A novel STM for quality atomic resolution with piezoelectric motor of high compactness and simplicity.

Scanning tunneling microscope (STM) is a renowned scientific tool for obtaining high-resolution atomic images of materials. Herein, we present an innovative design of the scanning unit with a compact yet powerful inertial piezoelectric motor inspired by the Spider Drive motor principle. The scanning unit mainly consists of a small 9 mm long piezoelectric tube scanner (PTS), one end of which is coaxially connected to the main sapphire body of the STM. Of particular emphasis in this design is the piezoelectric shaft (PS), constructed from piezoelectric material instead of conventional metallic or zirconium materials. The PS is a rectangular piezoelectric stack composed of two piezoelectric plates, which are elastically clamped on the inner wall of the PTS via a spring strip. The PTS and PS expand and contract independently with each other to improve the inertial force and reduce the threshold voltage. To ensure the stability of the PS and balance the stepping performance of the inertial motor, a counterweight, and a matching conical spring are fixed at the tail of the PS. This innovative design allows for the assessment of scanning unit performance by applying a driving signal, threshold voltage is 50 V at room temperature. Step sizes vary from 0.1 to 1 µm by changing the driving signal at room temperature. Furthermore, we successfully obtained atomic-resolution images of a highly oriented pyrolytic graphite (HOPG) sample and low drift rates of 23.4 pm/min and 34.6 pm/min in X-Y plane and Z direction, respectively, under ambient conditions. This small, compact STM unit has the potential for the development of a rotatable STM for use in cryogen-free magnets, and superconducting magnets.

Atomic resolution imaging using a novel, compact and stiff scanning tunnelling microscope in cryogen-free superconducting magnet.

We present the design and performance of a novel scanning tunnelling microscope (STM) operating in a cryogen-free superconducting magnet. Our home-built STM head is compact (51.5 mm long and 20 mm in diameter) and has a single arm that provides complete openness in the scanning area between the tip and sample. The STM head consists of two piezoelectric tubes (PTs), a piezoelectric scanning tube (PST) mounted on a well-polished zirconia shaft, and a large PT housed in a sapphire tube called the motor tube. The main body of the STM head is made of tantalum. In this design, we fixed the sapphire tube to the frame with screws so that the tube's position can be changed quickly. To analyse the stiffness of the STM head unit, we identified the lowest eigenfrequencies with 3 and 4 kHz in the bending modes, 8 kHz in a torsional mode, and 9 kHz in a longitudinal mode by finite element analysis, and also measured the low drift rates in the X-Y plane and in the Z direction. The high performance of the home-built STM was demonstrated by images of the hexagonal graphite lattice at 300 K and in a sweeping magnetic field from 0 T to 9 T. Our results confirm the high stability, vibration resistance, insensitivity to high magnetic fields and the application potential of our newly developed STM for the investigation of low-frequency systems with high static support stiffness in physics, chemistry, material and biological sciences.

A fuzzy parametric model for decision making involving F-OWA operator with unknown weights environment.

Weight determining of attributes is an important factor in decision support systems since it corresponds to the relative importance of each criteria which is necessary to be determined since all the attributes aren't equally important. The aim of this paper is to put forward a method for multi Criteria decision making (MCDM) problems based on three trapezoidal fuzzy numbers under completely unknown weights environment. Based on the idea that the attribute with a larger deviation value among alternatives should be assigned a larger weight, an optimization model based on maximizing deviation method is established. F-OWA is considered to be vastly superior from the existing operators which usually take into account only the relative significance of decision makers. F-OWA operator considers not only the ratings of attribute values but also their ordered position that is it not only signifies the decision makers but also values the individual assessments. We utilize fuzzy ordered weighted averaging (F-OWA) operator to compute the collective overall preference value of each alternative and select the most desirable one according to their expected score values. The presented method is more generalized since we have used TTFNs, which are more effective in capturing uncertainty than IT2FS, just like triangular fuzzy numbers have a better representational power than simple interval numbers. Moreover, an illustrative example is given for the justification of the proposed technique.