Methanol

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Methanol 

Methanol

Names
Pronunciation	/ˈmɛθənɒl/
Preferred IUPAC name Methanol
Other names Carbinol Columbian spirits Hydroxymethane MeOH Methyl alcohol Methyl hydroxide Methylic alcohol Methylol Methylene hydrate Pyroligneous spirit Wood alcohol Wood naphtha Wood spirit
Identifiers
CAS Number	67-56-1
3D model (JSmol)	Interactive image
3DMet	B01170
Beilstein Reference	1098229
ChEBI	CHEBI:17790
ChEMBL	ChEMBL14688
ChemSpider	864
ECHA InfoCard	100.000.599
EC Number	200-659-6
Gmelin Reference	449
KEGG	D02309
MeSH	Methanol
PubChem CID	887
RTECS number	PC1400000
UNII	Y4S76JWI15
UN number	1230
CompTox Dashboard (EPA)	DTXSID2021731

InChI

SMILES
Properties
Chemical formula	CH 3OH or CH 4O
Molar mass	32.04 g mol−1
Appearance	Colourless liquid
Odor	Sweet and pungent
Density	0.792 g/cm3
Melting point	−97.6 °C (−143.7 °F; 175.6 K)
Boiling point	64.7 °C (148.5 °F; 337.8 K)
Solubility in water	miscible
log P	−0.69
Vapor pressure	13.02 kPa (at 20 °C)
Acidity (pKa)	15.5
Conjugate acid	Methyloxonium
Conjugate base	Methanolate
Magnetic susceptibility (χ)	−21.40·10−6 cm3/mol
Refractive index (nD)	1.33141
Viscosity	0.545 mPa·s (at 25 °C)
Dipole moment	1.69 D
Thermochemistry
Heat of combustion, higher value (HHV)	725.7 kJ/mol, 173.4 kcal/mol, 5.77 kcal/g
Hazards
Occupational safety and health (OHS/OSH):
Main hazards	Methanol and its vapours are flammable. Moderately toxic for small animals – Highly toxic to large animals and humans – May be fatal/lethal or cause blindness and damage to the liver, kidneys, and heart if swallowed – Toxicity effects from repeated over exposure have an accumulative effect on the central nervous system, especially the optic nerve – Symptoms may be delayed, become severe after 12 to 18 hours, and linger for several days after exposure
GHS labelling:
Pictograms
Signal word	Danger
Hazard statements	H225, H301, H311, H331, H370
Precautionary statements	P210, P233, P235, P240, P241, P242, P243, P260, P264, P270, P271, P280, P301+P330+P331, P302+P352, P303+P361+P353, P304+P340, P305+P351+P338, P307+P311, P310, P311, P312, P337+P313, P361, P363, P370+P378, P403+P233, P405, P501
NFPA 704 (fire diamond)	1 3 0
Flash point	11 to 12 °C (52 to 54 °F; 284 to 285 K)
Autoignition temperature	470 °C (878 °F; 743 K) 385 °C (725 °F; 658 K)
Explosive limits	6–36%
Lethal dose or concentration (LD, LC):
LD50 (median dose)	5628 mg/kg (rat, oral) 7300 mg/kg (mouse, oral) 12880 mg/kg (rat, oral) 14200 mg/kg (rabbit, oral)
LC50 (median concentration)	64,000 ppm (rat, 4 h)
LCLo (lowest published)	33,082 ppm (cat, 6 h) 37,594 ppm (mouse, 2 h)
NIOSH (US health exposure limits):
PEL (Permissible)	TWA 200 ppm (260 mg/m3)
REL (Recommended)	TWA 200 ppm (260 mg/m3) ST 250 ppm (325 mg/m3) [skin]
IDLH (Immediate danger)	6000 ppm
Safety data sheet (SDS)
Related compounds
Related compounds	Methanethiol Silanol Ethanol
Supplementary data page
Methanol (data page)
Except where otherwise noted, data are given for materials in their standard state (at 25 °C [77 °F], 100 kPa).

Methanol, also known as methyl alcohol, amongst other names, is a chemical and the simplest alcohol, with the formula CH₃OH (a methyl group linked to a hydroxyl group, often abbreviated MeOH). It is a light, volatile, colourless, flammable liquid with a distinctive alcoholic odour similar to that of ethanol (potable alcohol). A polar solvent, methanol acquired the name wood alcohol because it was once produced chiefly by the destructive distillation of wood. Today, methanol is mainly produced industrially by hydrogenation of carbon monoxide.

Methanol consists of a methyl group linked to a polar hydroxyl group. With more than 20 million tons produced annually, it is used as a precursor to other commodity chemicals, including formaldehyde, acetic acid, methyl tert-butyl ether, methyl benzoate, anisole, peroxyacids, as well as a host of more specialised chemicals.

Occurrence

Small amounts of methanol are present in normal, healthy human individuals. One study found a mean of 4.5 ppm in the exhaled breath of test subjects. The mean endogenous methanol in humans of 0.45 g/d may be metabolized from pectin found in fruit; one kilogram of apple produces up to 1.4 g of methanol.

Methanol is produced by anaerobic bacteria and phytoplankton.

Interstellar medium

Methanol is also found in abundant quantities in star-forming regions of space and is used in astronomy as a marker for such regions. It is detected through its spectral emission lines.

In 2006, astronomers using the MERLIN array of radio telescopes at Jodrell Bank Observatory discovered a large cloud of methanol in space 463 terametres (288 billion miles) across. In 2016, astronomers detected methanol in a planet-forming disc around the young star TW Hydrae using ALMA radio telescope.

