WNGZWZSS0110rqql? GenevaDJ2  AUTOSAVE.WKZ(#04)d!    rv0 ,Xd@CC$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqr@ Ca@ Cb@ End_pH@ Ka@  Kw@ Start_pH@ Va@ K1a@ K2a@ K3a@C$@24@@4 0%2 @400 0.@40 0/@ 0000 0.!@400 0/@4 0 0.0 0 0.0 0 0.%& @40%2@4/ @400/@40/ 000/@400/@4 0.0 0.0 0.'1%2"@ C@ ,@)$@/%0/%1@$@2%4@B  /%-D@.@$@2%4@ @ .@  @ $@2%4@ C @4 @40 0/@4 0.@ 0@40 0 0/@4 0 0.@ 00 0 0 0/@4 0 0 0.@4 0/@4 0 0/ 0 0 0/  0 0 0/%0% 0@4. /%@4@4 0. 0 0.  0 0.%0%1%2"@ @ @ @ @ @ /%1/%2@  @  Geneva @  Geneva @  Geneva @  Geneva @  Geneva @ l Geneva @  Geneva @  Geneva @  Geneva @   Acid conc.  Acid vol.  Base Conc. pK1 pK2 pK3(K1a(K2aK3a(Kw Start pH End pH @  ? $@ ? @ @ )@5B( zGz?5B( Ll8>5B( 3*@V=@(+=  333333)@ @@ @?Type in your data here @<titrant volume0pH @:]ݮ?? @:IBx@SQ@ @:BaCf@أp= @ @:" a4,!@](\@ @: o"@zG @ @: jA#@gfffff@ @: y-$@Q@ @ _*d2n$@? ףp=@ @ @-(%@@ @ w&@(\@ @ -_*@Q@ @ IaB/@KzG@ @ 2B\41@ףp= @ @ ܊-3@hfffff @ @ 3@IzG!@ @ |3@*\("@ @ Y4@Q#@ @ U5\4@Gz%@ @ D4@(\&@ @&Q;X6@p= ףp'@ @&`9@QQ(@ @  =@233333)@ @ {ŗC@Gz*@ @  @  @  @  @  @ ! @ " @m#0pH0[H+]0calc Vb0 calc pH measured Vb Measured pH @N$% %i@% &$#% @N%%= ףp=%wy@% ̙#%= ףp= @N&%zGz%H@% #$#%zGz @N'%o= ףp %M M@% #%o= ףp  @N(%Q %s 4'@% XCwC#%Q  @N)%efffff%u 9@% #%efffff @N*%zG%EƢl@% U.k#%zG @N+%Q%8IT@% w#%Q @N,%Gz%}A:3>@% r#%Gz @N-%p= ף%=%@% @#%p= ף @N.%/33333%mR<@% 7'ڷ"%/33333 @N/%hGzĿ%Vs ?% 7!%hGzĿ @N0%Q?%9?% ؁S,%Q? @j1%ףp= ?%_Mc?% rE+%ףp= ?Data are echoed here @|2%(\?%r?% ӑt%(\?%]ݮ?%?%؁S, @3 %?%r¸?% U1?%?%IBx@%SQ@%U1?%k%  @$@%Q@%@-(%@%@% @$@%,ߥ,8@ @; %|Gz@%PR))*>% 8K<$@%|Gz@%w&@%(\@%8K<$@%(&@ @< %? ףp=@%_>>% K &@%? ףp=@%-_*@%Q@%K &@% ^@ @= %@%yư>% N((@%@%IaB/@%KzG@%N((@%Ī\ @> %(\@%M ,]>% 3Q hHO-@%(\@%2B\41@%ףp= @%3Q hHO-@%I B @? %Q@%Z~>% 91@%Q@%܊-3@%hfffff @%91@%E8T @@ %KzG@%2%=i>% ѹ{2@%KzG@%3@%IzG!@%ѹ{2@%_5ic @A %ףp= @%ԨR>% ?`pz3@%ףp= @%|3@%*\("@%?`pz3@%1ޅ͋? @B %hfffff @%ш s;>% (F3@%hfffff @%Y4@%Q#@%(F3@%-{%l-@ @C %IzG!@%u֫#>% c(3@%IzG!@%U5\4@%Gz%@%c(3@%%)J@ @D %*\("@%:E >% ;זJ3@%*\("@%D4@%(\&@%;זJ3@%Gc@ @E % ףp= #@%!X=% H@4@% ףp= #@%Q;X6@%p= ףp'@%H@4@%7;61Kt@ @F %Q#@%/#=% U%4G 4@%Q#@%`9@%QQ(@%U%4G 4@%Nɭ+q@ @G %$@%\t>=% ˨4@%$@% =@%233333)@%˨4@%`?^@ @H %Gz%@% >ɯ=% J$'L4@%Gz%@%{ŗC@%Gz*@%J$'L4@%, E@ @I %(\&@%*I=% a|{4@%(\&@%%%a|{4@%hx#@ @J %p= ףp'@%yQ€=% RV36@%p= ףp'@%%%RV36@%Xl`g; @K %QQ(@%uWh=% {@+9@%QQ(@%%%{@+9@%(w @L %233333)@%=R'Q=% |`s'@@%233333)@%%%|`s'@@%fC % @M %Gz*@%ܓ 9=% ^L@%Gz*@%%%^L@%(f9( @`N%(\*@%5"=% z^œh%(\*@%% @`O%գp= +@%)% =% c`;%գp= +@%% @`P%Q,@%wU<% v}2-%Q,@%% @`Q%-@%jl<% acK'%-@%% @`R%xGz.@%r1"<% 3*%%xGz.@%% @`S%Y(\/@%i{g$<% 4(k$%Y(\/@%% @`T%Q0@%CPݕ<% Tq`&$%Q0@%% @`U%(\0@%t^ <% zqn$%(\0@%% @`V%0@%FFg<% ^ $%0@%% @`W%p= ףp1@%Ÿ]xP<% }$%p= ףp1@%% @`X%zG1@%߭JQ8<% jʬ$%zG1@%% @`Y%RQ2@%!