Limits...
Dynamic-load-enabled ultra-low power multiple-state RRAM devices.

Yang X, Chen IW - Sci Rep (2012)

Bottom Line: Bipolar resistance-switching materials allowing intermediate states of wide-varying resistance values hold the potential of drastically reduced power for non-volatile memory.This approach is entirely scalable and applicable to other bipolar RRAM with intermediate states.The projected power is 12 nW for a 100 × 100 nm(2) device and 500 pW for a 10 × 10 nm(2) device.

View Article: PubMed Central - PubMed

Affiliation: Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104-6272, USA.

ABSTRACT
Bipolar resistance-switching materials allowing intermediate states of wide-varying resistance values hold the potential of drastically reduced power for non-volatile memory. To exploit this potential, we have introduced into a nanometallic resistance-random-access-memory (RRAM) device an asymmetric dynamic load, which can reliably lower switching power by orders of magnitude. The dynamic load is highly resistive during on-switching allowing access to the highly resistive intermediate states; during off-switching the load vanishes to enable switching at low voltage. This approach is entirely scalable and applicable to other bipolar RRAM with intermediate states. The projected power is 12 nW for a 100 × 100 nm(2) device and 500 pW for a 10 × 10 nm(2) device. The dynamic range of the load can be increased to allow power to be further decreased by taking advantage of the exponential decay of wave-function in a newly discovered nanometallic random material, reaching possibly 1 pW for a 10×10 nm(2) nanometallic RRAM device.

No MeSH data available.


Related in: MedlinePlus

Scaling behavior of off-switching power consumption in literature (triangles) and in this work (filled circles) using asymmetric load for devices of two thickness, 10 nm (blue) and 17 nm (red).Extrapolation (dash line) gives 12 nW and 500 pW for 100×100 nm2 device and 10×10 nm2 device, respectively (10 nm thick), and 1.5 nW and 60 pW for their 17 nm counterparts. See Supplementary Information for details of literature data. All power data are calculated from , where Voff is off-switching voltage and Ron is off-switching resistance at Voff.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3473363&req=5

f1: Scaling behavior of off-switching power consumption in literature (triangles) and in this work (filled circles) using asymmetric load for devices of two thickness, 10 nm (blue) and 17 nm (red).Extrapolation (dash line) gives 12 nW and 500 pW for 100×100 nm2 device and 10×10 nm2 device, respectively (10 nm thick), and 1.5 nW and 60 pW for their 17 nm counterparts. See Supplementary Information for details of literature data. All power data are calculated from , where Voff is off-switching voltage and Ron is off-switching resistance at Voff.

Mentions: Power consumption is a key issue for electron devices including resistive random access memory (RRAM), which has attributes of high density, fast write/read speed, fatigue endurance and long retention1. In a RRAM, on-switching (also called set-switching) consumes relatively little power because the current is limited by the relatively high (off) resistance. So the power consumption is dictated by off-switching (also called reset-switching) which has a relatively low (on) resistance. Off-switching power should be proportional to the area of the resistance cell if the voltage/current density required to trigger switching is independent of the area. Indeed, literature data of off-switching power of some 20 RRAMs shown in Figure 1 support such a “scaling law”: they vary from the mW range for micrometer-sized devices to the μW range for nanometer-sized devices2345678910111213141516171819202122. Recognizing such a trend, our goal here is to systematically seek scalable strategies to further lower the power for RRAM off-switching. Our power data and the scaling prediction are summarized in Figure 1.


Dynamic-load-enabled ultra-low power multiple-state RRAM devices.

Yang X, Chen IW - Sci Rep (2012)

Scaling behavior of off-switching power consumption in literature (triangles) and in this work (filled circles) using asymmetric load for devices of two thickness, 10 nm (blue) and 17 nm (red).Extrapolation (dash line) gives 12 nW and 500 pW for 100×100 nm2 device and 10×10 nm2 device, respectively (10 nm thick), and 1.5 nW and 60 pW for their 17 nm counterparts. See Supplementary Information for details of literature data. All power data are calculated from , where Voff is off-switching voltage and Ron is off-switching resistance at Voff.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3473363&req=5

f1: Scaling behavior of off-switching power consumption in literature (triangles) and in this work (filled circles) using asymmetric load for devices of two thickness, 10 nm (blue) and 17 nm (red).Extrapolation (dash line) gives 12 nW and 500 pW for 100×100 nm2 device and 10×10 nm2 device, respectively (10 nm thick), and 1.5 nW and 60 pW for their 17 nm counterparts. See Supplementary Information for details of literature data. All power data are calculated from , where Voff is off-switching voltage and Ron is off-switching resistance at Voff.
Mentions: Power consumption is a key issue for electron devices including resistive random access memory (RRAM), which has attributes of high density, fast write/read speed, fatigue endurance and long retention1. In a RRAM, on-switching (also called set-switching) consumes relatively little power because the current is limited by the relatively high (off) resistance. So the power consumption is dictated by off-switching (also called reset-switching) which has a relatively low (on) resistance. Off-switching power should be proportional to the area of the resistance cell if the voltage/current density required to trigger switching is independent of the area. Indeed, literature data of off-switching power of some 20 RRAMs shown in Figure 1 support such a “scaling law”: they vary from the mW range for micrometer-sized devices to the μW range for nanometer-sized devices2345678910111213141516171819202122. Recognizing such a trend, our goal here is to systematically seek scalable strategies to further lower the power for RRAM off-switching. Our power data and the scaling prediction are summarized in Figure 1.

Bottom Line: Bipolar resistance-switching materials allowing intermediate states of wide-varying resistance values hold the potential of drastically reduced power for non-volatile memory.This approach is entirely scalable and applicable to other bipolar RRAM with intermediate states.The projected power is 12 nW for a 100 × 100 nm(2) device and 500 pW for a 10 × 10 nm(2) device.

View Article: PubMed Central - PubMed

Affiliation: Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104-6272, USA.

ABSTRACT
Bipolar resistance-switching materials allowing intermediate states of wide-varying resistance values hold the potential of drastically reduced power for non-volatile memory. To exploit this potential, we have introduced into a nanometallic resistance-random-access-memory (RRAM) device an asymmetric dynamic load, which can reliably lower switching power by orders of magnitude. The dynamic load is highly resistive during on-switching allowing access to the highly resistive intermediate states; during off-switching the load vanishes to enable switching at low voltage. This approach is entirely scalable and applicable to other bipolar RRAM with intermediate states. The projected power is 12 nW for a 100 × 100 nm(2) device and 500 pW for a 10 × 10 nm(2) device. The dynamic range of the load can be increased to allow power to be further decreased by taking advantage of the exponential decay of wave-function in a newly discovered nanometallic random material, reaching possibly 1 pW for a 10×10 nm(2) nanometallic RRAM device.

No MeSH data available.


Related in: MedlinePlus