Safety

Methanol is highly flammable. Its vapours are slightly heavier than air, can travel and ignite. Methanol fires should be extinguished with dry chemical, carbon dioxide, water spray or alcohol-resistant foam.

Toxicity

Main article: Methanol toxicity

See also: List of methanol poisoning incidents

Ingesting as little as 10 mL (0.34 US fl oz) of pure methanol can cause permanent blindness by destruction of the optic nerve. 30 mL (1.0 US fl oz) is potentially fatal. The median lethal dose is 100 mL (3.4 US fl oz), i.e., 1–2 mL/kg body weight of pure methanol. The reference dose for methanol is 0.5 mg/kg in a day. Toxic effects begin hours after ingestion, and antidotes can often prevent permanent damage. Because of its similarities in both appearance and odor to ethanol (the alcohol in beverages), it is difficult to differentiate between the two; such is also the case with denatured alcohol, adulterated liquors or very low quality alcoholic beverages.

Methanol is toxic by two mechanisms. First, methanol can be fatal due to effects on the central nervous system, acting as a central nervous system depressant in the same manner as ethanol poisoning. Second, in a process of toxication, it is metabolised to formic acid (which is present as the formate ion) via formaldehyde in a process initiated by the enzyme alcohol dehydrogenase in the liver. Methanol is converted to formaldehyde via alcohol dehydrogenase (ADH) and formaldehyde is converted to formic acid (formate) via aldehyde dehydrogenase (ALDH). The conversion to formate via ALDH proceeds completely, with no detectable formaldehyde remaining. Formate is toxic because it inhibits mitochondrial cytochrome c oxidase, causing hypoxia at the cellular level, and metabolic acidosis, among a variety of other metabolic disturbances.

Outbreaks of methanol poisoning have occurred primarily due to contamination of drinking alcohol. This is more common in the developing world. In 2013 more than 1700 cases nonetheless occurred in the United States. Those affected are often adult men. Outcomes may be good with early treatment. Toxicity to methanol was described as early as 1856.

Because of its toxic properties, methanol is frequently used as a denaturant additive for ethanol manufactured for industrial uses. This addition of methanol exempts industrial ethanol (commonly known as "denatured alcohol" or "methylated spirit") from liquor excise taxation in the US and some other countries.

During the course of the COVID-19 pandemic, the U.S. Food and Drug Administration found a number of hand sanitizer products being sold that were labeled as containing ethanol but tested positive for methanol contamination. Due to the toxic effects of methanol when absorbed through the skin or ingested, in contrast to the relatively safer ethanol, the FDA ordered recalls of such hand sanitizer products containing methanol, and issued an import alert to stop these products from illegally entering the U.S. market.

Applications

Formaldehyde, acetic acid, methyl tert-butylether

Methanol is primarily converted to formaldehyde, which is widely used in many areas, especially polymers. The conversion entails oxidation:

${\displaystyle {\ce {2 CH3OH + O2 -> 2 CH2O + 2 H2O}}}$

Acetic acid can be produced from methanol.

The Cativa process converts methanol into acetic acid.

Methanol and isobutene are combined to give methyl tert-butyl ether (MTBE). MTBE is a major octane booster in gasoline.

Methanol to hydrocarbons, olefins, gasoline

Condensation of methanol to produce hydrocarbons and even aromatic systems is the basis of several technologies related to gas to liquids. These include methanol-to-hydrocarbons (MtH), methanol to gasoline (MtG), methanol to olefins (MtO), and methanol to propylene (MtP). These conversions are catalyzed by zeolites as heterogeneous catalysts. The MtG process was once commercialized at Motunui in New Zealand.

Gasoline additive

The European Fuel Quality Directive allows fuel producers to blend up to 3% methanol, with an equal amount of cosolvent, with gasoline sold in Europe. China uses more than 4.5 billion liters of methanol per year as a transportation fuel in low level blends for conventional vehicles, and high level blends in vehicles designed for methanol fuels. In recent years, however, most modern gasoline-using vehicles can use a variety of alcohol fuels, resulting in similar or higher horsepower, but for a simple change in the vehicle's software settings and possibly a 50 cent seal or tube part.

Other chemicals

Methanol is the precursor to most simple methylamines, methyl halides, and methyl ethers. Methyl esters are produced from methanol, including the transesterification of fats and production of biodiesel via transesterification.

Niche and potential uses

Energy carrier

Methanol is a promising energy carrier because, as a liquid, it is easier to store than hydrogen and natural gas. Its energy density is, however, low than methane, per kg. Its combustion energy density is 15.6 MJ/L, whereas that of ethanol is 24 and gasoline is 33 MJ/L.

Further advantages for methanol is its ready biodegradability and low environmental toxicity. It does not persist in either aerobic (oxygen-present) or anaerobic (oxygen-absent) environments. The half-life for methanol in groundwater is just one to seven days, while many common gasoline components have half-lives in the hundreds of days (such as benzene at 10–730 days). Since methanol is miscible with water and biodegradable, it is unlikely to accumulate in groundwater, surface water, air or soil.

Fuel

Main articles: Methanol fuel and methanol economy

Methanol is occasionally used to fuel internal combustion engines. It burns forming carbon dioxide and water:

${\displaystyle {\ce {2 CH3OH + 3 O2 -> 2 CO2 + 4 H2O}}}$

Methanol fuel has been proposed for ground transportation. The chief advantage of a methanol economy is that it could be adapted to gasoline internal combustion engines with minimum modification to the engines and to the infrastructure that delivers and stores liquid fuel. Its energy density, however, is less than gasoline, meaning more frequent fill ups would be required. However, it is equivalent to super high-octane gasoline in horsepower, and most modern computer-controlled fuel injection systems can already use it.

