1 / 24

Rotational Ambiguity in Hard-Soft Modeling Method

Rotational Ambiguity in Hard-Soft Modeling Method. Hard-Soft Modeling.

yehuda
Download Presentation

Rotational Ambiguity in Hard-Soft Modeling Method

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Rotational Ambiguity in Hard-Soft Modeling Method

  2. Hard-Soft Modeling A approach mixing the qualities of hard-modeling and soft-modeling methods is proposed to analyze chemical data. The soft-modeling method, which obtains the pure concentration profiles and spectra of all absorbing species present in the raw measurements by using typical s constraints, a hard constraint is introduced to force some or all the concentration profiles to fulfill a known chemical model, which is refined at each iterative cycle of the optimization process. This modification of soft method drastically decreases the rotational ambiguity associated with the profiles obtained using exclusively constraints. The optional inclusion of some or all the absorbing species into the known chemical model allows the successful treatment of data matrices whose instrumental response is not exclusively due to the chemical components involved in the known process, an impossible scenario for classical hard-modeling approaches

  3. Hard-Soft Modeling Procedure 1 1 ABCX ABCX 0.9 0.9 A C A C 0.8 0.8 0.7 0.7 0.6 0.6 Concentration (a.u.) 0.5 0.5 Concentration (a.u.) 0.4 0.4 B B X X 0.3 0.3 0.2 0.2 0.1 0.1 CSM CHM 0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Time C Time C Non-linear model fitting min(CHM - CSM) CHM = f(k1, k2) • All or some of the concentration profiles can be constrained. • All or some of the batches can be constrained.

  4. Hard-Soft Modeling in Two-Components system 1T12 T21 1 u1 + T12 u2 T21 u1 + u2 [ u1 u2 ] = = [ c1 c2 ] = C UT = c1= u1 +T12 u2 c2=T21 u1 + u2 v1 v2 a1 a2 1-T12 -T21 1 1 = A T-1V = = 1 - T12 T21 1 a1= (v1 - T21 v2) 1 - T12 T21 1 a2=(-T12v1 +v2) 1 - T12 T21

  5. GridSearch2_HSM.m HSM in 2 component system

  6. ? Shows the effects of introducing the hard modeling constraint on second component concentration profile

  7. Concentration Profiles Matrix in Three Components System 1 1 1 [ u1 u2 u3] T21 T22 T23 UT = = [ c1 c2 c3 ] = C T31 T32 T33 c1= u1 +T21 u2 + T31 u3 c2= u1 +T22 u2 + T32 u3 c3= u1 +T23 u2 + T33 u3

  8. Spectral Profiles Matrix in Three Components System T22T33 - T32T23 T32 - T33 T23 - T22 v1 v2 T-1V = T23T31 - T21T33 T33 - T31 T21 - T23 v3 T21T32 - T22T31 T31 - T32 T22 - T21 1 1 1 det (T) det (T) det (T) 1 det (T) a1 = ((T22T33 - T32T23) v1 + (T32 - T33 ) v2+ (T23 - T22) v3) a2 = ((T23T31 – T21T33) v1 + (T33 - T31 ) v2+ (T21 - T23) v3) a1 = ((T21T32 – T22T31) v1 + (T31 - T32 ) v2+ (T22 - T21) v3)

  9. Hard-Soft Modeling for a Typical Kinetics System k1 A B K1≠ k1 k2 C D A, B and D are absorbing

  10. Visualization the Area of Feasible Solutions -Concentration Profiles Space

  11. Visualization the Area of Feasible Solutions -Spectral Profiles Space

  12. Introducing the hard constraint on A and B -Concentration Profiles Space

  13. Visualization the Area of Feasible Solutions -Spectral Profiles Space

  14. ? How we can use the obxerved correspondence between concentration and spectral profiles?

More Related