151 lines
39 KiB
XML
151 lines
39 KiB
XML
v {xschem version=3.0.0 file_version=1.2 }
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G {}
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K {}
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V {}
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S {}
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E {}
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B 2 1210 -510 1840 -30 {flags=graph
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y1=1.16665
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y2=5.05705
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divy=4
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subdivy=1
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x1=2.3
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x2=2.7
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divx=6
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subdivx=1
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node="v(diffout) v(plus) v(minus)"
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color="7 8 10 11 12 13 14 15 16 17"
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dataset=0
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}
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B 2 1230 -1050 1807 -523 {flags=image,unscaled
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}
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T {CMOS DIFFERENTIAL AMPLIFIER
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EXAMPLE} 250 -650 0 0 0.4 0.4 {}
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T {This is an example of a code block that will
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be placed as a header in the netlist.
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use 'place=header' attribute and set the
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header text as a 'value' attribute} 720 -720 0 0 0.4 0.4 {}
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T {Select one or more graphs (and no other objects)
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and use arrow keys to zoom / pan waveforms} 740 -800 0 0 0.3 0.3 {}
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T {gain AC plot at 1uA, 10uA, 100uA bias current} 1250 -1090 0 0 0.4 0.4 {layer=5}
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N 30 -310 30 -280 {lab=VCC}
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N 30 -310 60 -310 {lab=VCC}
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N 260 -240 260 -190 {lab=GN}
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N 260 -190 300 -190 {lab=GN}
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N 300 -190 300 -160 {lab=GN}
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N 300 -160 530 -160 {lab=GN}
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N 500 -290 520 -290 {lab=0}
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N 670 -290 690 -290 {lab=0}
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N 500 -260 690 -260 {lab=#net1}
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N 440 -290 460 -290 {lab=PLUS}
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N 730 -290 750 -290 {lab=MINUS}
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N 690 -490 740 -490 {lab=VCC}
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N 450 -490 500 -490 {lab=VCC}
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N 540 -490 650 -490 {lab=G}
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N 540 -490 540 -460 {lab=G}
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N 500 -460 540 -460 {lab=G}
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N 690 -560 690 -520 {lab=VCC}
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N 500 -560 690 -560 {lab=VCC}
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N 500 -560 500 -520 {lab=VCC}
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N 570 -580 570 -560 {lab=VCC}
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N 690 -420 830 -420 {lab=DIFFOUT}
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N 30 -440 30 -410 {lab=PLUS}
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N 30 -440 60 -440 {lab=PLUS}
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N 30 -590 30 -560 {lab=MINUS}
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N 30 -590 60 -590 {lab=MINUS}
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N 570 -130 570 -100 {lab=0}
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N 570 -130 590 -130 {lab=0}
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N 590 -160 590 -130 {lab=0}
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N 570 -160 590 -160 {lab=0}
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N 260 -130 260 -100 {lab=0}