Methanol is an alternative fuel for ships that helps the shipping industry meet increasingly strict emissions regulations. It significantly reduces emissions of sulphur oxides (SOx), nitrogen oxides (NOx) and particulate matter. Methanol can be used with high efficiency in marine diesel engines after minor modifications using a small amount of pilot fuel (Dual fuel).

In China, methanol fuels industrial boilers, which are used extensively to generate heat and steam for various industrial applications and residential heating. Its use is displacing coal, which is under pressure from increasingly stringent environmental regulations.

Direct-methanol fuel cells are unique in their low temperature, atmospheric pressure operation, which lets them be greatly miniaturized. This, combined with the relatively easy and safe storage and handling of methanol, may open the possibility of fuel cell-powered consumer electronics, such as laptop computers and mobile phones.

Methanol is also a widely used fuel in camping and boating stoves. Methanol burns well in an unpressurized burner, so alcohol stoves are often very simple, sometimes little more than a cup to hold fuel. This lack of complexity makes them a favorite of hikers who spend extended time in the wilderness. Similarly, the alcohol can be gelled to reduce risk of leaking or spilling, as with the brand "Sterno".

Methanol is mixed with water and injected into high performance diesel and gasoline engines for an increase of power and a decrease in intake air temperature in a process known as water methanol injection.

Other applications

Methanol is used as a denaturant for ethanol, the product being known as "denatured alcohol" or "methylated spirit". This was commonly used during the Prohibition to discourage consumption of bootlegged liquor, and ended up causing several deaths. These types of practices are now illegal in the United States, being considered homicide.

Methanol is used as a solvent and as an antifreeze in pipelines and windshield washer fluid. Methanol was used as an automobile coolant antifreeze in the early 1900s. As of May 2018, methanol was banned in the EU for use in windscreen washing or defrosting due to its risk of human consumption as a result of 2012 Czech Republic methanol poisonings.

In some wastewater treatment plants, a small amount of methanol is added to wastewater to provide a carbon food source for the denitrifying bacteria, which convert nitrates to nitrogen gas and reduce the nitrification of sensitive aquifers.

Methanol is used as a destaining agent in polyacrylamide gel electrophoresis.

Production

From synthesis gas

Carbon monoxide and hydrogen react over a catalyst to produce methanol. Today, the most widely used catalyst is a mixture of copper and zinc oxides, supported on alumina, as first used by ICI in 1966. At 5–10 MPa (50–100 atm) and 250 °C (482 °F), the reaction

${\displaystyle {\ce {CO + 2 H2 -> CH3OH}}}$

is characterized by high selectivity (>99.8%). The production of synthesis gas from methane produces three moles of hydrogen for every mole of carbon monoxide, whereas the synthesis consumes only two moles of hydrogen gas per mole of carbon monoxide. One way of dealing with the excess hydrogen is to inject carbon dioxide into the methanol synthesis reactor, where it, too, reacts to form methanol according to the equation

${\displaystyle {\ce {CO2 + 3 H2 -> CH3OH + H2O}}}$.

In terms of mechanism, the process occurs via initial conversion of CO into CO₂, which is then hydrogenated:

${\displaystyle {\ce {CO2 + 3 H2 -> CH3OH + H2O}}}$

where the H₂O byproduct is recycled via the water-gas shift reaction

${\displaystyle {\ce {CO + H2O -> CO2 + H2}}}$.

This gives an overall reaction

${\displaystyle {\ce {CO + 2 H2 -> CH3OH}}}$,

which is the same as listed above. In a process closely related to methanol production from synthesis gas, a feed of hydrogen and CO₂ can be used directly. The main advantage of this process is that captured CO₂ and hydrogen sourced from electrolysis could be used, removing the dependence on fossil fuels.

Biosynthesis

The catalytic conversion of methane to methanol is effected by enzymes including methane monooxygenases. These enzymes are mixed-function oxygenases, i.e. oxygenation is coupled with production of water and NAD⁺:

${\displaystyle {\ce {CH4 + O2 + NADPH + H^+ -> CH3OH + H2O + NAD^+}}}$.

Both Fe- and Cu-dependent enzymes have been characterized. Intense but largely fruitless efforts have been undertaken to emulate this reactivity. Methanol is more easily oxidized than is the feedstock methane, so the reactions tend not to be selective. Some strategies exist to circumvent this problem. Examples include Shilov systems and Fe- and Cu containing zeolites. These systems do not necessarily mimic the mechanisms employed by metalloenzymes, but draw some inspiration from them. Active sites can vary substantially from those known in the enzymes. For example, a dinuclear active site is proposed in the sMMO enzyme, whereas a mononuclear iron (alpha-oxygen) is proposed in the Fe-zeolite.

Quality specifications and analysis

Methanol is available commercially in various purity grades. Commercial methanol is generally classified according to ASTM purity grades A and AA. Both grade A and grade AA purity are 99.85% methanol by weight. Grade "AA" methanol contains trace amounts of ethanol as well.

Methanol for chemical use normally corresponds to Grade AA. In addition to water, typical impurities include acetone and ethanol (which are very difficult to separate by distillation). UV-vis spectroscopy is a convenient method for detecting aromatic impurities. Water content can be determined by the Karl-Fischer titration.

History

In their embalming process, the ancient Egyptians used a mixture of substances, including methanol, which they obtained from the pyrolysis of wood. Pure methanol, however, was first isolated in 1661 by Robert Boyle, when he produced it via the distillation of buxus (boxwood). It later became known as "pyroxylic spirit". In 1834, the French chemists Jean-Baptiste Dumas and Eugene Peligot determined its elemental composition.