<% X>$%RQ2@%% @`Z%(\2@%>9 <% X$%(\2@%% @`[%4333333@%D`;% R%E$%4333333@%% @`\%p= ף3@% ;% a$$%p= ף3@%% @`]%Gz4@%!&;% q$%Gz4@%% @`^%Q4@%`˅;% 0Ue$%Q4@%% @`_%(\4@%[B>;% $$%(\4@%% @``%ifffff5@%9~;% [ $%ifffff5@%% @`a%ڣp= 5@%6e;% $%ڣp= 5@%% @`b%KzG6@%腗O;% a$%KzG6@%% @`c%Q6@%j 7;% $%Q6@%% @`d%-\(7@%ɒ9 ;% m;$%-\(7@%% @`e%7@%w+!K;% $%7@%% @`f%ףp= 8@% 2:% $%ףp= 8@%% @ g%% @ h%% @ i%% @ j%% @ k%% @ l%% @ m%% @ n%% @ o%% @ p%% @ q%% @ r%%2BU  Chicago Geneva++@,Click on these buttons for scale expansion  Geneva Geneva((*>pH 10-13onA0pH 10-13Y 4   select chart 52 axis 3 manual scaling from 10 to 13 with 5 major and 5 minor divisions ( Chicago GenevaP6pH 1-3tton@ jpH 1-3W 4 select chart 52 axis 3 manual scaling from 1 to 3 with 4 major and 5 minor divisions ( Chicago GenevaP=pH 1-13ton? ApH 1-13Y 4   select chart 52 axis 3 manual scaling from 1 to 13 with 12 major and 5 minor divisions ( Chicago GenevaP8pH 6-8tton> (pH 6-8W 4 select chart 52 axis 3 manual scaling from 6 to 8 with 4 major and 5 minor divisions ( Chicago GenevaP;0-75 mLton=P0-75 mLW 4 Kselect chart 52 axis 1 manual scaling from 0 to 75 with 15 major and 5 minor divisions( Chicago Geneva0=0-40 mLton<`0-40 mLY 4 ( select chart 52 axis 1 manual scaling from 0 to 40 with 10 major and 5 minor divisions ( Chicago Geneva05$d  Chicago Geneva @,pH Geneva((%q Chicago Geneva@,Titrant volume, mL  Geneva((g4@2W2W& T$D@$@ $@,@$@ ?*@$@ $@ <22@2(2W2Wx(2W2Wn,j  Chicago Geneva@` ,Instructions: Enter your experimental data (titrant volume in mL vs measured pH) into the table on the right. Then enter the known parameters across the top: usually the acid volume (mL), base concentration (Molar), and the acid constants, as pK1, pK2, and pK3. These are the six bold-face numbers across the top above the graph. To change a parameter, click on the number, edit the value displayed in the entry box at the top of the screen, then click on the check mark or press the enter key. Finally, adjust the unknown parameters (e.g. acid concentration) until the calculated curve (solid line) goes through the center of the experimental data points (circles) on the graph. Any or all of the four parameters (Acid conc., Acid vol, Base conc, and pK1, 2 and 3) can be unknown parameters; however, the more parameters that are known, the easier it is to adjust the remaining ones to optimize the fit. Note: You can fine-tune the fit more precicely by expanding the scale of the plot. For example, you can locate the endpoint more exactly by expanding the x-axis: to do this, click on the x-axis line, pull down the Graph menu, select the Axes sub-menu, select Scale info..., type the the desired mininum and maximum x-axis limits, and click on OK. T. C. O'Haver, 1990 Geneva Geneva(( {mr)# # Chicago Geneva, Geneva((|88,,x,, ~ y b (,, d'D-@@!"4