A method for the patterning and control of single electrons on a surface is provided that includes implementing scanning tunneling microscopy hydrogen lithography with a scanning probe microscope to form charge structures with one or more confined charges; performing a series of field-free atomic force microscopy measurements on the charge structures with different tip heights, where interaction between the tip and the confined charge are elucidated; and adjusting tip heights to controllably position charges within the structures to write a given charge state. The present disclose also provides a Gibb's distribution machine formed with the method for the patterning and control of single electrons on a surface. A multi bit true random number generator and neural network learning hardware formed with the above described method are also provided.

A method for the patterning and control of single electrons on a surface is provided that includes implementing scanning tunneling microscopy hydrogen lithography with a scanning probe microscope to form charge structures with one or more confined charges; performing a series of field-free atomic force microscopy measurements on the charge structures with different tip heights, where interaction between the tip and the confined charge are elucidated; and adjusting tip heights to controllably position charges within the structures to write a given charge state. The present disclose also provides a Gibb's distribution machine formed with the method for the patterning and control of single electrons on a surface. A multi bit true random number generator and neural network learning hardware formed with the above described method are also provided.

In the system and method disclosed, an ultrahigh vacuum (UHV) scanning tunneling microscope (STM) tip is used to selectively desorb hydrogen atoms from the Si(100)-2X1:H surface by injecting electrons at a negative sample bias voltage. A new lithography method is disclosed that allows the STM to operate under imaging conditions and simultaneously desorb H atoms as required. A high frequency signal is added to the negative sample bias voltage to deliver the required energy for hydrogen removal. The resulted current at this frequency and its harmonics are filtered to minimize their effect on the operation of the STM's feedback loop. This approach offers a significant potential for controlled and precise removal of hydrogen atoms from a hydrogen-terminated silicon surface and thus may be used for the fabrication of practical silicon-based atomic-scale devices.

In the system and method disclosed, an ultrahigh vacuum (UHV) scanning tunneling microscope (STM) tip is used to selectively desorb hydrogen atoms from the Si(100)-2X1:H surface by injecting electrons at a negative sample bias voltage. A new lithography method is disclosed that allows the STM to operate under imaging conditions and simultaneously desorb H atoms as required. A high frequency signal is added to the negative sample bias voltage to deliver the required energy for hydrogen removal. The resulted current at this frequency and its harmonics are filtered to minimize their effect on the operation of the STM's feedback loop. This approach offers a significant potential for controlled and precise removal of hydrogen atoms from a hydrogen-terminated silicon surface and thus may be used for the fabrication of practical silicon-based atomic-scale devices.

A semiconductor carrier profiling method utilizes a scanning tunneling microscope and shielded probe with an attached spectrum analyzer to measure power loss of a microwave frequency comb generated in a tunneling junction. From this power loss and by utilizing an equivalent circuit or other model, spreading resistance may be determined and carrier density from the spreading resistance. The methodology is non-destructive of the sample and allows scanning across the surface of the sample. By not being destructive, additional analysis methods, like deconvolution, are available for use.

A semiconductor carrier profiling method utilizes a scanning tunneling microscope and shielded probe with an attached spectrum analyzer to measure power loss of a microwave frequency comb generated in a tunneling junction. From this power loss and by utilizing an equivalent circuit or other model, spreading resistance may be determined and carrier density from the spreading resistance. The methodology is non-destructive of the sample and allows scanning across the surface of the sample. By not being destructive, additional analysis methods, like deconvolution, are available for use.

This disclosure relates to automatic determination of locations of one or more closely spaced donor atoms implanted into a semiconductor crystal lattice. A processor receives image data generated by a scanning tunnelling microscope (STM). The image data is indicative of a tunnelling current between a scanning tip and the crystal lattice at multiple image locations. The processor applies a trained machine learning model to the image data to determine a classification into one of multiple candidate configurations of the one or more donor atoms. The multiple candidate configurations relate to different locations of the one or more donor atoms in the semiconductor crystal lattice. Based on an output of the trained machine learning model, the processor determines the location of the one or more donor atoms in the semiconductor crystal lattice.

A scanning probe microscope includes: a pump light output unit that emits pump light having a first specified phase to a specimen and performs emission of the pump light a plurality of number of times to excite the specimen; a probe light output unit that emits probe light having a second specified phase to the specimen once while the specimen is excited by one-time emission of the pump light; and a scanning probe that detects, from the specimen, a probe signal corresponding to each one-time emission of the probe light, wherein the pump light output unit or the probe light output unit includes a delay time adjustment unit that adjusts delay time from a start of the emission of the pump light until a start of the emission of the probe light.

A scanning probe microscope includes: a pump light output unit that emits pump light having a first specified phase to a specimen and performs emission of the pump light a plurality of number of times to excite the specimen; a probe light output unit that emits probe light having a second specified phase to the specimen once while the specimen is excited by one-time emission of the pump light; and a scanning probe that detects, from the specimen, a probe signal corresponding to each one-time emission of the probe light, wherein the pump light output unit or the probe light output unit includes a delay time adjustment unit that adjusts delay time from a start of the emission of the pump light until a start of the emission of the probe light.

A method for autonomously applying a dangling bond pattern to a substrate for atom scale device fabrication includes inputting the pattern, initiating a patterning process, scanning the substrate using a scanning probe microscope (SPM) to generate an SPM image of the substrate, feeding the SPM image into a trained convolution neural network (CNN), analyzing the SPM image using the CNN to identify substrate defects, determining a defect free substrate area for pattern application; and applying the pattern to the substrate in that area. An atom scale electronic component includes functional patches on a substrate and wires electrically connecting the functional patches. Training a CNN includes recording a Scanning Tunneling Microscope (STM) image of the substrate, extracting images of defects from the STM image, labeling pixel-wise the defect images, and feeding the extracted and labeled images of defects into a CNN to train the CNN for semantic segmentation.