They also introduced the word "methylène" to organic chemistry, forming it from Greek methy = "alcoholic liquid" + hȳlē = "forest, wood, timber, material". "Methylène" designated a "radical" that was about 14% hydrogen by weight and contained one carbon atom. This would be CH₂, but at the time carbon was thought to have an atomic weight only six times that of hydrogen, so they gave the formula as CH. They then called wood alcohol (l'esprit de bois) "bihydrate de méthylène" (bihydrate because they thought the formula was C₄H₈O₄ = (CH)₄(H₂O)₂). The term "methyl" was derived in about 1840 by back-formation from "methylene", and was then applied to describe "methyl alcohol". This was shortened to "methanol" in 1892 by the International Conference on Chemical Nomenclature. The suffix -yl, which, in organic chemistry, forms names of carbon groups, is from the word methyl.

French chemist Paul Sabatier presented the first process that could be used to produce methanol synthetically in 1905. This process suggested that carbon dioxide and hydrogen could be reacted to produce methanol. German chemists Alwin Mittasch and Mathias Pier, working for Badische-Anilin & Soda-Fabrik (BASF), developed a means to convert synthesis gas (a mixture of carbon monoxide, carbon dioxide, and hydrogen) into methanol and received a patent. According to Bozzano and Manenti, BASF's process was first utilized in Leuna, Germany in 1923. Operating conditions consisted of "high" temperatures (between 300 and 400 °C) and pressures (between 250 and 350 atm) with a zinc/chromium oxide catalyst.

US patent 1,569,775 (US 1569775) was applied for on 4 Sep 1924 and issued on 12 January 1926 to BASF; the process used a chromium and manganese oxide catalyst with extremely vigorous conditions: pressures ranging from 50 to 220 atm, and temperatures up to 450 °C. Modern methanol production has been made more efficient through use of catalysts (commonly copper) capable of operating at lower pressures. The modern low pressure methanol (LPM) process was developed by ICI in the late 1960s US 3326956 with the technology patent since long expired.

During World War II, methanol was used as a fuel in several German military rocket designs, under the name M-Stoff, and in a roughly 50/50 mixture with hydrazine, known as C-Stoff.

The use of methanol as a motor fuel received attention during the oil crises of the 1970s. By the mid-1990s, over 20,000 methanol "flexible fuel vehicles" (FFV) capable of operating on methanol or gasoline were introduced in the U.S. In addition, low levels of methanol were blended in gasoline fuels sold in Europe during much of the 1980s and early-1990s. Automakers stopped building methanol FFVs by the late-1990s, switching their attention to ethanol-fueled vehicles. While the methanol FFV program was a technical success, rising methanol pricing in the mid- to late-1990s during a period of slumping gasoline pump prices diminished interest in methanol fuels.

In the early 1970s, a process was developed by Mobil for producing gasoline fuel from methanol.

Between the 1960s and 1980s methanol emerged as a precursor to the feedstock chemicals acetic acid and acetic anhydride. These processes include the Monsanto acetic acid synthesis, Cativa process, and Tennessee Eastman acetic anhydride process.

Analog-to-digital converter

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Analog-to-digital_converter 

4-channel stereo multiplexed analog-to-digital converter WM8775SEDS made by Wolfson Microelectronics placed on an X-Fi Fatal1ty Pro sound card

 

AD570 8-bit successive-approximation analog-to-digital converter

 

AD570/AD571 silicon die

 

INTERSIL ICL7107. 31/2 digit single-chip A/D converter

 

ICL7107 silicon die

In electronics, an analog-to-digital converter (ADC, A/D, or A-to-D) is a system that converts an analog signal, such as a sound picked up by a microphone or light entering a digital camera, into a digital signal. An ADC may also provide an isolated measurement such as an electronic device that converts an analog input voltage or current to a digital number representing the magnitude of the voltage or current. Typically the digital output is a two's complement binary number that is proportional to the input, but there are other possibilities.

There are several ADC architectures. Due to the complexity and the need for precisely matched components, all but the most specialized ADCs are implemented as integrated circuits (ICs). These typically take the form of metal–oxide–semiconductor (MOS) mixed-signal integrated circuit chips that integrate both analog and digital circuits.

A digital-to-analog converter (DAC) performs the reverse function; it converts a digital signal into an analog signal.

Explanation

An ADC converts a continuous-time and continuous-amplitude analog signal to a discrete-time and discrete-amplitude digital signal. The conversion involves quantization of the input, so it necessarily introduces a small amount of error or noise. Furthermore, instead of continuously performing the conversion, an ADC does the conversion periodically, sampling the input, limiting the allowable bandwidth of the input signal.

The performance of an ADC is primarily characterized by its bandwidth and signal-to-noise ratio (SNR). The bandwidth of an ADC is characterized primarily by its sampling rate. The SNR of an ADC is influenced by many factors, including the resolution, linearity and accuracy (how well the quantization levels match the true analog signal), aliasing and jitter. The SNR of an ADC is often summarized in terms of its effective number of bits (ENOB), the number of bits of each measure it returns that are on average not noise. An ideal ADC has an ENOB equal to its resolution. ADCs are chosen to match the bandwidth and required SNR of the signal to be digitized. If an ADC operates at a sampling rate greater than twice the bandwidth of the signal, then per the Nyquist–Shannon sampling theorem, perfect reconstruction is possible. The presence of quantization error limits the SNR of even an ideal ADC. However, if the SNR of the ADC exceeds that of the input signal, its effects may be neglected resulting in an essentially perfect digital representation of the analog input signal.

