The present invention relates to a method for referencing a near-field measurement, e.g. in a scanning probe microscope.

The present disclosure relates to a method for analyzing an electrode for a battery, which has the advantage of being capable of more easily distinguishing between the constituent materials of the electrode such as the electrode active material, the conductive material, and the pores, by using scanning spreading resistance microscopy.

The present disclosure relates to a method for analyzing an electrode for a battery, which has the advantage of being capable of more easily distinguishing between the constituent materials of the electrode such as the electrode active material, the conductive material, and the pores, by using scanning spreading resistance microscopy.

The invention relates to a measuring device for a scanning probe microscope that includes a sample receptacle which is configured to receive a measurement sample to be examined, a measuring probe which is arranged on a probe holder and has a probe tip with which the measurement sample can be measured. A displacement device is configured to move the measuring probe and the sample receptacle relative to each other, in order to measure the measurement sample, such that the measuring probe, in order to measure the measurement sample, executes a raster movement relative to said measurement sample in at least one spatial direction. Movement measurement signals indicating a first movement component in a first spatial direction that disrupts the raster movement and a second movement component in a second spatial direction that disrupts the raster movement, which second spatial direction extends transversely to the first spatial direction. Compensating control signal components cause a first countermovement which substantially compensates for the first disruptive movement component in the first spatial direction, and/or cause a second countermovement which substantially compensates for the second disruptive movement component in the second spatial direction.

The invention relates to a measuring device for a scanning probe microscope that includes a sample receptacle which is configured to receive a measurement sample to be examined, a measuring probe which is arranged on a probe holder and has a probe tip with which the measurement sample can be measured. A displacement device is configured to move the measuring probe and the sample receptacle relative to each other, in order to measure the measurement sample, such that the measuring probe, in order to measure the measurement sample, executes a raster movement relative to said measurement sample in at least one spatial direction. Movement measurement signals indicating a first movement component in a first spatial direction that disrupts the raster movement and a second movement component in a second spatial direction that disrupts the raster movement, which second spatial direction extends transversely to the first spatial direction. Compensating control signal components cause a first countermovement which substantially compensates for the first disruptive movement component in the first spatial direction, and/or cause a second countermovement which substantially compensates for the second disruptive movement component in the second spatial direction.

An atomic force microscope equipped with an optical measurement device is disclosed. An atomic force microscope equipped with an optical measurement device which acquires characteristics of a surface of a measurement target by moving a probe along the surface of the measurement target while scanning the measurement target on an XY plane using an XY scanner for supporting the measurement target, includes: an optical measurement device including a lighting unit configured to allow light to enter the surface of the measurement target, and a detection unit configured to detect light reflected by the surface of the measurement target, the optical measurement device being configured to acquire the characteristics of the surface of the measurement target by the scanning by the XY scanner; and a control device configured to control an operation of the atomic force microscope and an operation of the optical measurement device.

A dialysis system is provided that includes a dialysis machine and a potassium sensing device that is configured to measure the concentration of potassium in the patient's blood, in spent dialysate resulting from treating the patient, or in both. The potassium sensing device can be configured to generate a sensed value of the concentration of potassium. A control and computing unit, including a processor and a memory, is configured to receive the sensed value, compare the value with one or more values stored in the memory, and generate a control signal based on the comparison. A potassium infusion circuit uses the control signal to infuse supplemental potassium solution into the treatment dialysate, a replacement fluid, or both. The memory can include stored patient-historical and population data.

A dialysis system is provided that includes a dialysis machine and a potassium sensing device that is configured to measure the concentration of potassium in the patient's blood, in spent dialysate resulting from treating the patient, or in both. The potassium sensing device can be configured to generate a sensed value of the concentration of potassium. A control and computing unit, including a processor and a memory, is configured to receive the sensed value, compare the value with one or more values stored in the memory, and generate a control signal based on the comparison. A potassium infusion circuit uses the control signal to infuse supplemental potassium solution into the treatment dialysate, a replacement fluid, or both. The memory can include stored patient-historical and population data.

A method comprises using an atomic-force microscope, acquiring a set of images associated with surfaces, and, using a machine-learning algorithm applied to the images, classifying the surfaces. As a particular example, the classification can be done in a way that relies on surface parameters derived from the images rather than using the images directly.

A method comprises using an atomic-force microscope, acquiring a set of images associated with surfaces, and, using a machine-learning algorithm applied to the images, classifying the surfaces. As a particular example, the classification can be done in a way that relies on surface parameters derived from the images rather than using the images directly.