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N 240 -130 260 -130 {lab=0}
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N 240 -160 240 -130 {lab=0}
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N 240 -160 260 -160 {lab=0}
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N 690 -460 690 -380 { lab=DIFFOUT}
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N 500 -460 500 -380 { lab=G}
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N 570 -260 570 -250 { lab=#net1}
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N 690 -380 690 -320 { lab=DIFFOUT}
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N 500 -380 500 -320 { lab=G}
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N 570 -250 570 -190 { lab=#net1}
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C {lab_pin.sym} 750 -360 0 0 {name=p20 lab=0 net_name=true}
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C {lab_pin.sym} 30 -220 0 0 {name=p17 lab=0 net_name=true}
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C {title.sym} 160 -30 0 0 {name=l1 author="Stefan Schippers" net_name=true}
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C {nmos4.sym} 550 -160 0 0 {name=m1 model=cmosn w=5u l=2u m=1 net_name=true}
|
|
C {pmos4.sym} 670 -490 0 0 {name=m2 model=cmosp w=5u l=2u m=1 net_name=true}
|
|
C {vsource.sym} 30 -250 0 0 {name=VVCC value=5 net_name=true}
|
|
C {lab_pin.sym} 570 -100 0 0 {name=p1 lab=0 net_name=true}
|
|
C {lab_pin.sym} 60 -310 0 1 {name=p2 lab=VCC net_name=true}
|
|
C {nmos4.sym} 280 -160 0 1 {name=m3 model=cmosn w=5u l=2u m=1 net_name=true}
|
|
C {lab_pin.sym} 260 -100 0 0 {name=p3 lab=0 net_name=true}
|
|
C {isource.sym} 260 -270 0 0 {name=IBIAS value=100u net_name=true}
|
|
C {lab_pin.sym} 260 -300 0 0 {name=p4 lab=0 net_name=true}
|
|
C {nmos4.sym} 480 -290 0 0 {name=m4 model=cmosn w=10u l=1u m=1 net_name=true}
|
|
C {lab_pin.sym} 520 -290 0 1 {name=p5 lab=0 net_name=true}
|
|
C {nmos4.sym} 710 -290 0 1 {name=m5 model=cmosn w=10u l=1u m=1 net_name=true}
|
|
C {lab_pin.sym} 670 -290 0 0 {name=p0 lab=0 net_name=true}
|
|
C {lab_pin.sym} 740 -490 0 1 {name=p6 lab=VCC net_name=true}
|
|
C {pmos4.sym} 520 -490 0 1 {name=m6 model=cmosp w=5u l=2u m=1 net_name=true}
|
|
C {lab_pin.sym} 450 -490 0 0 {name=p7 lab=VCC net_name=true}
|
|
C {lab_pin.sym} 570 -580 0 0 {name=p8 lab=VCC net_name=true}
|
|
C {lab_pin.sym} 440 -290 0 0 {name=p9 lab=PLUS net_name=true}
|
|
C {lab_pin.sym} 750 -290 0 1 {name=p10 lab=MINUS net_name=true}
|
|
C {lab_pin.sym} 830 -420 0 1 {name=p11 lab=DIFFOUT net_name=true}
|
|
C {lab_pin.sym} 260 -210 0 0 {name=p13 lab=GN net_name=true}
|
|
C {lab_pin.sym} 30 -350 0 0 {name=p14 lab=0 net_name=true}
|
|
C {vsource.sym} 30 -380 0 0 {name=VPLUS value="2.5 pwl 0 2.4 10n 2.4 10.1n 2.6" net_name=true}
|
|
C {lab_pin.sym} 60 -440 0 1 {name=p15 lab=PLUS net_name=true}
|
|
C {lab_pin.sym} 30 -500 0 0 {name=p16 lab=0 net_name=true}
|
|
C {vsource.sym} 30 -530 0 0 {name=V1 value=2.5 net_name=true}
|
|
C {lab_pin.sym} 60 -590 0 1 {name=p18 lab=MINUS net_name=true}
|
|
C {capa.sym} 750 -390 0 0 {name=CL
|
|
m=1
|
|
value=2p
|
|
footprint=1206
|
|
device="ceramic capacitor" net_name=true}
|
|
C {code.sym} 900 -190 0 0 {name=STIMULI
|
|
only_toplevel=true
|
|
value=".temp 30
|
|
** models are generally not free: you must download
|
|
** SPICE models for active devices and put them into the below
|
|
** referenced file in netlist/simulation directory.
|
|
.include \\"models_cmos_example.txt\\"
|
|
.option savecurrents
|
|
.save all @m4[gm] @m5[gm] @m1[gm]
|
|
.control
|
|
save all
|
|
set appendwrite
|
|
op
|
|
write cmos_example.raw
|
|
* tran 1n 300n
|
|
dc vplus 2.3 2.7 0.001
|
|
write cmos_example.raw
|
|
.endc
|
|
|
|
"}
|
|
C {lab_pin.sym} 500 -430 0 0 {name=p12 lab=G net_name=true}
|
|
C {launcher.sym} 700 -60 0 0 {name=h1
|
|
descr=Backannotate
|
|
tclcommand="ngspice::annotate"}
|
|
C {launcher.sym} 700 -110 0 0 {name=h2
|
|
descr="View raw file"
|
|
tclcommand="textwindow $netlist_dir/cmos_example.raw"}
|
|
C {ngspice_probe.sym} 500 -390 0 0 {name=r1}
|
|
C {ngspice_probe.sym} 420 -160 0 0 {name=r2}
|
|
C {ngspice_probe.sym} 600 -260 0 0 {name=r3}
|
|
C {ngspice_probe.sym} 770 -420 0 0 {name=r4}
|
|
C {ngspice_get_value.sym} 620 -160 0 0 {name=r5 node=i(@$\{path\}m1[id])
|
|
descr="I="}
|
|
C {code.sym} 920 -580 0 0 {name=HEADER
|
|
place=header
|
|
only_toplevel=true
|
|
value="** ======================== **
|
|
** This is a netlist header **
|
|
** ======================== **"}
|
|
C {launcher.sym} 755 -835 0 0 {name=h3
|
|
descr="Select arrow and
|
|
Ctrl-Left-Click to load/unload waveforms"
|
|
tclcommand="
|
|
xschem raw_read $netlist_dir/[file tail [file rootname [xschem get current_name]]].raw
|
|
"
|
|
}
|