Resolution

Fig. 1. An 8-level ADC coding scheme

The resolution of the converter indicates the number of different, ie discrete, values it can produce over the allowed range of analog input values. Thus a particular resolution determines the magnitude of the quantization error and therefore determines the maximum possible signal-to-noise ratio for an ideal ADC without the use of oversampling. The input samples are usually stored electronically in binary form within the ADC, so the resolution is usually expressed as the audio bit depth. In consequence, the number of discrete values available is usually a power of two. For example, an ADC with a resolution of 8 bits can encode an analog input to one in 256 different levels (2⁸ = 256). The values can represent the ranges from 0 to 255 (i.e. as unsigned integers) or from −128 to 127 (i.e. as signed integer), depending on the application.

Resolution can also be defined electrically, and expressed in volts. The change in voltage required to guarantee a change in the output code level is called the least significant bit (LSB) voltage. The resolution Q of the ADC is equal to the LSB voltage. The voltage resolution of an ADC is equal to its overall voltage measurement range divided by the number of intervals:

${\displaystyle Q={\dfrac {E_{\mathrm {FSR} }}{2^{M}}},}$

where M is the ADC's resolution in bits and E_FSR is the full scale voltage range (also called 'span'). E_FSR is given by

${\displaystyle E_{\mathrm {FSR} }=V_{\mathrm {RefHi} }-V_{\mathrm {RefLow} },\,}$

where V_RefHi and V_RefLow are the upper and lower extremes, respectively, of the voltages that can be coded.

Normally, the number of voltage intervals is given by

${\displaystyle N=2^{M},\,}$

where M is the ADC's resolution in bits.

That is, one voltage interval is assigned in between two consecutive code levels.

Example:

• Coding scheme as in figure 1
• Full scale measurement range = 0 to 1 volt
• ADC resolution is 3 bits: 2³ = 8 quantization levels (codes)
• ADC voltage resolution, Q = 1 V / 8 = 0.125 V.

In many cases, the useful resolution of a converter is limited by the signal-to-noise ratio (SNR) and other errors in the overall system expressed as an ENOB.

Comparison of quantizing a sinusoid to 64 levels (6 bits) and 256 levels (8 bits). The additive noise created by 6-bit quantization is 12 dB greater than the noise created by 8-bit quantization. When the spectral distribution is flat, as in this example, the 12 dB difference manifests as a measurable difference in the noise floors.

Quantization error

Analog to digital conversion as shown with fig. 1 and fig. 2.

Quantization error is introduced by the quantization inherent in an ideal ADC. It is a rounding error between the analog input voltage to the ADC and the output digitized value. The error is nonlinear and signal-dependent. In an ideal ADC, where the quantization error is uniformly distributed between −1/2 LSB and +1/2 LSB, and the signal has a uniform distribution covering all quantization levels, the Signal-to-quantization-noise ratio (SQNR) is given by

${\displaystyle \mathrm {SQNR} =20\log _{10}(2^{Q})\approx 6.02\cdot Q\ \mathrm {dB} \,\!}$

where Q is the number of quantization bits. For example, for a 16-bit ADC, the quantization error is 96.3 dB below the maximum level.

Quantization error is distributed from DC to the Nyquist frequency. Consequently, if part of the ADC's bandwidth is not used, as is the case with oversampling, some of the quantization error will occur out-of-band, effectively improving the SQNR for the bandwidth in use. In an oversampled system, noise shaping can be used to further increase SQNR by forcing more quantization error out of band.

Dither

Main article: dither

In ADCs, performance can usually be improved using dither. This is a very small amount of random noise (e.g. white noise), which is added to the input before conversion. Its effect is to randomize the state of the LSB based on the signal. Rather than the signal simply getting cut off altogether at low levels, it extends the effective range of signals that the ADC can convert, at the expense of a slight increase in noise. Note that dither can only increase the resolution of a sampler. It cannot improve the linearity, and thus accuracy does not necessarily improve.

Quantization distortion in an audio signal of very low level with respect to the bit depth of the ADC is correlated with the signal and sounds distorted and unpleasant. With dithering, the distortion is transformed into noise. The undistorted signal may be recovered accurately by averaging over time. Dithering is also used in integrating systems such as electricity meters. Since the values are added together, the dithering produces results that are more exact than the LSB of the analog-to-digital converter.

Dither is often applied when quantizing photographic images to a fewer number of bits per pixel—the image becomes noisier but to the eye looks far more realistic than the quantized image, which otherwise becomes banded. This analogous process may help to visualize the effect of dither on an analog audio signal that is converted to digital.

Accuracy

An ADC has several sources of errors. Quantization error and (assuming the ADC is intended to be linear) non-linearity are intrinsic to any analog-to-digital conversion. These errors are measured in a unit called the least significant bit (LSB). In the above example of an eight-bit ADC, an error of one LSB is 1/256 of the full signal range, or about 0.4%.

Nonlinearity

All ADCs suffer from nonlinearity errors caused by their physical imperfections, causing their output to deviate from a linear function (or some other function, in the case of a deliberately nonlinear ADC) of their input. These errors can sometimes be mitigated by calibration, or prevented by testing. Important parameters for linearity are integral nonlinearity and differential nonlinearity. These nonlinearities introduce distortion that can reduce the signal-to-noise ratio performance of the ADC and thus reduce its effective resolution.

