Memory Cell Programming With Analog Verification and One Extra Pulse
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing memory cell programming methods, such as selective slow programming convergence (SSPC), while improving threshold voltage distributions, incur additional time and complexity due to the need to apportion memory cells into different subsets for each programming pulse, and may result in some cells not reaching their intended threshold voltages.
Innovation Solution
Implementing an enhanced programming method that combines analog verification after one programming pulse and digital verification after subsequent pulses, with data line voltage levels adjusted based on memory cell current levels, allowing for efficient correction of cells not reaching their intended threshold voltages using only one additional pulse.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If selective slow programming convergence (SSPC) is used to improve threshold voltage distributions, then manufacturing precision is improved, but device complexity and programming time increase due to the need to apportion memory cells into different subsets for each programming pulse
Solution Approach 1:
The patent segments the verification process into two distinct phases: analog verification performed after the first programming pulse to identify cells needing additional programming, and digital verification performed after subsequent pulses to confirm final threshold voltage states. This segmentation allows the complex verification task to be divided into manageable stages, reducing the complexity of tracking individual cell states throughout the entire programming process.
Solution Approach 2:
The patent applies partial verification at intermediate stages (analog verification after the first pulse) rather than waiting until the end of programming. This partial action allows the system to identify and correct cells that fail to reach their target threshold voltages early in the process, avoiding the need for excessive verification steps later and simplifying the overall programming sequence.
2Manufacturing precision
If selective slow programming convergence (SSPC) is used to improve threshold voltage distributions, then manufacturing precision is improved, but loss of time increases due to additional programming pulses and verification steps
Solution Approach 1:
The patent performs preliminary analog verification after the first programming pulse to identify cells that have not reached their intended threshold voltages. This preliminary action allows the system to prepare correction programming pulses in advance for only the affected cells, rather than requiring all cells to undergo the full programming sequence, thereby reducing overall programming time while maintaining precision.
Solution Approach 2:
The patent implements feedback through the analog verification step, where the threshold voltage distribution of programmed cells is measured and used to determine which cells require additional programming pulses. This feedback mechanism allows the programming process to adapt dynamically, applying additional pulses only to cells that need them, thus minimizing time loss while ensuring manufacturing precision.
3Manufacturing precision
If selective slow programming convergence (SSPC) is used to improve threshold voltage distributions, then manufacturing precision is improved, but reliability decreases because some cells may not reach their intended threshold voltages
Solution Approach 1:
The patent uses feedback from analog verification to identify cells that fail to reach their target threshold voltages. This feedback information is then used to selectively apply additional programming pulses only to those unreliable cells, ensuring that all cells achieve their intended threshold voltage states and improving overall programming reliability while maintaining the precision benefits of SSPC.
Solution Approach 2:
The patent enables the programming system to self-diagnose and self-correct by using analog verification to automatically identify cells that did not reach their target states. The system then automatically applies correction programming pulses to these cells without external intervention, ensuring reliable programming completion while maintaining the precision advantages of the SSPC approach.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces errors by ensuring memory cells reach their desired threshold voltages efficiently, minimizing the need for additional programming pulses and simplifying the verification process.
Implementation Method 1
Changes in threshold voltage (Vt) of the memory cells, through programming (which is often referred to as writing) of charge storage structures (e.g., floating gates or charge traps)
Implementation Method 2
programming (which is often referred to as writing) of charge storage structures (e.g., floating gates or charge traps)
Data Source
AI summary
Memories might include a controller configured to cause the memory to apply a programming pulse to a memory cell, determine whether a threshold voltage level of the memory cell is higher than a first threshold and determine whether the threshold voltage level of the memory cell is lower than a second threshold that is lower than the first threshold, apply a first voltage level to a corresponding data line of the memory cell having a voltage level selected in response to whether the threshold voltage level of the memory cell is higher than the first threshold, lower than the second threshold, or neither higher than the first threshold nor lower than the second threshold, and apply a subsequent programming pulse to the memory cell while applying the first voltage level to the corresponding data line of the memory cell.