza MAC, Cremonesi L, Delmonte B, Sanvito T, Paroli B, Pullia A, Baccolo G, Maggi V, ACS Earth Space Chem (2017)
CLASSIZER™ ONE v0.7 recognizes and characterizes aggregates in suspension. Information on aggregate compactness and aggregate size distribution are provided
IMPROVE PRODUCT STABILITY - Measure sample aggregation
Scattering signals of microsized particles strongly depends on their aspect ratio. Traditional technologies consider particles as spheres. Particles misinterpretation typically follows.
NON SPHERICAL PARTICLES – EFFECTIVE MEASUREMENTS
Quart rtz Kaolinit
“Measuring shape and size of micrometric particles from the analysis of the forward scattered field” , J. Appl. Phys. 119 (2016) “Shape and size constraints on dust optical properties from the Dome C ice core, Antarctica”, Scientific Reports 6 (2016)
CLASSIZER™ ONE v0.7 accesses to more parameters. Dedicated algorithms can be developed to interpret data. Information on aspect ratio and effective particle size distribution are retrieved.
NON SPHERICAL PARTICLES – EFFECTIVE MEASUREMENTS
“Measuring shape and size of micrometric particles from the analysis of the forward scattered field” , J. Appl. Phys. 119 (2016) “Shape and size constraints on dust optical properties from the Dome C ice core, Antarctica”, Scientific Reports 6 (2016)
CLASSIZER™ ONE v0.7 accesses to more parameters. Dedicated algorithms can be developed to interpret data. Information on aspect ratio and effective particle size distribution are retrieved.
NON SPHERICAL PARTICLES – EFFECTIVE MEASUREMENTS
“Measuring shape and size of micrometric particles from the analysis of the forward scattered field” , J. Appl. Phys. 119 (2016) “Shape and size constraints on dust optical properties from the Dome C ice core, Antarctica”, Scientific Reports 6 (2016)
CLASSIZER™ ONE v0.7 accesses to more parameters. Dedicated algorithms can be developed to interpret data. Information on aspect ratio and effective particle size distribution are retrieved.
“Measuring shape and size of micrometric particles from the analysis of the forward scattered field” , J. Appl. Phys. 119 (2016) “Shape and size constraints on dust optical properties from the Dome C ice core, Antarctica”, Scientific Reports 6 (2016)
NON SPHERICAL PARTICLES – EFFECTIVE MEASUREMENTS
OIL / LUBRICANTS – Effective analysis of impurities
Recognition/rejection of microbubbles/microdroplets Effective measurements of impurities
CLASSIZER™ ONE v0.7 is able to discriminate di differ fferen ent go gold nanopar nanoparti ticl cle of
simi milar ar size bu but di differ fferent ent surfac face shapes pes / rough ghnes ness due to surface plasmon resonance
Potenza M, Krpetic Z, Sanvito T, Cai Q, Monopoli M, de Araújo J, Cella C, Boselli L, Castagnola V, Milani P, Dawson K, Nanoscale (2017), Adv Article
METAL NANOPARTICLES
Sede Monza Via Carlo Rota, 37 20900 Monza (MB) Tel 039 834 977 Email: zagarella@optoprim.it Sede Roma Via Monte Giberto, 15 00138 Roma (RM) Tel 06 8765 7838 Email: ventura@optoprim.it