Jitter

When digitizing a sine wave ${\displaystyle x(t)=A\sin {(2\pi f_{0}t)}}$, the use of a non-ideal sampling clock will result in some uncertainty in when samples are recorded. Provided that the actual sampling time uncertainty due to clock jitter is ${\displaystyle \Delta t}$, the error caused by this phenomenon can be estimated as ${\displaystyle E_{ap}\leq |x'(t)\Delta t|\leq 2A\pi f_{0}\Delta t}$. This will result in additional recorded noise that will reduce the effective number of bits (ENOB) below that predicted by quantization error alone. The error is zero for DC, small at low frequencies, but significant with signals of high amplitude and high frequency. The effect of jitter on performance can be compared to quantization error: ${\displaystyle \Delta t<{\frac {1}{2^{q}\pi f_{0}}}}$, where q is the number of ADC bits.

Output size (bits)	Signal Frequency
	1 Hz	1 kHz	10 kHz	1 MHz	10 MHz	100 MHz	1 GHz
8	1,243 µs	1.24 µs	124 ns	1.24 ns	124 ps	12.4 ps	1.24 ps
10	311 µs	311 ns	31.1 ns	311 ps	31.1 ps	3.11 ps	0.31 ps
12	77.7 µs	77.7 ns	7.77 ns	77.7 ps	7.77 ps	0.78 ps	0.08 ps ("77.7fs")
14	19.4 µs	19.4 ns	1.94 ns	19.4 ps	1.94 ps	0.19 ps	0.02 ps ("19.4fs")
16	4.86 µs	4.86 ns	486 ps	4.86 ps	0.49 ps	0.05 ps ("48.5 fs")	–
18	1.21 µs	1.21 ns	121 ps	1.21 ps	0.12 ps	–	–
20	304 ns	304 ps	30.4 ps	0.30 ps ("303.56 fs")	0.03 ps ("30.3 fs")	–	–
24	18.9 ns	18.9 ps	1.89 ps	0.019 ps ("18.9 fs")	-	–	–

Clock jitter is caused by phase noise. The resolution of ADCs with a digitization bandwidth between 1 MHz and 1 GHz is limited by jitter. For lower bandwidth conversions such as when sampling audio signals at 44.1 kHz, clock jitter has a less significant impact on performance.

Sampling rate

Main article: Sampling rate

An analog signal is continuous in time and it is necessary to convert this to a flow of digital values. It is therefore required to define the rate at which new digital values are sampled from the analog signal. The rate of new values is called the sampling rate or sampling frequency of the converter. A continuously varying bandlimited signal can be sampled and then the original signal can be reproduced from the discrete-time values by a reconstruction filter. The Nyquist–Shannon sampling theorem implies that a faithful reproduction of the original signal is only possible if the sampling rate is higher than twice the highest frequency of the signal.

Since a practical ADC cannot make an instantaneous conversion, the input value must necessarily be held constant during the time that the converter performs a conversion (called the conversion time). An input circuit called a sample and hold performs this task—in most cases by using a capacitor to store the analog voltage at the input, and using an electronic switch or gate to disconnect the capacitor from the input. Many ADC integrated circuits include the sample and hold subsystem internally.

Aliasing

Main article: Aliasing

An ADC works by sampling the value of the input at discrete intervals in time. Provided that the input is sampled above the Nyquist rate, defined as twice the highest frequency of interest, then all frequencies in the signal can be reconstructed. If frequencies above half the Nyquist rate are sampled, they are incorrectly detected as lower frequencies, a process referred to as aliasing. Aliasing occurs because instantaneously sampling a function at two or fewer times per cycle results in missed cycles, and therefore the appearance of an incorrectly lower frequency. For example, a 2 kHz sine wave being sampled at 1.5 kHz would be reconstructed as a 500 Hz sine wave.

To avoid aliasing, the input to an ADC must be low-pass filtered to remove frequencies above half the sampling rate. This filter is called an anti-aliasing filter, and is essential for a practical ADC system that is applied to analog signals with higher frequency content. In applications where protection against aliasing is essential, oversampling may be used to greatly reduce or even eliminate it.

Although aliasing in most systems is unwanted, it can be exploited to provide simultaneous down-mixing of a band-limited high-frequency signal (see undersampling and frequency mixer). The alias is effectively the lower heterodyne of the signal frequency and sampling frequency.

Oversampling

Main article: Oversampling

For economy, signals are often sampled at the minimum rate required with the result that the quantization error introduced is white noise spread over the whole passband of the converter. If a signal is sampled at a rate much higher than the Nyquist rate and then digitally filtered to limit it to the signal bandwidth produces the following advantages:

• Oversampling can make it easier to realize analog anti-aliasing filters
• Improved audio bit depth
• Reduced noise, especially when noise shaping is employed in addition to oversampling.

Oversampling is typically used in audio frequency ADCs where the required sampling rate (typically 44.1 or 48 kHz) is very low compared to the clock speed of typical transistor circuits (>1 MHz). In this case, the performance of the ADC can be greatly increased at little or no cost. Furthermore, as any aliased signals are also typically out of band, aliasing can often be completely eliminated using very low cost filters.

Relative speed and precision

The speed of an ADC varies by type. The Wilkinson ADC is limited by the clock rate which is processable by current digital circuits. For a successive-approximation ADC, the conversion time scales with the logarithm of the resolution, i.e. the number of bits. Flash ADCs are certainly the fastest type of the three; The conversion is basically performed in a single parallel step.

There is a potential tradeoff between speed and precision. Flash ADCs have drifts and uncertainties associated with the comparator levels results in poor linearity. To a lesser extent, poor linearity can also be an issue for successive-approximation ADCs. Here, nonlinearity arises from accumulating errors from the subtraction processes. Wilkinson ADCs have the best linearity of the three.

