Analyzing the surface passivity effect of germanium oxynitride:a comprehensive approach through first principles simulation and interface state density

High-purity germanium(HPGe)detectors,which are used for direct dark matter detection,have the advantages of a low threshold and excellent energy resolution.The surface passivation of HPGe has become crucial for achieving an extremely low energy threshold.In this study,first-principles simulations,passivation film preparation,and metal oxide semiconductor(MOS)capacitor characterization were combined to study surface passivation.Theoretical calculations of the energy band structure of the -H,-OH,and -NH_(2) passivation groups on the surface of Ge were performed,and the interface state density and potential with five different passivation groups with N/O atomic ratios were accurately analyzed to obtain a stable surface state.Based on the theoretical calculation results,the surface passivation layers of the Ge_(2)ON_(2) film were prepared via magnetron sputtering in accordance with the optimum atomic ratio structure.The microstructure,C-V,and I-V electrical properties of the layers,and the passivation effect of the Al/Ge_(2)ON_(2)/Ge MOS were characterized to test the interface state density.The mean interface state density obtained by the Terman method was 8.4×10^(11) cm^(-2) eV^(-1).The processing of germanium oxynitrogen passivation films is expected to be used in direct dark matter detection of the HPGe detector surface passivation technology to reduce the detector leakage currents.

Strategyproof Facility Location with Limited Locations

We study the mechanism design of facility location problems.The problem is to design mechanisms to select a set of locations on which to build a set of facilities,aiming to optimize some system objective and achieve desirable properties based on the strategic agents'locations.The agents might have incentives to misreport their private locations,in order to minimize the costs(i.e.,the distance from the closest facility).We study the setting with limited locations,that is,the facilities can only be built on a given finite set of candidate locations,rather than the whole space.For locating a single facility and two facilities on a real line,we propose strategyproof mechanisms with tight approximation ratios,under the objectives of minimizing the total cost and the maximum cost.Further,we consider the problem of locating an obnoxious facility from which the agents want to stay as far away as possible,and derive tight bounds on the approximation ratio of strategyproof mechanisms.

Approximation Algorithms on k-Correlation Clustering

In this paper,we consider the k-correlation clustering problem.Given an edge-weighted graph G(V,E)where the edges are labeled either“+”(similar)or“−”(different)with nonnegative weights,we want to partition the nodes into at most k-clusters to maximize agreements—the total weights of“+”edges within clusters and“−”edges between clusters.This problem is NP-hard.We design an approximation algorithm with the approximation ratio{a,(2-k)a+k-1/k},where a is the weighted proportion of“+”edges in all edges.As a varies from 0 to 1,the approximation ratio varies from k-1/k to 1 and the minimum value is 1/2.

Approximation Algorithms on k-Cycle Transversal and k-Clique Transversal

Given a weighted graph G=(V,E)with weight w:E→Z+,a k-cycle transversal is an edge subset A of E such that G−A has no k-cycle.The minimum weight of kcycle transversal is the weighted transversal number on k-cycle,denoted byτk(Gw).In this paper,we design a(k−1/2)-approximation algorithm for the weighted transversal number on k-cycle when k is odd.Given a weighted graph G=(V,E)with weight w:E→Z+,a k-clique transversal is an edge subset A of E such that G−A has no k-clique.The minimum weight of k-clique transversal is the weighted transversal number on k-clique,denoted byτapproximation algorithm for the weighted transversal number on k(Gw).In this paper,we design a(k2−k−1)/2-k-clique.Last,we discuss the relationship between k-clique covering and k-clique packing in complete graph Kn.