Sliding scale principle

The sliding scale or randomizing method can be employed to greatly improve the linearity of any type of ADC, but especially flash and successive approximation types. For any ADC the mapping from input voltage to digital output value is not exactly a floor or ceiling function as it should be. Under normal conditions, a pulse of a particular amplitude is always converted to the same digital value. The problem lies in that the ranges of analog values for the digitized values are not all of the same widths, and the differential linearity decreases proportionally with the divergence from the average width. The sliding scale principle uses an averaging effect to overcome this phenomenon. A random, but known analog voltage is added to the sampled input voltage. It is then converted to digital form, and the equivalent digital amount is subtracted, thus restoring it to its original value. The advantage is that the conversion has taken place at a random point. The statistical distribution of the final levels is decided by a weighted average over a region of the range of the ADC. This in turn desensitizes it to the width of any specific level.

Types

These are several common ways of implementing an electronic ADC.

Direct-conversion

Main article: Flash ADC

A direct-conversion or flash ADC has a bank of comparators sampling the input signal in parallel, each firing for a specific voltage range. The comparator bank feeds a logic circuit that generates a code for each voltage range.

ADCs of this type have a large die size and high power dissipation. They are often used for video, wideband communications, or other fast signals in optical and magnetic storage.

The circuit consists of a resistive divider network, a set of op-amp comparators and a priority encoder. A small amount of hysteresis is built into the comparator to resolve any problems at voltage boundaries. At each node of the resistive divider, a comparison voltage is available. The purpose of the circuit is to compare the analog input voltage with each of the node voltages.

The circuit has the advantage of high speed as the conversion takes place simultaneously rather than sequentially. Typical conversion time is 100 ns or less. Conversion time is limited only by the speed of the comparator and of the priority encoder. This type of ADC has the disadvantage that the number of comparators required almost doubles for each added bit. Also, the larger the value of n, the more complex is the priority encoder.

Successive approximation

A successive-approximation ADC uses a comparator and a binary search to successively narrow a range that contains the input voltage. At each successive step, the converter compares the input voltage to the output of an internal digital to analog converter which initially represents the midpoint of the allowed input voltage range. At each step in this process, the approximation is stored in a successive approximation register (SAR) and the output of the digital to analog converter is updated for a comparison over a narrower range.

Ramp-compare

A ramp-compare ADC produces a saw-tooth signal that ramps up or down then quickly returns to zero. When the ramp starts, a timer starts counting. When the ramp voltage matches the input, a comparator fires, and the timer's value is recorded. Timed ramp converters can be implemented economically, however, the ramp time may be sensitive to temperature because the circuit generating the ramp is often a simple analog integrator. A more accurate converter uses a clocked counter driving a DAC. A special advantage of the ramp-compare system is that converting a second signal just requires another comparator and another register to store the timer value. To reduce sensitivity to input changes during conversion, a sample and hold can charge a capacitor with the instantaneous input voltage and the converter can time the time required to discharge with a constant current.

Wilkinson

The Wilkinson ADC was designed by Denys Wilkinson in 1950. The Wilkinson ADC is based on the comparison of an input voltage with that produced by a charging capacitor. The capacitor is allowed to charge until a comparator determines it matches the input voltage. Then, the capacitor is discharged linearly. The time required to discharge the capacitor is proportional to the amplitude of the input voltage. While the capacitor is discharging, pulses from a high-frequency oscillator clock are counted by a register. The number of clock pulses recorded in the register is also proportional to the input voltage.

Integrating

An integrating ADC (also dual-slope or multi-slope ADC) applies the unknown input voltage to the input of an integrator and allows the voltage to ramp for a fixed time period (the run-up period). Then a known reference voltage of opposite polarity is applied to the integrator and is allowed to ramp until the integrator output returns to zero (the run-down period). The input voltage is computed as a function of the reference voltage, the constant run-up time period, and the measured run-down time period. The run-down time measurement is usually made in units of the converter's clock, so longer integration times allow for higher resolutions. Likewise, the speed of the converter can be improved by sacrificing resolution. Converters of this type (or variations on the concept) are used in most digital voltmeters for their linearity and flexibility.

Charge balancing ADC

The principle of charge balancing ADC is to first convert the input signal to a frequency using a voltage-to-frequency converter. This frequency is then measured by a counter and converted to an output code proportional to the analog input. The main advantage of these converters is that it is possible to transmit frequency even in a noisy environment or in isolated form. However, the limitation of this circuit is that the output of the voltage-to-frequency converter depends upon an RC product whose value cannot be accurately maintained over temperature and time.

Dual-slope ADC

The analog part of the circuit consists of a high input impedance buffer, precision integrator and a voltage comparator. The converter first integrates the analog input signal for a fixed duration and then it integrates an internal reference voltage of opposite polarity until the integrator output is zero. The main disadvantage of this circuit is the long duration time. They are particularly suitable for accurate measurement of slowly varying signals such as thermocouples and weighing scales.

Delta-encoded

A delta-encoded or counter-ramp ADC has an up-down counter that feeds a digital to analog converter (DAC). The input signal and the DAC both go to a comparator. The comparator controls the counter. The circuit uses negative feedback from the comparator to adjust the counter until the DAC's output matches the input signal and number is read from the counter. Delta converters have very wide ranges and high resolution, but the conversion time is dependent on the input signal behavior, though it will always have a guaranteed worst-case. Delta converters are often very good choices to read real-world signals as most signals from physical systems do not change abruptly. Some converters combine the delta and successive approximation approaches; this works especially well when high frequency components of the input signal are known to be small in magnitude.

Pipelined

A pipelined ADC (also called subranging quantizer) uses two or more conversion steps. First, a coarse conversion is done. In a second step, the difference to the input signal is determined with a digital to analog converter (DAC). This difference is then converted more precisely, and the results are combined in the last step. This can be considered a refinement of the successive-approximation ADC wherein the feedback reference signal consists of the interim conversion of a whole range of bits (for example, four bits) rather than just the next-most-significant bit. By combining the merits of the successive approximation and flash ADCs this type is fast, has a high resolution, and can be implemented efficiently.

Sigma-delta

Main article: Delta-sigma modulation

A sigma-delta ADC (also known as a delta-sigma ADC) oversamples the incoming signal by a large factor using a smaller number of bits than required are converted using a flash ADC and filters the desired signal band. The resulting signal, along with the error generated by the discrete levels of the flash, is fed back and subtracted from the input to the filter. This negative feedback has the effect of noise shaping the quantization error that it does not appear in the desired signal frequencies. A digital filter (decimation filter) follows the ADC which reduces the sampling rate, filters off unwanted noise signal and increases the resolution of the output.

Time-interleaved

A time-interleaved ADC uses M parallel ADCs where each ADC samples data every M:th cycle of the effective sample clock. The result is that the sample rate is increased M times compared to what each individual ADC can manage. In practice, the individual differences between the M ADCs degrade the overall performance reducing the spurious-free dynamic range (SFDR). However, techniques exist to correct for these time-interleaving mismatch errors.

Intermediate FM stage

An ADC with an intermediate FM stage first uses a voltage-to-frequency converter to produce an oscillating signal with a frequency proportional to the voltage of the input signal, and then uses a frequency counter to convert that frequency into a digital count proportional to the desired signal voltage. Longer integration times allow for higher resolutions. Likewise, the speed of the converter can be improved by sacrificing resolution. The two parts of the ADC may be widely separated, with the frequency signal passed through an opto-isolator or transmitted wirelessly. Some such ADCs use sine wave or square wave frequency modulation; others use pulse-frequency modulation. Such ADCs were once the most popular way to show a digital display of the status of a remote analog sensor.

Time-stretch

A Time-stretch analog-to-digital converter (TS-ADC) digitizes a very wide bandwidth analog signal, that cannot be digitized by a conventional electronic ADC, by time-stretching the signal prior to digitization. It commonly uses a photonic preprocessor to time-stretch the signal, which effectively slows the signal down in time and compresses its bandwidth. As a result, an electronic ADC, that would have been too slow to capture the original signal, can now capture this slowed-down signal. For continuous capture of the signal, the frontend also divides the signal into multiple segments in addition to time-stretching. Each segment is individually digitized by a separate electronic ADC. Finally, a digital signal processor rearranges the samples and removes any distortions added by the preprocessor to yield the binary data that is the digital representation of the original analog signal.

Commercial

In many cases, the most expensive part of an integrated circuit is the pins, because they make the package larger, and each pin has to be connected to the integrated circuit's silicon. To save pins, it is common for ADCs to send their data one bit at a time over a serial interface to the computer, with each bit coming out when a clock signal changes state. This saves quite a few pins on the ADC package, and in many cases, does not make the overall design any more complex.

Commercial ADCs often have several inputs that feed the same converter, usually through an analog multiplexer. Different models of ADC may include sample and hold circuits, instrumentation amplifiers or differential inputs, where the quantity measured is the difference between two inputs.

Applications

Music recording

Analog-to-digital converters are integral to modern music reproduction technology and digital audio workstation-based sound recording. Music may be produced on computers using an analog recording and therefore analog-to-digital converters are needed to create the pulse-code modulation (PCM) data streams that go onto compact discs and digital music files. The current crop of analog-to-digital converters utilized in music can sample at rates up to 192 kilohertz. Many recording studios record in 24-bit/96 kHz pulse-code modulation (PCM) format and then downsample and dither the signal for Compact Disc Digital Audio production (44.1 kHz) or to 48 kHz for radio and television broadcast applications.

Digital signal processing

ADCs are required in systems that process, store, or transport virtually any analog signal in digital form. TV tuner cards, for example, use fast video analog-to-digital converters. Slow on-chip 8-, 10-, 12-, or 16-bit analog-to-digital converters are common in microcontrollers. Digital storage oscilloscopes need very fast analog-to-digital converters, also crucial for software-defined radio and their new applications.

Scientific instruments

Digital imaging systems commonly use analog-to-digital converters for digitizing pixels. Some radar systems use analog-to-digital converters to convert signal strength to digital values for subsequent signal processing. Many other in situ and remote sensing systems commonly use analogous technology.

Many sensors in scientific instruments produce an analog signal; temperature, pressure, pH, light intensity etc. All these signals can be amplified and fed to an ADC to produce a digital representation.

Rotary encoder

Some non-electronic or only partially electronic devices, such as rotary encoders, can also be considered ADCs. Typically the digital output of an ADC will be a two's complement binary number that is proportional to the input. An encoder might output a Gray code.

Displaying

Flat panel displays are inherently digital and need an ADC to process an analog signal such as composite or VGA.

Electrical symbol

Testing

Testing an analog-to-digital converter requires an analog input source and hardware to send control signals and capture digital data output. Some ADCs also require an accurate source of reference signal.

The key parameters to test an ADC are:

1. DC offset error
2. DC gain error
3. signal-to-noise ratio (SNR)
4. Total harmonic distortion (THD)
5. Integral nonlinearity (INL)
6. Differential nonlinearity (DNL)
7. Spurious free dynamic range
8. Power dissipation